diff --git a/.ipynb_checkpoints/PrepareModelBenchmark-checkpoint.ipynb b/.ipynb_checkpoints/PrepareModelBenchmark-checkpoint.ipynb index e12d8ba..fb14865 100644 --- a/.ipynb_checkpoints/PrepareModelBenchmark-checkpoint.ipynb +++ b/.ipynb_checkpoints/PrepareModelBenchmark-checkpoint.ipynb @@ -338,9 +338,11 @@ }, { "cell_type": "code", - "execution_count": 18, - "id": "19fcd4ea", - "metadata": {}, + "execution_count": 189, + "id": "f5774456", + "metadata": { + "scrolled": false + }, "outputs": [ { "data": { @@ -348,41 +350,49 @@ "30704" ] }, - "execution_count": 18, + "execution_count": 189, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "len(X)" + "len(y)" ] }, { "cell_type": "code", - "execution_count": 19, - "id": "f5774456", - "metadata": { - "scrolled": false - }, + "execution_count": 190, + "id": "130517cb", + "metadata": {}, + "outputs": [], + "source": [ + "X = X[:len(X)-(len(X)%30)]" + ] + }, + { + "cell_type": "code", + "execution_count": 191, + "id": "19fcd4ea", + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "30704" + "30690" ] }, - "execution_count": 19, + "execution_count": 191, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "len(y)" + "len(X)" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 192, "id": "4098afde", "metadata": {}, "outputs": [], @@ -392,7 +402,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 193, "id": "799eec56", "metadata": {}, "outputs": [], @@ -402,7 +412,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 194, "id": "07af109c", "metadata": {}, "outputs": [ @@ -412,7 +422,7 @@ "(30704, 26)" ] }, - "execution_count": 22, + "execution_count": 194, "metadata": {}, "output_type": "execute_result" } @@ -423,17 +433,17 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 195, "id": "8bf41012", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(30704, 42, 3)" + "(30690, 42, 3)" ] }, - "execution_count": 23, + "execution_count": 195, "metadata": {}, "output_type": "execute_result" } @@ -444,7 +454,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 196, "id": "a524cb3f", "metadata": {}, "outputs": [], @@ -462,28 +472,28 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 197, "id": "b991ee9a", "metadata": {}, "outputs": [], "source": [ - "batch_size = 16\n", + "batch_size = 30\n", "X_total_batch, y_total_batch = batch_generate(X_total, y_total, batch_size)" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 198, "id": "f59d541f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(1919, 16, 42, 3)" + "(1023, 30, 42, 3)" ] }, - "execution_count": 26, + "execution_count": 198, "metadata": {}, "output_type": "execute_result" } @@ -494,7 +504,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 199, "id": "1f845381", "metadata": {}, "outputs": [], @@ -504,7 +514,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 200, "id": "00612e36", "metadata": {}, "outputs": [], @@ -514,17 +524,17 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 201, "id": "118e86a9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(1919, 26)" + "(1023, 26)" ] }, - "execution_count": 29, + "execution_count": 201, "metadata": {}, "output_type": "execute_result" } @@ -535,7 +545,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 202, "id": "f8620c6b", "metadata": {}, "outputs": [], @@ -545,7 +555,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 203, "id": "43cecf26", "metadata": {}, "outputs": [], @@ -555,17 +565,17 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 204, "id": "a86cfe2b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(1535, 16, 42, 3)" + "(818, 30, 42, 3)" ] }, - "execution_count": 32, + "execution_count": 204, "metadata": {}, "output_type": "execute_result" } @@ -576,7 +586,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 205, "id": "8add1291", "metadata": {}, "outputs": [], @@ -586,17 +596,17 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 206, "id": "19d57590", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(384, 16, 42, 3)" + "(205, 30, 42, 3)" ] }, - "execution_count": 34, + "execution_count": 206, "metadata": {}, "output_type": "execute_result" } @@ -607,17 +617,17 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 207, "id": "672571a1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(1535, 26)" + "(818, 26)" ] }, - "execution_count": 35, + "execution_count": 207, "metadata": {}, "output_type": "execute_result" } @@ -628,17 +638,17 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 208, "id": "cc3d2b9e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(384, 26)" + "(205, 26)" ] }, - "execution_count": 36, + "execution_count": 208, "metadata": {}, "output_type": "execute_result" } @@ -649,7 +659,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 209, "id": "6c5b0479", "metadata": {}, "outputs": [], @@ -662,7 +672,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 210, "id": "a3dba74d", "metadata": {}, "outputs": [], @@ -674,7 +684,7 @@ }, { "cell_type": "code", - "execution_count": 241, + "execution_count": 211, "id": "493e3f91", "metadata": {}, "outputs": [], @@ -685,7 +695,62 @@ }, { "cell_type": "code", - "execution_count": 242, + "execution_count": 212, + "id": "6db54471", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"sequential_11\"\n", + "_________________________________________________________________\n", + " Layer (type) Output Shape Param # \n", + "=================================================================\n", + " conv2d_44 (Conv2D) (None, 30, 42, 32) 896 \n", + " \n", + " max_pooling2d_33 (MaxPoolin (None, 15, 21, 32) 0 \n", + " g2D) \n", + " \n", + " conv2d_45 (Conv2D) (None, 13, 19, 64) 18496 \n", + " \n", + " max_pooling2d_34 (MaxPoolin (None, 6, 9, 64) 0 \n", + " g2D) \n", + " \n", + " conv2d_46 (Conv2D) (None, 4, 7, 128) 73856 \n", + " \n", + " conv2d_47 (Conv2D) (None, 2, 5, 256) 295168 \n", + " \n", + " max_pooling2d_35 (MaxPoolin (None, 1, 2, 256) 0 \n", + " g2D) \n", + " \n", + " flatten_11 (Flatten) (None, 512) 0 \n", + " \n", + " dense_33 (Dense) (None, 128) 65664 \n", + " \n", + " dropout_22 (Dropout) (None, 128) 0 \n", + " \n", + " dense_34 (Dense) (None, 64) 8256 \n", + " \n", + " dropout_23 (Dropout) (None, 64) 0 \n", + " \n", + " dense_35 (Dense) (None, 26) 1690 \n", + " \n", + "=================================================================\n", + "Total params: 464,026\n", + "Trainable params: 464,026\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 213, "id": "912211ea", "metadata": {}, "outputs": [ @@ -693,66 +758,546 @@ "name": "stdout", "output_type": "stream", "text": [ - "Epoch 1/25\n", - "39/39 [==============================] - 1s 22ms/step - loss: 3.8358 - categorical_accuracy: 0.1474 - val_loss: 2.2882 - val_categorical_accuracy: 0.2964\n", - "Epoch 2/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 1.8303 - categorical_accuracy: 0.4088 - val_loss: 1.1405 - val_categorical_accuracy: 0.6287\n", - "Epoch 3/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 1.0971 - categorical_accuracy: 0.6319 - val_loss: 0.5824 - val_categorical_accuracy: 0.8371\n", - "Epoch 4/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.6238 - categorical_accuracy: 0.7997 - val_loss: 0.3655 - val_categorical_accuracy: 0.8958\n", - "Epoch 5/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.4290 - categorical_accuracy: 0.8664 - val_loss: 0.1786 - val_categorical_accuracy: 0.9544\n", - "Epoch 6/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.2688 - categorical_accuracy: 0.9112 - val_loss: 0.1541 - val_categorical_accuracy: 0.9446\n", - "Epoch 7/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.2510 - categorical_accuracy: 0.9153 - val_loss: 0.1166 - val_categorical_accuracy: 0.9707\n", - "Epoch 8/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.1872 - categorical_accuracy: 0.9349 - val_loss: 0.0951 - val_categorical_accuracy: 0.9805\n", - "Epoch 9/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.1357 - categorical_accuracy: 0.9560 - val_loss: 0.0703 - val_categorical_accuracy: 0.9805\n", - "Epoch 10/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.1229 - categorical_accuracy: 0.9658 - val_loss: 0.1158 - val_categorical_accuracy: 0.9674\n", - "Epoch 11/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.1400 - categorical_accuracy: 0.9495 - val_loss: 0.1316 - val_categorical_accuracy: 0.9642\n", - "Epoch 12/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.1346 - categorical_accuracy: 0.9536 - val_loss: 0.0554 - val_categorical_accuracy: 0.9935\n", - "Epoch 13/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.0929 - categorical_accuracy: 0.9682 - val_loss: 0.0938 - val_categorical_accuracy: 0.9707\n", - "Epoch 14/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.1204 - categorical_accuracy: 0.9634 - val_loss: 0.0808 - val_categorical_accuracy: 0.9674\n", - "Epoch 15/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.0921 - categorical_accuracy: 0.9731 - val_loss: 0.0670 - val_categorical_accuracy: 0.9902\n", - "Epoch 16/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.0786 - categorical_accuracy: 0.9788 - val_loss: 0.0725 - val_categorical_accuracy: 0.9902\n", - "Epoch 17/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.0562 - categorical_accuracy: 0.9853 - val_loss: 0.0962 - val_categorical_accuracy: 0.9870\n", - "Epoch 18/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.0588 - categorical_accuracy: 0.9837 - val_loss: 0.0882 - val_categorical_accuracy: 0.9902\n", - "Epoch 19/25\n", - "39/39 [==============================] - 1s 20ms/step - loss: 0.0830 - categorical_accuracy: 0.9723 - val_loss: 0.0757 - val_categorical_accuracy: 0.9902\n", - "Epoch 20/25\n", - "39/39 [==============================] - 1s 21ms/step - loss: 0.1165 - categorical_accuracy: 0.9642 - val_loss: 0.0959 - val_categorical_accuracy: 0.9772\n", - "Epoch 21/25\n", - "39/39 [==============================] - 1s 22ms/step - loss: 0.0924 - categorical_accuracy: 0.9707 - val_loss: 0.0456 - val_categorical_accuracy: 0.9902\n", - "Epoch 22/25\n", - "39/39 [==============================] - 1s 21ms/step - loss: 0.0611 - categorical_accuracy: 0.9813 - val_loss: 0.0495 - val_categorical_accuracy: 0.9935\n", - "Epoch 23/25\n", - "39/39 [==============================] - 1s 21ms/step - loss: 0.0314 - categorical_accuracy: 0.9919 - val_loss: 0.0480 - val_categorical_accuracy: 0.9935\n", - "Epoch 24/25\n", - "39/39 [==============================] - 1s 21ms/step - loss: 0.0278 - categorical_accuracy: 0.9935 - val_loss: 0.0549 - val_categorical_accuracy: 0.9935\n", - "Epoch 25/25\n", - "39/39 [==============================] - 1s 22ms/step - loss: 0.0160 - categorical_accuracy: 0.9959 - val_loss: 0.0569 - val_categorical_accuracy: 0.9902\n" + "Epoch 1/250\n", + "21/21 [==============================] - 1s 27ms/step - loss: 4.6753 - categorical_accuracy: 0.1376 - val_loss: 2.6457 - val_categorical_accuracy: 0.2012\n", + "Epoch 2/250\n", + "21/21 [==============================] - 0s 21ms/step - loss: 2.1744 - categorical_accuracy: 0.3303 - val_loss: 1.4784 - val_categorical_accuracy: 0.5000\n", + "Epoch 3/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 1.4214 - categorical_accuracy: 0.5535 - val_loss: 0.8685 - val_categorical_accuracy: 0.7744\n", + "Epoch 4/250\n", + "21/21 [==============================] - 0s 21ms/step - loss: 1.0410 - categorical_accuracy: 0.6453 - val_loss: 0.5384 - val_categorical_accuracy: 0.8476\n", + "Epoch 5/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.7952 - categorical_accuracy: 0.7554 - val_loss: 0.3288 - val_categorical_accuracy: 0.9329\n", + "Epoch 6/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.5731 - categorical_accuracy: 0.8333 - val_loss: 0.2917 - val_categorical_accuracy: 0.9390\n", + "Epoch 7/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.4635 - categorical_accuracy: 0.8700 - val_loss: 0.1933 - val_categorical_accuracy: 0.9634\n", + "Epoch 8/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.3666 - categorical_accuracy: 0.9021 - val_loss: 0.2161 - val_categorical_accuracy: 0.9573\n", + "Epoch 9/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.3277 - categorical_accuracy: 0.9067 - val_loss: 0.1393 - val_categorical_accuracy: 0.9695\n", + "Epoch 10/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.3071 - categorical_accuracy: 0.9174 - val_loss: 0.1128 - val_categorical_accuracy: 0.9756\n", + "Epoch 11/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.2090 - categorical_accuracy: 0.9511 - val_loss: 0.1119 - val_categorical_accuracy: 0.9756\n", + "Epoch 12/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.2012 - categorical_accuracy: 0.9419 - val_loss: 0.0755 - val_categorical_accuracy: 0.9756\n", + "Epoch 13/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1497 - categorical_accuracy: 0.9587 - val_loss: 0.1092 - val_categorical_accuracy: 0.9695\n", + "Epoch 14/250\n", + "21/21 [==============================] - 0s 21ms/step - loss: 0.2278 - categorical_accuracy: 0.9235 - val_loss: 0.0737 - val_categorical_accuracy: 0.9756\n", + "Epoch 15/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1454 - categorical_accuracy: 0.9572 - val_loss: 0.1042 - val_categorical_accuracy: 0.9756\n", + "Epoch 16/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1029 - categorical_accuracy: 0.9725 - val_loss: 0.0979 - val_categorical_accuracy: 0.9756\n", + "Epoch 17/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1022 - categorical_accuracy: 0.9709 - val_loss: 0.1210 - val_categorical_accuracy: 0.9756\n", + "Epoch 18/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0927 - categorical_accuracy: 0.9725 - val_loss: 0.1178 - val_categorical_accuracy: 0.9695\n", + "Epoch 19/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1412 - categorical_accuracy: 0.9602 - val_loss: 0.1346 - val_categorical_accuracy: 0.9695\n", + "Epoch 20/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1014 - categorical_accuracy: 0.9679 - val_loss: 0.0620 - val_categorical_accuracy: 0.9756\n", + "Epoch 21/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1153 - categorical_accuracy: 0.9679 - val_loss: 0.0780 - val_categorical_accuracy: 0.9817\n", + "Epoch 22/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0763 - categorical_accuracy: 0.9740 - val_loss: 0.0767 - val_categorical_accuracy: 0.9878\n", + "Epoch 23/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0802 - categorical_accuracy: 0.9801 - val_loss: 0.0931 - val_categorical_accuracy: 0.9817\n", + "Epoch 24/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1222 - categorical_accuracy: 0.9709 - val_loss: 0.1875 - val_categorical_accuracy: 0.9512\n", + "Epoch 25/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0716 - categorical_accuracy: 0.9771 - val_loss: 0.0874 - val_categorical_accuracy: 0.9817\n", + "Epoch 26/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0851 - categorical_accuracy: 0.9740 - val_loss: 0.0924 - val_categorical_accuracy: 0.9817\n", + "Epoch 27/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1095 - categorical_accuracy: 0.9709 - val_loss: 0.0583 - val_categorical_accuracy: 0.9939\n", + "Epoch 28/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0630 - categorical_accuracy: 0.9847 - val_loss: 0.0562 - val_categorical_accuracy: 0.9939\n", + "Epoch 29/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0674 - categorical_accuracy: 0.9817 - val_loss: 0.0858 - val_categorical_accuracy: 0.9817\n", + "Epoch 30/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0779 - categorical_accuracy: 0.9832 - val_loss: 0.0772 - val_categorical_accuracy: 0.9878\n", + "Epoch 31/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0673 - categorical_accuracy: 0.9801 - val_loss: 0.0621 - val_categorical_accuracy: 0.9878\n", + "Epoch 32/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0709 - categorical_accuracy: 0.9771 - val_loss: 0.1291 - val_categorical_accuracy: 0.9817\n", + "Epoch 33/250\n", + "21/21 [==============================] - 0s 19ms/step - loss: 0.0743 - categorical_accuracy: 0.9755 - val_loss: 0.0685 - val_categorical_accuracy: 0.9939\n", + "Epoch 34/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0478 - categorical_accuracy: 0.9862 - val_loss: 0.0719 - val_categorical_accuracy: 0.9939\n", + "Epoch 35/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0363 - categorical_accuracy: 0.9878 - val_loss: 0.0731 - val_categorical_accuracy: 0.9939\n", + "Epoch 36/250\n", + "21/21 [==============================] - 0s 21ms/step - loss: 0.0515 - categorical_accuracy: 0.9817 - val_loss: 0.0741 - val_categorical_accuracy: 0.9878\n", + "Epoch 37/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0343 - categorical_accuracy: 0.9924 - val_loss: 0.0616 - val_categorical_accuracy: 0.9817\n", + "Epoch 38/250\n", + "21/21 [==============================] - 0s 22ms/step - loss: 0.0554 - categorical_accuracy: 0.9832 - val_loss: 0.0856 - val_categorical_accuracy: 0.9878\n", + "Epoch 39/250\n", + "21/21 [==============================] - 0s 22ms/step - loss: 0.0505 - categorical_accuracy: 0.9832 - val_loss: 0.0812 - val_categorical_accuracy: 0.9939\n", + "Epoch 40/250\n", + "21/21 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model.fit(X_train, y_train, validation_split=0.2, epochs=250)" ] }, { "cell_type": "code", - "execution_count": 243, + "execution_count": 214, "id": "880c4b32", "metadata": {}, "outputs": [], @@ -762,7 +1307,7 @@ }, { "cell_type": "code", - "execution_count": 244, + "execution_count": 215, "id": "1184301b", "metadata": {}, "outputs": [ @@ -770,7 +1315,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy Score: 0.9921875\n" + "Accuracy Score: 0.9951219512195122\n" ] } ], @@ -784,7 +1329,7 @@ }, { "cell_type": "code", - "execution_count": 245, + "execution_count": 216, "id": "c600e018", "metadata": {}, "outputs": [ @@ -802,17 +1347,17 @@ }, { "cell_type": "code", - "execution_count": 246, + "execution_count": 217, "id": "4730fa35", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "25" + "250" ] }, - "execution_count": 246, + "execution_count": 217, "metadata": {}, "output_type": "execute_result" } @@ -823,13 +1368,13 @@ }, { "cell_type": "code", - "execution_count": 248, + "execution_count": 220, "id": "3b02b8f5", "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -852,13 +1397,13 @@ }, { "cell_type": "code", - "execution_count": 249, + "execution_count": 221, "id": "dd6f4b76", "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ "
" ] @@ -908,7 +1453,7 @@ }, { "cell_type": "code", - "execution_count": 250, + "execution_count": 222, "id": "41873402", "metadata": {}, "outputs": [], @@ -921,7 +1466,7 @@ }, { "cell_type": "code", - "execution_count": 251, + "execution_count": 223, "id": "f73c99f3", "metadata": {}, "outputs": [], @@ -932,17 +1477,17 @@ }, { "cell_type": "code", - "execution_count": 252, + "execution_count": 224, "id": "050530cd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'L'" + "'D'" ] }, - "execution_count": 252, + "execution_count": 224, "metadata": {}, "output_type": "execute_result" } @@ -953,17 +1498,17 @@ }, { "cell_type": "code", - "execution_count": 253, + "execution_count": 225, "id": "3844a38d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'L'" + "'D'" ] }, - "execution_count": 253, + "execution_count": 225, "metadata": {}, "output_type": "execute_result" } @@ -974,13 +1519,13 @@ }, { "cell_type": "code", - "execution_count": 254, + "execution_count": 226, "id": "490d85d0", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1006,7 +1551,7 @@ }, { "cell_type": "code", - "execution_count": 255, + "execution_count": 227, "id": "3ee1d088", "metadata": {}, "outputs": [ @@ -1014,10 +1559,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "Precision Score: 0.9830128205128206\n", - "Recall Score: 0.9905982905982906\n", - "F1 Score: 0.9857885859914257\n", - "F Beta Score for Beta as 0.5 = 0.9839141601551946\n" + "Precision Score: 0.9967948717948717\n", + "Recall Score: 0.9945054945054945\n", + "F1 Score: 0.9953691793156676\n", + "F Beta Score for Beta as 0.5 = 0.9961517432813223\n" ] } ], @@ -1030,7 +1575,7 @@ }, { "cell_type": "code", - "execution_count": 256, + "execution_count": 228, "id": "66772715", "metadata": {}, "outputs": [ @@ -1040,36 +1585,36 @@ "text": [ " precision recall f1-score support\n", "\n", - " A 1.00 1.00 1.00 16\n", - " B 1.00 1.00 1.00 14\n", - " C 1.00 1.00 1.00 29\n", - " D 1.00 1.00 1.00 17\n", - " E 1.00 1.00 1.00 16\n", - " F 1.00 0.89 0.94 9\n", - " G 1.00 1.00 1.00 8\n", - " H 1.00 1.00 1.00 11\n", - " I 1.00 1.00 1.00 18\n", - " J 0.88 1.00 0.93 7\n", - " K 1.00 1.00 1.00 16\n", - " L 1.00 1.00 1.00 18\n", - " M 1.00 1.00 1.00 9\n", - " N 1.00 1.00 1.00 12\n", - " O 1.00 0.93 0.97 15\n", - " P 0.93 0.93 0.93 15\n", - " Q 0.75 1.00 0.86 3\n", - " R 1.00 1.00 1.00 16\n", - " S 1.00 1.00 1.00 17\n", - " T 1.00 1.00 1.00 17\n", - " U 1.00 1.00 1.00 14\n", + " A 1.00 1.00 1.00 4\n", + " B 1.00 1.00 1.00 8\n", + " C 1.00 1.00 1.00 4\n", + " D 1.00 1.00 1.00 12\n", + " E 1.00 1.00 1.00 5\n", + " F 1.00 1.00 1.00 10\n", + " G 0.92 1.00 0.96 11\n", + " H 1.00 1.00 1.00 8\n", + " I 1.00 1.00 1.00 10\n", + " J 1.00 1.00 1.00 8\n", + " K 1.00 1.00 1.00 9\n", + " L 1.00 1.00 1.00 9\n", + " M 1.00 1.00 1.00 8\n", + " N 1.00 1.00 1.00 7\n", + " O 1.00 1.00 1.00 8\n", + " P 1.00 1.00 1.00 8\n", + " Q 1.00 1.00 1.00 6\n", + " R 1.00 1.00 1.00 10\n", + " S 1.00 0.86 0.92 7\n", + " T 1.00 1.00 1.00 7\n", + " U 1.00 1.00 1.00 8\n", " V 1.00 1.00 1.00 11\n", - " W 1.00 1.00 1.00 19\n", - " X 1.00 1.00 1.00 18\n", - " Y 1.00 1.00 1.00 16\n", - " Z 1.00 1.00 1.00 23\n", + " W 1.00 1.00 1.00 5\n", + " X 1.00 1.00 1.00 4\n", + " Y 1.00 1.00 1.00 7\n", + " Z 1.00 1.00 1.00 11\n", "\n", - " accuracy 0.99 384\n", - " macro avg 0.98 0.99 0.99 384\n", - "weighted avg 0.99 0.99 0.99 384\n", + " accuracy 1.00 205\n", + " macro avg 1.00 0.99 1.00 205\n", + "weighted avg 1.00 1.00 1.00 205\n", "\n" ] } @@ -1081,7 +1626,7 @@ }, { "cell_type": "code", - "execution_count": 257, + "execution_count": 229, "id": "44f72c9f", "metadata": {}, "outputs": [ @@ -1089,7 +1634,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Hamming Loss: 0.0078125\n" + "Hamming Loss: 0.004878048780487805\n" ] } ], @@ -1100,7 +1645,7 @@ }, { "cell_type": "code", - "execution_count": 258, + "execution_count": 230, "id": "c1b71974", "metadata": {}, "outputs": [ @@ -1108,8 +1653,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "Jaccard Score: 0.9739316239316239\n", - "Matthews correlation coefficient: 0.9918501020941433\n" + "Jaccard Score: 0.9913003663003663\n", + "Matthews correlation coefficient: 0.9949345792170793\n" ] } ], @@ -1121,7 +1666,7 @@ }, { "cell_type": "code", - "execution_count": 259, + "execution_count": 231, "id": "6245c168", "metadata": {}, "outputs": [], @@ -1149,7 +1694,7 @@ }, { "cell_type": "code", - "execution_count": 260, + "execution_count": 232, "id": "be42467e", "metadata": {}, "outputs": [ @@ -1160,7 +1705,7 @@ " 'Z'], dtype='" ] @@ -1200,13 +1745,13 @@ }, { "cell_type": "code", - "execution_count": 262, + "execution_count": 234, "id": "7bdbc5a8", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -1228,7 +1773,7 @@ }, { "cell_type": "code", - "execution_count": 263, + "execution_count": 235, "id": "fa10e646", "metadata": {}, "outputs": [], @@ -1239,7 +1784,7 @@ }, { "cell_type": "code", - "execution_count": 264, + "execution_count": 236, "id": "f8250c41", "metadata": {}, "outputs": [ @@ -1249,13 +1794,6 @@ "text": [ "INFO:tensorflow:Assets written to: saved_models_benchmark\\assets\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:tensorflow:Assets written to: saved_models_benchmark\\assets\n" - ] } ], "source": [ @@ -1269,7 +1807,7 @@ }, { "cell_type": "code", - "execution_count": 265, + "execution_count": 237, "id": "47dd0e88", "metadata": {}, "outputs": [], @@ -1281,7 +1819,7 @@ }, { "cell_type": "code", - "execution_count": 266, + "execution_count": 238, "id": "c3c36a2d", "metadata": {}, "outputs": [], @@ -1309,7 +1847,7 @@ }, { "cell_type": "code", - "execution_count": 267, + "execution_count": 239, "id": "42a64831", "metadata": {}, "outputs": [ @@ -1317,14 +1855,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmpto0yrz1c\\assets\n" + "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmpl7nu4ca2\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmpto0yrz1c\\assets\n", "WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded\n", "WARNING:absl:Optimization option OPTIMIZE_FOR_SIZE is deprecated, please use optimizations=[Optimize.DEFAULT] instead.\n" ] @@ -1333,14 +1870,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmpm5ywhtaz\\assets\n" + "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmp6jt9dkh4\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmpm5ywhtaz\\assets\n", + "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmp6jt9dkh4\\assets\n", "WARNING:absl:Optimization option OPTIMIZE_FOR_SIZE is deprecated, please use optimizations=[Optimize.DEFAULT] instead.\n", "WARNING:absl:Optimization option OPTIMIZE_FOR_SIZE is deprecated, please use optimizations=[Optimize.DEFAULT] instead.\n", "WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded\n" @@ -1353,7 +1890,7 @@ }, { "cell_type": "code", - "execution_count": 268, + "execution_count": 240, "id": "a440220b", "metadata": {}, "outputs": [], diff --git a/.ipynb_checkpoints/PrepareModelCustom-checkpoint.ipynb b/.ipynb_checkpoints/PrepareModelCustom-checkpoint.ipynb index 8fe9937..1f67752 100644 --- a/.ipynb_checkpoints/PrepareModelCustom-checkpoint.ipynb +++ b/.ipynb_checkpoints/PrepareModelCustom-checkpoint.ipynb @@ -167,7 +167,7 @@ "no_sequences = 30\n", "\n", "# no of frames in each video\n", - "sequence_length = 16" + "sequence_length = 30" ] }, { @@ -231,7 +231,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "id": "7b4d65e2", "metadata": { "scrolled": false @@ -251,7 +251,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "id": "17c51f1b", "metadata": {}, "outputs": [], @@ -262,7 +262,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, "id": "19fcd4ea", "metadata": {}, "outputs": [ @@ -272,7 +272,7 @@ "780" ] }, - "execution_count": 17, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -283,7 +283,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 16, "id": "f5774456", "metadata": { "scrolled": false @@ -295,7 +295,7 @@ "780" ] }, - "execution_count": 18, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -306,7 +306,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 17, "id": "4098afde", "metadata": {}, "outputs": [], @@ -316,7 +316,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 18, "id": "f8620c6b", "metadata": {}, "outputs": [], @@ -326,17 +326,17 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 19, "id": "a86cfe2b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(624, 16, 42, 3)" + "(624, 30, 42, 3)" ] }, - "execution_count": 21, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -347,17 +347,17 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 20, "id": "19d57590", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(156, 16, 42, 3)" + "(156, 30, 42, 3)" ] }, - "execution_count": 22, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -368,7 +368,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 21, "id": "672571a1", "metadata": {}, "outputs": [ @@ -378,7 +378,7 @@ "(624, 26)" ] }, - "execution_count": 23, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -389,7 +389,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 22, "id": "cc3d2b9e", "metadata": {}, "outputs": [ @@ -399,7 +399,7 @@ "(156, 26)" ] }, - "execution_count": 24, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -410,7 +410,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 23, "id": "6c5b0479", "metadata": {}, "outputs": [], @@ -423,7 +423,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 24, "id": "a3dba74d", "metadata": {}, "outputs": [], @@ -435,7 +435,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 25, "id": "9533039b", "metadata": {}, "outputs": [], @@ -446,7 +446,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 92, "id": "493e3f91", "metadata": {}, "outputs": [], @@ -454,7 +454,7 @@ "model = Sequential()\n", "\n", "model.add(Conv2D(filters=32, kernel_size=(3,3), activation='relu', padding = 'same', input_shape=X_train.shape[1:]))\n", - "model.add(MaxPool2D(pool_size=(1,2), strides=None))\n", + "model.add(MaxPool2D(pool_size=(2,2), strides=None))\n", "\n", "model.add(Conv2D(filters=64, kernel_size=(3,3), activation='relu'))\n", "model.add(MaxPool2D(pool_size=(2,2), strides=None))\n", @@ -469,7 +469,6 @@ "\n", "\n", "\n", - "\n", "model.add(Flatten())\n", "\n", "model.add(Dense(128,activation =\"relu\"))\n", @@ -485,7 +484,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 93, "id": "0e85302e", "metadata": {}, "outputs": [ @@ -493,38 +492,38 @@ "name": "stdout", "output_type": "stream", "text": [ - "Model: \"sequential_3\"\n", + "Model: \"sequential_11\"\n", "_________________________________________________________________\n", " Layer (type) Output Shape Param # \n", "=================================================================\n", - " conv2d_12 (Conv2D) (None, 16, 42, 32) 896 \n", + " conv2d_44 (Conv2D) (None, 30, 42, 32) 896 \n", " \n", - " max_pooling2d_9 (MaxPooling (None, 16, 21, 32) 0 \n", - " 2D) \n", + " max_pooling2d_33 (MaxPoolin (None, 15, 21, 32) 0 \n", + " g2D) \n", " \n", - " conv2d_13 (Conv2D) (None, 14, 19, 64) 18496 \n", + " conv2d_45 (Conv2D) (None, 13, 19, 64) 18496 \n", " \n", - " max_pooling2d_10 (MaxPoolin (None, 7, 9, 64) 0 \n", + " max_pooling2d_34 (MaxPoolin (None, 6, 9, 64) 0 \n", " g2D) \n", " \n", - " conv2d_14 (Conv2D) (None, 5, 7, 128) 73856 \n", + " conv2d_46 (Conv2D) (None, 4, 7, 128) 73856 \n", " \n", - " conv2d_15 (Conv2D) (None, 3, 5, 256) 295168 \n", + " conv2d_47 (Conv2D) (None, 2, 5, 256) 295168 \n", " \n", - " max_pooling2d_11 (MaxPoolin (None, 1, 2, 256) 0 \n", + " max_pooling2d_35 (MaxPoolin (None, 1, 2, 256) 0 \n", " g2D) \n", " \n", - " flatten_3 (Flatten) (None, 512) 0 \n", + " flatten_11 (Flatten) (None, 512) 0 \n", " \n", - " dense_9 (Dense) (None, 128) 65664 \n", + " dense_33 (Dense) (None, 128) 65664 \n", " \n", - " dropout_6 (Dropout) (None, 128) 0 \n", + " dropout_22 (Dropout) (None, 128) 0 \n", " \n", - " dense_10 (Dense) (None, 64) 8256 \n", + " dense_34 (Dense) (None, 64) 8256 \n", " \n", - " dropout_7 (Dropout) (None, 64) 0 \n", + " dropout_23 (Dropout) (None, 64) 0 \n", " \n", - " dense_11 (Dense) (None, 26) 1690 \n", + " dense_35 (Dense) (None, 26) 1690 \n", " \n", "=================================================================\n", "Total params: 464,026\n", @@ -540,7 +539,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 94, "id": "a5bbb03d", "metadata": {}, "outputs": [], @@ -550,7 +549,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 95, "id": "912211ea", "metadata": {}, "outputs": [ @@ -558,222 +557,1058 @@ "name": "stdout", "output_type": "stream", "text": [ - "Epoch 1/100\n", - "16/16 [==============================] - 1s 29ms/step - loss: 3.2229 - categorical_accuracy: 0.0721 - val_loss: 3.1005 - val_categorical_accuracy: 0.0800\n", - "Epoch 2/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 3.0234 - categorical_accuracy: 0.1082 - val_loss: 2.8460 - val_categorical_accuracy: 0.1760\n", - "Epoch 3/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 2.8585 - categorical_accuracy: 0.1403 - val_loss: 2.6667 - val_categorical_accuracy: 0.2320\n", - "Epoch 4/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 2.7114 - categorical_accuracy: 0.1924 - val_loss: 2.5688 - val_categorical_accuracy: 0.2080\n", - "Epoch 5/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 2.5513 - categorical_accuracy: 0.2365 - val_loss: 2.2031 - val_categorical_accuracy: 0.3440\n", - "Epoch 6/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 2.2395 - categorical_accuracy: 0.2806 - val_loss: 2.0264 - val_categorical_accuracy: 0.4160\n", - "Epoch 7/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 2.0219 - categorical_accuracy: 0.3327 - val_loss: 1.8286 - val_categorical_accuracy: 0.3920\n", - "Epoch 8/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.9193 - categorical_accuracy: 0.3407 - val_loss: 1.7887 - val_categorical_accuracy: 0.4400\n", - "Epoch 9/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.7239 - categorical_accuracy: 0.4409 - val_loss: 1.6786 - val_categorical_accuracy: 0.4720\n", - "Epoch 10/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.5966 - categorical_accuracy: 0.4629 - val_loss: 1.5551 - val_categorical_accuracy: 0.5520\n", - "Epoch 11/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.5733 - categorical_accuracy: 0.4569 - val_loss: 1.6099 - val_categorical_accuracy: 0.4960\n", - "Epoch 12/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.5050 - categorical_accuracy: 0.4930 - val_loss: 1.4998 - val_categorical_accuracy: 0.5600\n", - "Epoch 13/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.2710 - categorical_accuracy: 0.5792 - val_loss: 1.2563 - val_categorical_accuracy: 0.6320\n", - "Epoch 14/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 1.1448 - categorical_accuracy: 0.5892 - val_loss: 1.2611 - val_categorical_accuracy: 0.6080\n", - "Epoch 15/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 1.1093 - categorical_accuracy: 0.6112 - val_loss: 1.1743 - val_categorical_accuracy: 0.6560\n", - "Epoch 16/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 1.1377 - categorical_accuracy: 0.5832 - val_loss: 1.1630 - val_categorical_accuracy: 0.6960\n", - "Epoch 17/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.9505 - categorical_accuracy: 0.6633 - val_loss: 1.0647 - val_categorical_accuracy: 0.6480\n", - "Epoch 18/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.8373 - categorical_accuracy: 0.7074 - val_loss: 0.9812 - val_categorical_accuracy: 0.7680\n", - "Epoch 19/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.8333 - categorical_accuracy: 0.6914 - val_loss: 1.0481 - val_categorical_accuracy: 0.7280\n", - "Epoch 20/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.8526 - categorical_accuracy: 0.7014 - val_loss: 0.9702 - val_categorical_accuracy: 0.7280\n", - "Epoch 21/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.7415 - categorical_accuracy: 0.7415 - val_loss: 0.9232 - val_categorical_accuracy: 0.7520\n", - "Epoch 22/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.7063 - categorical_accuracy: 0.7635 - val_loss: 0.9633 - val_categorical_accuracy: 0.7520\n", - "Epoch 23/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.6511 - categorical_accuracy: 0.7796 - val_loss: 0.8636 - val_categorical_accuracy: 0.8160\n", - "Epoch 24/100\n", - "16/16 [==============================] - 0s 18ms/step - loss: 0.5929 - categorical_accuracy: 0.8056 - val_loss: 0.9440 - val_categorical_accuracy: 0.7520\n", - "Epoch 25/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.5736 - categorical_accuracy: 0.8036 - val_loss: 0.8064 - val_categorical_accuracy: 0.8000\n", - "Epoch 26/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 0.5017 - categorical_accuracy: 0.8156 - val_loss: 0.7988 - val_categorical_accuracy: 0.7840\n", - "Epoch 27/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.4334 - categorical_accuracy: 0.8317 - val_loss: 0.7012 - val_categorical_accuracy: 0.8320\n", - "Epoch 28/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.5081 - categorical_accuracy: 0.8236 - val_loss: 0.7811 - val_categorical_accuracy: 0.8080\n", - "Epoch 29/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.4240 - categorical_accuracy: 0.8437 - val_loss: 0.6682 - val_categorical_accuracy: 0.8160\n", - "Epoch 30/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.3713 - categorical_accuracy: 0.8677 - val_loss: 0.7253 - val_categorical_accuracy: 0.8480\n", - "Epoch 31/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.3603 - categorical_accuracy: 0.8717 - val_loss: 0.7806 - val_categorical_accuracy: 0.8000\n", - "Epoch 32/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.3508 - categorical_accuracy: 0.8697 - val_loss: 0.7556 - val_categorical_accuracy: 0.8240\n", - "Epoch 33/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.3315 - categorical_accuracy: 0.8918 - val_loss: 0.7645 - val_categorical_accuracy: 0.8400\n", - "Epoch 34/100\n", - "16/16 [==============================] - 0s 24ms/step - loss: 0.2965 - categorical_accuracy: 0.9038 - val_loss: 0.8480 - val_categorical_accuracy: 0.8400\n", - "Epoch 35/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.3715 - categorical_accuracy: 0.8838 - val_loss: 0.6484 - val_categorical_accuracy: 0.8720\n", - "Epoch 36/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.2969 - categorical_accuracy: 0.8858 - val_loss: 0.6275 - val_categorical_accuracy: 0.8560\n", - "Epoch 37/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.2123 - categorical_accuracy: 0.9339 - val_loss: 0.7202 - val_categorical_accuracy: 0.8640\n", - "Epoch 38/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.2941 - categorical_accuracy: 0.8978 - val_loss: 0.8392 - val_categorical_accuracy: 0.8320\n", - "Epoch 39/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.2526 - categorical_accuracy: 0.9238 - val_loss: 0.6771 - val_categorical_accuracy: 0.8560\n", - "Epoch 40/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.3140 - categorical_accuracy: 0.8858 - val_loss: 0.8108 - val_categorical_accuracy: 0.8080\n", - "Epoch 41/100\n", - "16/16 [==============================] - 0s 29ms/step - loss: 0.2606 - categorical_accuracy: 0.9319 - val_loss: 0.6298 - val_categorical_accuracy: 0.8560\n", - "Epoch 42/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.2204 - categorical_accuracy: 0.9218 - val_loss: 0.6714 - val_categorical_accuracy: 0.8560\n", - "Epoch 43/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.1692 - categorical_accuracy: 0.9339 - val_loss: 0.5969 - val_categorical_accuracy: 0.8640\n", - "Epoch 44/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.2055 - categorical_accuracy: 0.9319 - val_loss: 0.6999 - val_categorical_accuracy: 0.8800\n", - "Epoch 45/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.1948 - categorical_accuracy: 0.9419 - val_loss: 0.7755 - val_categorical_accuracy: 0.8480\n", - "Epoch 46/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.2336 - categorical_accuracy: 0.9178 - val_loss: 0.7158 - val_categorical_accuracy: 0.8560\n", - "Epoch 47/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.1922 - categorical_accuracy: 0.9299 - val_loss: 0.7854 - val_categorical_accuracy: 0.8480\n", - "Epoch 48/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.2264 - categorical_accuracy: 0.9178 - val_loss: 0.9473 - val_categorical_accuracy: 0.8240\n", - "Epoch 49/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.1565 - categorical_accuracy: 0.9539 - val_loss: 0.6922 - val_categorical_accuracy: 0.8800\n", - "Epoch 50/100\n", - "16/16 [==============================] - 1s 37ms/step - loss: 0.1425 - categorical_accuracy: 0.9519 - val_loss: 0.7299 - val_categorical_accuracy: 0.8640\n", - "Epoch 51/100\n", - "16/16 [==============================] - 1s 32ms/step - loss: 0.1028 - categorical_accuracy: 0.9719 - val_loss: 0.7734 - val_categorical_accuracy: 0.8800\n", - "Epoch 52/100\n", - "16/16 [==============================] - 0s 24ms/step - loss: 0.0776 - categorical_accuracy: 0.9699 - val_loss: 0.7024 - val_categorical_accuracy: 0.8800\n", - "Epoch 53/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.0952 - categorical_accuracy: 0.9699 - val_loss: 0.7696 - val_categorical_accuracy: 0.8720\n", - "Epoch 54/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.0979 - categorical_accuracy: 0.9699 - val_loss: 0.6391 - val_categorical_accuracy: 0.8880\n", - "Epoch 55/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.1418 - categorical_accuracy: 0.9439 - val_loss: 0.8247 - val_categorical_accuracy: 0.8560\n", - "Epoch 56/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.1139 - categorical_accuracy: 0.9579 - val_loss: 0.8348 - val_categorical_accuracy: 0.8800\n", - "Epoch 57/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.1112 - categorical_accuracy: 0.9579 - val_loss: 0.8574 - val_categorical_accuracy: 0.8560\n", - "Epoch 58/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.0750 - categorical_accuracy: 0.9739 - val_loss: 0.6934 - val_categorical_accuracy: 0.8800\n", - "Epoch 59/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.0794 - categorical_accuracy: 0.9840 - val_loss: 0.6185 - val_categorical_accuracy: 0.8880\n", - "Epoch 60/100\n", - "16/16 [==============================] - 0s 24ms/step - loss: 0.0797 - categorical_accuracy: 0.9739 - val_loss: 0.7429 - val_categorical_accuracy: 0.8640\n", - "Epoch 61/100\n", - "16/16 [==============================] - 0s 29ms/step - loss: 0.1981 - categorical_accuracy: 0.9379 - val_loss: 0.6515 - val_categorical_accuracy: 0.8960\n", - "Epoch 62/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.1966 - categorical_accuracy: 0.9359 - val_loss: 0.7868 - val_categorical_accuracy: 0.8640\n", - "Epoch 63/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.1372 - categorical_accuracy: 0.9559 - val_loss: 0.9240 - val_categorical_accuracy: 0.8160\n", - "Epoch 64/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.1060 - categorical_accuracy: 0.9679 - val_loss: 0.6382 - val_categorical_accuracy: 0.9120\n", - "Epoch 65/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.0911 - categorical_accuracy: 0.9739 - val_loss: 0.7762 - val_categorical_accuracy: 0.8400\n", - "Epoch 66/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.1127 - categorical_accuracy: 0.9599 - val_loss: 0.9982 - val_categorical_accuracy: 0.8160\n", - "Epoch 67/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.0752 - categorical_accuracy: 0.9760 - val_loss: 0.6734 - val_categorical_accuracy: 0.8880\n", - "Epoch 68/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.0518 - categorical_accuracy: 0.9800 - val_loss: 0.7425 - val_categorical_accuracy: 0.8960\n", - "Epoch 69/100\n", - "16/16 [==============================] - 0s 29ms/step - loss: 0.0467 - categorical_accuracy: 0.9820 - val_loss: 0.7276 - val_categorical_accuracy: 0.8720\n", - "Epoch 70/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.0737 - categorical_accuracy: 0.9760 - val_loss: 0.7341 - val_categorical_accuracy: 0.8880\n", - "Epoch 71/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.0438 - categorical_accuracy: 0.9860 - val_loss: 0.9370 - val_categorical_accuracy: 0.8720\n", - "Epoch 72/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.0392 - categorical_accuracy: 0.9900 - val_loss: 0.8334 - val_categorical_accuracy: 0.9120\n", - "Epoch 73/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.0310 - categorical_accuracy: 0.9900 - val_loss: 0.8172 - val_categorical_accuracy: 0.9040\n", - "Epoch 74/100\n", - "16/16 [==============================] - 0s 29ms/step - loss: 0.0563 - categorical_accuracy: 0.9860 - val_loss: 0.7033 - val_categorical_accuracy: 0.9280\n", - "Epoch 75/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.0486 - categorical_accuracy: 0.9800 - val_loss: 0.7949 - val_categorical_accuracy: 0.8880\n", - "Epoch 76/100\n", - "16/16 [==============================] - 0s 24ms/step - loss: 0.0749 - categorical_accuracy: 0.9739 - val_loss: 0.6894 - val_categorical_accuracy: 0.9120\n", - "Epoch 77/100\n", - "16/16 [==============================] - 0s 26ms/step - loss: 0.0817 - categorical_accuracy: 0.9699 - val_loss: 1.0077 - val_categorical_accuracy: 0.8640\n", - "Epoch 78/100\n", - "16/16 [==============================] - 0s 24ms/step - loss: 0.1340 - categorical_accuracy: 0.9499 - val_loss: 0.8971 - val_categorical_accuracy: 0.8640\n", - "Epoch 79/100\n", - "16/16 [==============================] - 0s 26ms/step - loss: 0.0939 - categorical_accuracy: 0.9739 - val_loss: 0.5820 - val_categorical_accuracy: 0.9280\n", - "Epoch 80/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.0559 - categorical_accuracy: 0.9820 - val_loss: 0.6334 - val_categorical_accuracy: 0.8880\n", - "Epoch 81/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.0580 - categorical_accuracy: 0.9820 - val_loss: 0.5898 - val_categorical_accuracy: 0.9360\n", - "Epoch 82/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.0438 - categorical_accuracy: 0.9820 - val_loss: 0.7552 - val_categorical_accuracy: 0.9040\n", - "Epoch 83/100\n", - "16/16 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val_categorical_accuracy: 0.9440\n", + "Epoch 494/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 0.0021 - categorical_accuracy: 0.9980 - val_loss: 0.4926 - val_categorical_accuracy: 0.9440\n", + "Epoch 495/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 1.9070e-04 - categorical_accuracy: 1.0000 - val_loss: 0.4827 - val_categorical_accuracy: 0.9440\n", + "Epoch 496/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 0.0014 - categorical_accuracy: 1.0000 - val_loss: 0.5006 - val_categorical_accuracy: 0.9360\n", + "Epoch 497/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 8.5796e-04 - categorical_accuracy: 1.0000 - val_loss: 0.4914 - val_categorical_accuracy: 0.9360\n", + "Epoch 498/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 4.7972e-04 - categorical_accuracy: 1.0000 - val_loss: 0.4816 - val_categorical_accuracy: 0.9360\n", + "Epoch 499/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 5.7910e-05 - categorical_accuracy: 1.0000 - val_loss: 0.4771 - val_categorical_accuracy: 0.9360\n", + "Epoch 500/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 5.4242e-05 - categorical_accuracy: 1.0000 - val_loss: 0.4757 - val_categorical_accuracy: 0.9440\n" ] } ], "source": [ - "history = model.fit(X_train, y_train, validation_split=0.2, epochs=100)" + "history = model.fit(X_train, y_train, validation_split=0.2, epochs=500)" ] }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 96, "id": "8df847cc", "metadata": {}, "outputs": [ @@ -781,7 +1616,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy Score: 0.9423076923076923\n" + "Accuracy Score: 0.9358974358974359\n" ] } ], @@ -796,7 +1631,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 97, "id": "c600e018", "metadata": {}, "outputs": [ @@ -814,7 +1649,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 98, "id": "1184301b", "metadata": {}, "outputs": [ @@ -822,38 +1657,38 @@ "name": "stdout", "output_type": "stream", "text": [ - "Model: \"sequential_3\"\n", + "Model: \"sequential_11\"\n", "_________________________________________________________________\n", " Layer (type) Output Shape Param # \n", "=================================================================\n", - " conv2d_12 (Conv2D) (None, 16, 42, 32) 896 \n", + " conv2d_44 (Conv2D) (None, 30, 42, 32) 896 \n", " \n", - " max_pooling2d_9 (MaxPooling (None, 16, 21, 32) 0 \n", - " 2D) \n", + " max_pooling2d_33 (MaxPoolin (None, 15, 21, 32) 0 \n", + " g2D) \n", " \n", - " conv2d_13 (Conv2D) (None, 14, 19, 64) 18496 \n", + " conv2d_45 (Conv2D) (None, 13, 19, 64) 18496 \n", " \n", - " max_pooling2d_10 (MaxPoolin (None, 7, 9, 64) 0 \n", + " max_pooling2d_34 (MaxPoolin (None, 6, 9, 64) 0 \n", " g2D) \n", " \n", - " conv2d_14 (Conv2D) (None, 5, 7, 128) 73856 \n", + " conv2d_46 (Conv2D) (None, 4, 7, 128) 73856 \n", " \n", - " conv2d_15 (Conv2D) (None, 3, 5, 256) 295168 \n", + " conv2d_47 (Conv2D) (None, 2, 5, 256) 295168 \n", " \n", - " max_pooling2d_11 (MaxPoolin (None, 1, 2, 256) 0 \n", + " max_pooling2d_35 (MaxPoolin (None, 1, 2, 256) 0 \n", " g2D) \n", " \n", - " flatten_3 (Flatten) (None, 512) 0 \n", + " flatten_11 (Flatten) (None, 512) 0 \n", " \n", - " dense_9 (Dense) (None, 128) 65664 \n", + " dense_33 (Dense) (None, 128) 65664 \n", " \n", - " dropout_6 (Dropout) (None, 128) 0 \n", + " dropout_22 (Dropout) (None, 128) 0 \n", " \n", - " dense_10 (Dense) (None, 64) 8256 \n", + " dense_34 (Dense) (None, 64) 8256 \n", " \n", - " dropout_7 (Dropout) (None, 64) 0 \n", + " dropout_23 (Dropout) (None, 64) 0 \n", " \n", - " dense_11 (Dense) (None, 26) 1690 \n", + " dense_35 (Dense) (None, 26) 1690 \n", " \n", "=================================================================\n", "Total params: 464,026\n", @@ -869,17 +1704,17 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 99, "id": "4730fa35", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "100" + "500" ] }, - "execution_count": 64, + "execution_count": 99, "metadata": {}, "output_type": "execute_result" } @@ -890,13 +1725,13 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 101, "id": "3b02b8f5", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -921,13 +1756,13 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 102, "id": "dd6f4b76", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -962,7 +1797,7 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 103, "id": "41873402", "metadata": {}, "outputs": [], @@ -975,7 +1810,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 104, "id": "f73c99f3", "metadata": {}, "outputs": [], @@ -986,17 +1821,17 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 105, "id": "050530cd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'I'" + "'T'" ] }, - "execution_count": 70, + "execution_count": 105, "metadata": {}, "output_type": "execute_result" } @@ -1007,17 +1842,17 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 106, "id": "3844a38d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'I'" + "'T'" ] }, - "execution_count": 71, + "execution_count": 106, "metadata": {}, "output_type": "execute_result" } @@ -1028,7 +1863,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 107, "id": "880c4b32", "metadata": {}, "outputs": [], @@ -1038,13 +1873,13 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 108, "id": "490d85d0", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1070,7 +1905,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 109, "id": "3ee1d088", "metadata": {}, "outputs": [ @@ -1078,10 +1913,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "Precision Score: 0.9527930402930403\n", - "Recall Score: 0.9489926739926738\n", - "F1 Score: 0.945421860693354\n", - "F Beta Score for Beta as 0.5 = 0.9483468855680387\n" + "Precision Score: 0.9329212454212455\n", + "Recall Score: 0.9286935286935287\n", + "F1 Score: 0.9241946127752272\n", + "F Beta Score for Beta as 0.5 = 0.9273585870477405\n" ] } ], @@ -1094,7 +1929,7 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 110, "id": "66772715", "metadata": {}, "outputs": [ @@ -1104,36 +1939,36 @@ "text": [ " precision recall f1-score support\n", "\n", - " A 1.00 1.00 1.00 4\n", + " A 1.00 1.00 1.00 8\n", " B 1.00 1.00 1.00 5\n", - " C 0.60 0.86 0.71 7\n", - " D 1.00 1.00 1.00 9\n", - " E 1.00 1.00 1.00 8\n", - " F 1.00 1.00 1.00 8\n", - " G 1.00 1.00 1.00 12\n", - " H 1.00 1.00 1.00 2\n", - " I 0.86 1.00 0.92 6\n", - " J 0.83 0.83 0.83 6\n", - " K 1.00 1.00 1.00 6\n", - " L 1.00 1.00 1.00 7\n", - " M 1.00 1.00 1.00 8\n", + " C 1.00 1.00 1.00 7\n", + " D 1.00 1.00 1.00 5\n", + " E 1.00 1.00 1.00 3\n", + " F 1.00 0.90 0.95 10\n", + " G 0.75 0.90 0.82 10\n", + " H 1.00 1.00 1.00 10\n", + " I 0.50 0.50 0.50 2\n", + " J 0.86 1.00 0.92 6\n", + " K 1.00 1.00 1.00 2\n", + " L 0.86 1.00 0.92 6\n", + " M 1.00 0.80 0.89 5\n", " N 1.00 1.00 1.00 5\n", - " O 1.00 0.60 0.75 10\n", - " P 0.86 1.00 0.92 6\n", - " Q 0.75 1.00 0.86 3\n", - " R 1.00 1.00 1.00 5\n", - " S 1.00 1.00 1.00 3\n", + " O 0.88 1.00 0.93 7\n", + " P 1.00 1.00 1.00 6\n", + " Q 1.00 0.86 0.92 7\n", + " R 1.00 1.00 1.00 7\n", + " S 1.00 1.00 1.00 6\n", " T 1.00 0.80 0.89 5\n", - " U 1.00 0.75 0.86 4\n", - " V 0.88 1.00 0.93 7\n", - " W 1.00 1.00 1.00 2\n", - " X 1.00 1.00 1.00 7\n", - " Y 1.00 0.83 0.91 6\n", - " Z 1.00 1.00 1.00 5\n", + " U 1.00 0.50 0.67 6\n", + " V 1.00 0.89 0.94 9\n", + " W 0.83 1.00 0.91 5\n", + " X 0.83 1.00 0.91 5\n", + " Y 0.75 1.00 0.86 3\n", + " Z 1.00 1.00 1.00 6\n", "\n", " accuracy 0.94 156\n", - " macro avg 0.95 0.95 0.95 156\n", - "weighted avg 0.95 0.94 0.94 156\n", + " macro avg 0.93 0.93 0.92 156\n", + "weighted avg 0.95 0.94 0.93 156\n", "\n" ] } @@ -1145,7 +1980,7 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 111, "id": "44f72c9f", "metadata": {}, "outputs": [ @@ -1153,7 +1988,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Hamming Loss: 0.057692307692307696\n" + "Hamming Loss: 0.0641025641025641\n" ] } ], @@ -1164,7 +1999,7 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 112, "id": "c1b71974", "metadata": {}, "outputs": [ @@ -1172,8 +2007,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "Jaccard Score: 0.9070138195138195\n", - "Matthews correlation coefficient: 0.9403164913771194\n" + "Jaccard Score: 0.8760625058701983\n", + "Matthews correlation coefficient: 0.9334709474777175\n" ] } ], @@ -1185,7 +2020,7 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 113, "id": "6245c168", "metadata": {}, "outputs": [], @@ -1213,7 +2048,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 114, "id": "be42467e", "metadata": {}, "outputs": [ @@ -1224,7 +2059,7 @@ " 'Z'], dtype='" ] @@ -1264,13 +2099,13 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 116, "id": "7bdbc5a8", "metadata": {}, "outputs": [ { "data": { - "image/png": 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rcAzxJa5Dm+v02bL5ji9y3B8Vpu7dbtfY+KH669WNlV9QoJ/St0iS9u77TTt37VWra69x89S4VKWlfambbvy7gv73D//jA/pqxcr/uHkqwL2279yt12fNl91uV9HJk3p3yUp1v+M2d4+FGogMdh1+ha3BLvPz1ZTE55U8eYaKi0/J09NDL4wYor9e3djdo+ESdfhwth597BktfD9F3t61tHPHHj38yFPuHgtwq4GP/FPjJ72h6IcGqqTErru7dtE9Ed2dPxGoJDLYdWzGuQ5GqQLdunXTwIEDdd99913wa5w6srMKJwLKV6dxF+cPAi5SSfHZV41zJXIYlwoyGGaoKINdVoirAkEMsxDGMIPZhbgqkMMwAxkMM1SUwRxDDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSvMq749ixYxU+0d/fv4pHAQD8ETkMAOYotxDffPPNstlsMgzjrPtsNpt++eUXlw4GAFZHDgOAOcotxFu3bjVzDgDAn5DDAGAOp8cQl5aWavbs2YqLi1N+fr5mzpwpu91uxmwAAJHDAOBqTgvxhAkTtG3bNv38888yDENfffWVkpKSzJgNACByGABczWkhXr9+vZKTk+Xj4yM/Pz/NmTNH69atM2M2AIDIYQBwNaeF2MvLSx4evz/M29tbXl7lHnoMAKhi5DAAuJbTRG3RooUWLFggu92unTt3at68eWrVqpUZswEARA4DgKs53UM8cuRIZWRkKDs7W71791ZBQYESEhLMmA0AIHIYAFzNZpzrBJfVxKkjO909AiyiTuMu7h4BFlBSnOXuESqNHIYZyGCYoaIMdrqHODs7W88884xuuukmBQcHKyEhQbm5uVU6IACgfOQwALiW00I8atQoNWnSRIsXL9Y777yj+vXra/To0WbMBgAQOQwArub0S3VZWVl68803HbdHjBihiIgIlw4FAPgdOQwAruV0D/Hll1+uzMxMx+0DBw4oMDDQpUMBAH5HDgOAa5W7h/iJJ56QJOXk5CgqKkq33nqrPDw8tGHDBrVs2dK0AQHAqshhADBHuYU4NDT0nMtDQkJcNQsA4A/IYQAwR7mFODo6+pzLDcPQnj17XDYQAOA0chgAzOH0S3Xvv/++JkyYoBMnTjiWBQQEaN26dS4dDABwGjkMAK7ltBCnpKRo7ty5evPNNzV06FCtWbNGBw4cMGM2AIDIYQBwNadnmfD391f79u113XXXKTs7WwMHDtT3339vxmwAAJHDAOBqTguxl5eXjh8/rqZNm2rTpk2SJLvd7vLBAACnkcMA4FpOC/H999+vxx9/XCEhIVq4cKFiYmLUvHlzM2YDAIgcBgBXsxmGYTh7UGFhoerWrauDBw8qPT1dXbp0kY+Pj8uHO3Vkp8vXAUhSncZd3D0CLKCkOOuCn0sOoyYjg2GGijK43EI8d+7cCl+0f//+FzfVeSCIYRbCGGaobCEmh2EVZDDMUFEGl3uWiV9//dUlwwAAzg85DADmOK9DJtzFy/sqd48Ai2hQx9fdI8ACDh/f5u4RKo0chhnq1nL94T9AbkH5n3g5/VIdAAAAUJNRiAEAAGBpFGIAAABYmtNCXFpaqlmzZmnEiBHKz8/XzJkzOSE8AJiIHAYA13JaiCdMmKBff/3VcXWkr776SklJSS4fDABwGjkMAK7ltBCvX79eycnJ8vHxka+vr+bMmaN169aZMRsAQOQwALia00Ls5eUlD4/fH+bt7S0vr3JPXwwAqGLkMAC4ltNEbdGihRYsWCC73a6dO3dq3rx5atWqlRmzAQBEDgOAqzndQzxy5EhlZGQoOztbvXv3VkFBgRISEsyYDQAgchgAXI0r1QHiSnUwB1eqA86NK9XBDBVdqc7pIRPjxo075/JRo0Zd+EQAgPNGDgOAazk9ZMLf39/xp169evruu+/MmAsA8D/kMAC4VqUPmcjPz9fAgQM1f/58V83kwEd1MAuHTMAMVXXIBDmMmoZDJmCGig6ZqPSlm319fXXo0KGLGggAcOHIYQCoWk6PIX7ppZdks9kkSYZhKCMjQ82bN3f5YACA08hhAHAtp4W4QYMGZW736tVLvXr1ctlAAICyyGEAcC2nhXjv3r2aMGGCGbMAAM6BHAYA13J6DPHWrVtVjU9VDAA1HjkMAK7ldA9xYGCgevbsqfbt26tevXqO5Zz/EgDMQQ4DgGuVW4iLi4vl7e2tjh07qmPHjmbOBAAQOQwAZin3PMTR0dFatmyZ2fOUwfkvYRbOQwwzVPY8xOQwrILzEMMMF3QeYo5XAwD3IocBwBzlHjJx8uRJbdmypdxAbt26tcuGAgCQwwBglnIPmWjTpo0aNWp0ziC22Wz67LPPXD4cH9XBLBwyATNU9pAJchhWwSETMENFh0yUu4c4KChIy5cvd8U8AIDzQA4DgDmcnocYAAAAqMnKLcSdO3c2cw4AwJ+QwwBgjnKPIa4OOHYNZuEYYpihsscQVwfkMMzAMcQwwwWddg0AAACwAgoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNC9XvXBcXJyWLVtW7v1JSUmKiYlx1eoBwNLIYAA4fy67dHNeXp6KiookSRs3btTQoUP19ddfO+738/NT7dq1K3wNLhkKs3DpZpjBzEs3V0UGS+QwzMGlm2GGii7d7LI9xH5+fvLz85Mk1a9fX5IUGBjoqtVBUliPOzRuXJx8fHyUnv6LHhvwrPLy8t09FmqYsPA79Vz8EBmlpTp67LieGTJKu3dlunss/AkZbD4yGGYYn5SgqOgwHT16TJL0/37dqf79hrh3qBqAY4hriIYNAzTrrUm6/4EBat3mNu3atUeJ4xPcPRZqmNq1ffRGyivq33ewunaJ0icff67El0e5eyzA7chgmOWmm/6u/v2GKPiWcAXfEk4ZriIU4hrirrtu18aNP2v79l2SpBkz/60He0e7eSrUNJ6enrLZbPK77PSex3r16unkyZNungpwPzIYZvD29la79q019OkBWv/dx5q/4A1dfXVjd49VI7jskAmYq8nVjZW57zfH7X379qt+/cvk5+fLR3aoMgUFhRr+9Av66D/v62jOMXl4eig8tLe7xwLcjgyGGa688nKt/XK9Xho7Sb9s+VVDhj6m9z6YqS63Rrh7tEsee4hrCA8PD53r+5F2u90N06Cmuu76Fho24kkF3xSmtq26aPKrMzTn39PcPRbgdmQwzLBnzz7dG/OIftnyqyRp6uS31KzZX9W06dVunuzSRyGuIfZmZqlx40aO21dddYVyco6qsPCEG6dCTdP1jmB99+2Pji/RzX5rga67/loFBDRw82SAe5HBMEPrNq0U2zuqzDKbzaZTp0rcM1ANQiGuIdLSvtRNN/5dQUHNJEmPD+irFSv/4+apUNNs+nmLbvnHDQoM/Iuk02ec2Ltnn3Jyjrp5MsC9yGCYobS0VC+/8oJjj/Cjj/VRxuat+u23A26e7NLHMcQ1xOHD2Xr0sWe08P0UeXvX0s4de/TwI0+5eyzUMF+v/VavT52t5R/OV3HxKR07elx9ew9y91iA25HBMMMvW37Vc8PGaOHit+Tp4ams3w7okYeHunusGsFlF+b4o2+++Ub9+/fXtm2VOyk9J4SHWbgwB8xg5oU5/uhCM1gih2EOLswBM1R0YQ5TCvGFIohhFgoxzOCuQnwxyGGYgUIMM1RUiDmGGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaTbDMAx3DwEAAAC4C3uIAQAAYGkUYgAAAFgahRgAAACWRiEGAACApVGIAQAAYGkUYgAAAFgahRgAAACWRiEGAACApVGIAQAAYGkU4ksAFxOEWTZt2qT8/Hx3jwFUO+QwzEAGuw+F+BKwbds2d48AC3jhhRc0evRo2e12d48CVDvkMFyNDHYvCnE1N378eA0dOpTfGOFS48eP1+rVqzV27FjVr1/f3eMA1Qo5DFcjg93Py90DoHyJiYlavny55s+fL19fX3ePgxpqxowZmj9/vr744gtdccUVOnXqlGrVquXusYBqgRyGq5HB1QN7iKupxMRELVu2TPPnz1erVq1UUlLi7pFQAyUlJWn69Ony9vbWjBkzJEm1atXiIztA5DBcjwyuPthDXA1NmjRJS5Ys0aJFi9S8efMyvy3m5OQoICDAzROiJkhOTtYHH3ygDz74QPn5+Ro4cKBOnjyppKQkeXp6ym63y9PT091jAm5BDsPVyODqhT3E1cyhQ4eUkpKie++9V1dffbUkOUJ46tSp6tevnwoKCtw5ImqAnJwc7d69W++9956uv/56dezYURMnTlRaWpri4+MlyRHIgNWQw3A1Mrj6sRmcS6ba2bhxo+Lj4/XAAw8oJiZGAQEBSklJ0bx585SYmKiQkBB3j4gaoLi4WN7e3jIMQzabTXa7XV999ZWeffZZ3X333UpKSpIk9lLAkshhuBoZXL1QiKupjRs3avjw4XryySeVlZWld999VxMnTlRwcLC7R0MNVlpaqrVr1xLIgMhhmI8Mdh8KcTX2/fffa/DgwSoqKlJycrJ69Ojh7pFgAWcCediwYerevbvGjRvn7pEAtyGHYTYy2D04hrgau+GGG5SSkiI/Pz8dOXJEOTk57h4JFuDh4aHbbrtNEydO1OLFizV27Fh3jwS4DTkMs5HB7sEe4kvAmY/tHnroIUVGRvLtZpjCbrdr/fr1aty4sZo3b+7ucQC3IodhNjLYXBTiS8SZL3jExMQoNjZWDRo0cPdIAGAp5DBQc3HIxCWic+fOGjt2rD766CPZbDZ3jwMAlkMOAzUXe4gvMSdOnFCdOnXcPQYAWBY5DNQ8FGIAAABYGodMAAAAwNIoxAAAALA0CjEAAAAsjUIMAAAAS6MQwxT79u3Tddddp8jISMefXr16afHixRf92o8//riWLl0qSYqMjFRubm65j83Ly9NDDz1U6XWsXr1affv2PWv5hg0bFB4e7vT5LVu2rPQVruLi4jR79uxKPQcAzoUMJoNRMS93DwDrqF27tlJTUx23Dx48qPDwcLVp00atWrWqknX88fXP5fjx40pPT6+SdQHApYQMBspHIYbbNGrUSE2bNtXu3bu1ZcsWLV68WCdOnJCvr6/mz5+vRYsW6b333lNpaan8/f31/PPP65prrtHBgwcVFxenQ4cOqXHjxsrOzna8ZsuWLbV+/XoFBARo5syZWrZsmby8vNS0aVMlJycrPj5eRUVFioyM1NKlS7V7926NHz9ex44dk91uV9++fXXvvfdKkqZMmaKVK1fK399fTZs2dbo9u3bt0tixY1VQUKDDhw+rVatWmjx5snx8fCRJkydPVnp6ukpLSzV06FB17dpVksrdTgBwJTKYDMYfGIAJMjMzjQ4dOpRZ9uOPPxo33HCD8dtvvxlLliwxbrjhBiMvL88wDMPYsGGD8eCDDxqFhYWGYRjGV199ZXTv3t0wDMMYNGiQ8dprrxmGYRi7d+82OnToYCxZssQwDMNo0aKFkZ2dbXz66afG3XffbRw7dswwDMNITEw03njjjTJznDp1yggLCzM2b95sGIZh5ObmGj169DB++uknIy0tzQgLCzPy8vKMU6dOGQMGDDD69Olz1nZ9++23Rs+ePQ3DMIzk5GRj+fLlhmEYRnFxsREeHm6sXr3aMdfMmTMNwzCMbdu2GTfeeKORnZ1d4XaOGDHCmDVr1kX93AHAMMhgMhjOsIcYpjmzV0CS7Ha7GjRooFdeeUVXXnmlpNN7Fnx9fSVJX3zxhfbs2aPY2FjH83Nzc3Xs2DF98803GjFihCSpadOmuummm85a1/r169W9e3fVr19fkhQfHy/p9HF0Z+zevVt79+5VQkJCmRm3bNmiHTt26K677nLMc88992j+/PkVbt/w4cO1bt06vfXWW9q9e7cOHTqkwsJCx/29e/eWJLVo0ULXXHONfvrpJ/3www/lbicAVCUymAxG+SjEMM2fj1/7s7p16zr+XlpaqsjISA0fPtxx+9ChQ6pfv75sNpuMP1xg0cvr7P+MPT09ZbPZHLdzc3PP+qKH3W6Xn59fmZmOHDkiPz8/TZgwocw6PD09nW7fM888I7vdrh49eigkJET79+8v8xoeHr9/h7W0tFReXl4VbicAVCUymAxG+TjLBKql4OBgffjhhzp06JAk6b333lO/fv0kSV26dNHChQslSb/99ps2bNhw1vNvvfVWpaWlKT8/X5I0bdo0zZs3T15eXrLb7TIMQ82aNSvzD8T+/fsVHh6uzZs367bbbtPq1auVm5ur0tJSp18UkaSvv/5aTz75pMLCwiRJP//8s+x2u+P+ZcuWSZIyMjK0d+9etW/fvsLtBAB3IYNhNewhRrUUHBysxx57TI888ohsNpt8fX01ffp02Ww2vfDCC4qPj1ePHj10xRVXnPPb0bfffru2b9/u+IgsKChIL730kurUqaN27dqpZ8+eWrBggd544w2NHz9es2bNUklJiZ566il16tRJkrRt2zbdc889uuyyy9SqVSsdPXq0wpmffvppPfnkk6pbt658fX11ww03aO/evY77MzMzFRUVJZvNpkmTJsnf37/C7QQAdyGDyWCrsRl//DwBAAAAsBgOmQAAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRTiS4DdbtfcuXMVExOjyMhIhYWF6ZVXXlFxcfFFvebAgQMVGhqqd955p9LPT09P15AhQy54/X/WrVs3dejQQQUFBWWWL126VC1bttTq1asrfH5eXp4eeuihcu+PjIxUbm7uec+zdOlShYSE6F//+td5P+fPNm3apNGjR0uSNmzYoPDw8At+rYpMmzZNY8eOdclrn6/CwkK9/PLLCg0NVUREhCIiIvTaa6+pqKjIrXMBVYksJosr4u4sXrp0qTp16qTIyEhFRUUpMjJSsbGx+umnn9w206XEy90DwLkxY8bo+PHjevvtt+Xn56fCwkINGzZMI0eO1CuvvHJBr3nw4EF9/fXX+u9//ytPT89KP79t27aaOnXqBa27PA0aNFBaWpqioqIcy5YvX66GDRs6fe7x48eVnp5e7v2pqamVmmX58uV6+umnFRkZWann/dH27dt18ODBC37+paKkpET9+/dXhw4dtHz5ctWpU0cnTpzQxIkT9a9//Utvv/22vLyIGlz6yGKyuLrr3LmzZs6c6bj9+eef6//+7//0xRdfkMNOsIe4mtu3b59WrlypxMRE+fn5SZLq1q2rF198UXfeeaek07+RDxs2TOHh4YqIiNCECRNUUlIi6XRYTps2TbGxserWrZveffdd5efn69FHH1VJSYliYmK0d+9etWzZUjk5OY71nrldUFCgIUOGKDIyUtHR0Ro1apRKS0vL/JZd2fWXp1evXlqxYoXjdlZWlgoLC9W8eXPHssWLF+u+++5TVFSUunbt6ni9+Ph4FRUVKTIyUna7XW3atNFTTz2l0NBQpaenO7Zn+vTpio2Nld1u1+HDhxUcHKxvv/22zByJiYlKT0/XlClTNG/evAq378/rOWP//v2aOnWqNm7cqPj4eEmn96KeCfbu3btr48aNkqTi4mIlJiYqOjpavXr1UlxcnPLz88/6+ZSUlCgpKUmhoaEKCwvTyJEjz9oztWbNGsXGxiomJkYhISGaPHmyJJX7Ppa3vDJWr16t0tJSxcfHq06dOpKkOnXqaOTIkcrPz1daWlqlXg+ojshisviM6prF53LLLbfo8OHDldorb1UU4mouIyNDQUFB8vX1LbM8MDBQoaGhkqRx48bJ399fK1eu1JIlS7Rt2zbNmTNH0un/wRs0aKD3339fU6dOVVJSkmrVqqWUlBTVrl1bqamp+utf/1ru+tPS0lRQUKDU1FQtXrxYkpSZmVnmMZVd/8mTJ8+5rttvv11bt27VoUOHJJ3ek/DHPRQFBQVatGiRUlJStHz5cr322muOvTJJSUmO7fH09NSpU6fUtWtXffLJJ2rbtq3jNQYOHCgvLy/Nnj1bzz33nPr06aObb765zBwJCQlq06aNnnvuOT388MMVbl9567nyyis1ZMgQde7cWUlJSZKkAwcO6OGHH1ZqaqpiY2M1bdo0SVJKSoo8PT21dOlSrVixQpdffrleffXVs34+7777rjIyMpSamqpVq1apoKBAH330keN+wzA0Z84cJScna+nSpVq4cKFSUlKUk5NT7vt4Pu+vMz/99JM6d+581nKbzaZbbrlFP/zwQ6VeD6iOyOIox/1kcfXM4j8zDEMLFy5UixYtFBAQcFGvZQUU4mrOw8PD6W+Ja9euVZ8+fWSz2eTt7a3Y2FitXbvWcf8dd9whSWrdurWKi4tVWFh43uvv1KmTtm/frr59+yolJUX9+vVT06ZNXbL+WrVqKTQ0VKtWrZIkffzxx2WO9apXr55mzJihL7/8UpMnT9aMGTMq3JZzlTRPT0+9+uqreuutt2QYhh5//HGnPwNn23eu9ZxLkyZN1L59e0lSq1atHHuBvvjiC33++eeOY74+/fRT7dix46znf/PNN4qMjFTt2rXl4eGhyZMnl/lHymazacaMGcrIyND06dOVnJwswzB04sSJct/H83l/z8eZvTR/VlxcLJvNVunXA6obspgsPqM6Z/HGjRsdxxD37NlTGzdurPJDamoqCnE1165dO+3cufOsj20OHjyoAQMGqKioSKWlpWVKR2lpaZmC4uPjI0mOxxiGUeE6//jRT5MmTZSWlqYBAwYoPz9f/fv31+eff17m8VW5/qioKK1YsUI//vijmjVrJn9/f8d9Bw4cUFRUlLKystSpUycNHTq0wu2oW7fuOZdnZWXJx8dHe/fu1fHjxyt8jTPbU9H2lbeeP6tVq5bj7zabzfFzKC0tVUJCglJTU5WamqpFixZpypQpZz3/z8d/HTlyxLEHRzr9MWB0dLQyMjJ0/fXX67nnnpOXl5cMwyj3fTyf9zc9PV2RkZGOP3/297//XRs3bjyrLJSWlur7779Xx44dz+vnA1RnZLG/4z6yuHpmsXT6l4LU1FQtX75cH330kaZPn65mzZqd18/F6ijE1VyjRo0UERGhhIQERxDn5+drzJgx8vf3V+3atRUcHKx33nlHhmGouLhYH3zwgW699dZKrScgIMBx3NWZvQLS6Y+G4uPjFRwcrOHDhys4OFhbtmwp89yqWP8Z7du3V1FRkV577TVFR0eXuW/z5s0KCAjQoEGDFBwcrDVr1kg6/S1tLy8v2e12p//A5Obmavjw4UpOTlZ4eLhGjhzpdKYL3T5PT89y95z++fUXLFig4uJilZaW6vnnn9ekSZPOetwtt9yiVatWOR43ZswYffjhh4779+zZo/z8fA0dOlTdunXThg0bHI8t7308n/e3bdu2jn8gzvWFmNDQUNWpU0eJiYmOs0oUFRXppZdeUr169XTXXXc5/RkA1R1Z/DuyuHpmMS4OhfgS8MILLygoKEixsbGKjIzUfffdp6CgII0bN06SNGrUKOXk5DhOd9WsWTM98cQTlVrHqFGjNHbsWEVHR2vHjh0KDAyUdHovgd1uV1hYmGJiYpSXl6e+ffue9dyLXf8fRUZGateuXerSpUuZ5f/4xz/UqFEjde/eXT169ND+/fsVEBCgPXv2KDAwUO3atVPPnj119OjRCrczJCREwcHBGjx4sDIzM7VgwYIK57nQ7evQoYMyMzM1ePDgCh83aNAgXXXVVYqOjlZYWJgMw1BcXNxZj4uNjVXr1q0VExOjiIgIBQYGlnkvWrZsqZCQEPXo0UM9evTQmjVrFBQUpD179pT7Pp7P++uMl5eX5syZo7p16yomJkbh4eGKjo5W3bp1NWfOnDJ7Y4BLGVl8GllcPbMYF8dmOPs1DgAAAKjB2EMMAAAAS6MQAwAAwNIoxAAAALA0CjEAAAAsjUIMAAAAS/Ny/hD3OXVkp7tHgEXUadzF+YOAi1RSnOXuESqNHIYZ6pLBMMGpCjKYPcQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNC9XvXC3bt2UlZV11vJrr71Wq1atctVqAQD/Qw4DwPlxWSGWpLi4OIWHh5ddoZdLVwkA+ANyGACcc2kq+vr6KjAw0JWrsCTDMDRy3ERde83f1P/Be8vc91T8S7q84V808tlBkqTjuXlKnPSGduzeq5Mni/VYv1j16n6HO8ZGDRHW4w6NGxcnHx8fpaf/oscGPKu8vHx3j4VykMNVrzIZ/N0PP+uV6W+pxG6X/2WXacRTj6vVtc3dMTZqmDmzJyt98y967bWZ7h6lRuAY4kvMjt179a8h8Ur74uuz7puzYJF+3LS5zLKR4yaq0eUNtXje63prSqKSJ8/QgUOHzRoXNUzDhgGa9dYk3f/AALVuc5t27dqjxPEJ7h4LME1lMjgvv0BDR47Ts0/+S8v+/aaeHz5Yw55PVHFxsZkjo4Zp1SpI//nkA8XE9HT3KDUKhfgS8/6SVbonIlR3d+1SZvl3P27S19/+oPsjf/8f5HhuntZ//5MGPvJPSdIVlwfq3ZTXVP8yP1NnRs1x1123a+PGn7V9+y5J0oyZ/9aDvaPdPBVgnspk8J7MLPnWq6ubO3eUJDVv2kT16tXVfzdvNXVm1CwDn3hYc+a+qyVL+B5AVXJpIR47dqw6duxY5k92drYrV1njjXx2kHre3bXMskOHs5U8ZYZefuE5eXj+/pbu3febAhsG6N/vL1OfJ57V/Y8M0ZZft6tO7dpmj40aosnVjZW57zfH7X379qt+/cvk5+frxqlQEXK4alUmg//216t0oqhI6zb8IElK/2WbduzaqyPZOabOjJrlqaGj9P77y909Ro3j0mOIBw8erO7du5dZ5u/v78pVWs6pkhI9NyZZI4YMUGDDgLPu2/fbAdWrV1fvzJiovft+00ODhqnp1Vepdatr3TQxLmUeHh4yDOOs5Xa73Q3T4HyQw65VUQb71qunKUmjNTXlbU18Y7Y6t2+jGzu1Vy2+1AhUOy79vzIgIEBNmzZ15SosL2Pr/1Pmbwc0YepbkqQjOUdVWmrXyeJiDegXK0mKDrtLkvTXqxvr7+1aK/2XbRRiXJC9mVm68caOjttXXXWFcnKOqrDwhBunQkXIYdeqKIPHjBiiunXqaN70CY7H94x9VE2ubuyucQGUg19TL3Ed2lynz5bNd9x+ffY7OnYs1/EN5+tbBin140/14L29dCTnqP6b/ov6//Pe8l4OqFBa2pd65eXRCgpqpu3bd+nxAX21YuV/3D0W4DYVZbBhGBo0bLSmJo9Wm+ta6ONPv5S3dy21DGrmxokBnAuFuIabkvi8xk16XQuXfahSw9AT/R9U2+taunssXKIOH87Wo489o4Xvp8jbu5Z27tijhx95yt1jAdWSzWbTy2Oe05iXp+jUqRIFNgzQ1KTRstls7h4NwJ/YjHMdEFgFunXrpoEDB+q+++674Nc4dWRnFU4ElK9O4y7OHwRcpJLis68a50rkMC4VdclgmOBUBRnsskJcFQhimIVCDDOYXYirAjkMM1CIYYaKCjHnIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaV7l3XHs2LEKn+jv71/FowAA/ogcBgBzlFuIb775ZtlsNhmGcdZ9NptNv/zyi0sHAwCrI4cBwBzlFuKtW7eaOQcA4E/IYQAwh9NjiEtLSzV79mzFxcUpPz9fM2fOlN1uN2M2AIDIYQBwNaeFeMKECdq2bZt+/vlnGYahr776SklJSWbMBgAQOQwArua0EK9fv17Jycny8fGRn5+f5syZo3Xr1pkxGwBA5DAAuJrTQuzl5SUPj98f5u3tLS+vcg89BgBUMXIYAFzLaaK2aNFCCxYskN1u186dOzVv3jy1atXKjNkAACKHAcDVnO4hHjlypDIyMpSdna3evXuroKBACQkJZswGABA5DACuZjPOdYLLauLUkZ3uHgEWUadxF3ePAAsoKc5y9wiVRg7DDHXJYJjgVAUZ7HQPcXZ2tp555hnddNNNCg4OVkJCgnJzc6t0QABA+chhAHAtp4V41KhRatKkiRYvXqx33nlH9evX1+jRo82YDQAgchgAXM3pl+qysrL05ptvOm6PGDFCERERLh0KAPA7chgAXMvpHuLLL79cmZmZjtsHDhxQYGCgS4cCAPyOHAYA1yp3D/ETTzwhScrJyVFUVJRuvfVWeXh4aMOGDWrZsqVpAwKAVZHDAGCOcgtxaGjoOZeHhIS4ahYAwB+QwwBgjnILcXR09DmXG4ahPXv2uGwgAMBp5DAAmMPpl+ref/99TZgwQSdOnHAsCwgI0Lp161w6GADgNHIYAFzLaSFOSUnR3Llz9eabb2ro0KFas2aNDhw4YMZsAACRwwDgak7PMuHv76/27dvruuuuU3Z2tgYOHKjvv//ejNkAACKHAcDVnBZiLy8vHT9+XE2bNtWmTZskSXa73eWDAQBOI4cBwLWcFuL7779fjz/+uEJCQrRw4ULFxMSoefPmZswGABA5DACuZjMMw3D2oMLCQtWtW1cHDx5Uenq6unTpIh8fH5cPd+rITpevA5CkOo27uHsEWEBJcdYFP5ccRk1WlwyGCU5VkMHlFuK5c+dW+KL9+/e/uKnOA0EMs1CIYYbKFmJyGFZBIYYZKirE5Z5l4tdff3XJMACA80MOA4A5zuuQCXfxrdvM3SPAImp5eLp7BFjA0fzt7h6h0ry8r3L3CLAAP+867h4BFlBRBjv9Uh0AAABQk1GIAQAAYGkUYgAAAFia00JcWlqqWbNmacSIEcrPz9fMmTM5ITwAmIgcBgDXclqIJ0yYoF9//dVxdaSvvvpKSUlJLh8MAHAaOQwAruW0EK9fv17Jycny8fGRr6+v5syZo3Xr1pkxGwBA5DAAuJrTQuzl5SUPj98f5u3tLS+vck9fDACoYuQwALiW00Rt0aKFFixYILvdrp07d2revHlq1aqVGbMBAEQOA4CrOd1DPHLkSGVkZCg7O1u9e/dWQUGBEhISzJgNACByGABcjSvVAeJKdTAHV6oDzo0r1cEMFWWw00Mmxo0bd87lo0aNuvCJAADnjRwGANdyesiEv7+/40+9evX03XffmTEXAOB/yGEAcK1KHzKRn5+vgQMHav78+a6ayYFDJmAWDpmAGarqkAkzc5hDJmAGDpmAGSrK4EpfutnX11eHDh26qIEAABeOHAaAquX0GOKXXnpJNptNkmQYhjIyMtS8eXOXDwYAOI0cBgDXclqIGzRoUOZ2r1691KtXL5cNBAAoixwGANdyWoj37t2rCRMmmDELAOAcyGEAcC2nxxBv3bpV1fhUxQBQ45HDAOBaTvcQBwYGqmfPnmrfvr3q1avnWM75LwHAHOQwALhWuYW4uLhY3t7e6tixozp27GjmTAAAkcMAYJZyz0McHR2tZcuWmT1PGZyHGGbhPMQwQ2XPQ1wdcpjzEMMMnIcYZrig8xBzvBoAuBc5DADmKPeQiZMnT2rLli3lBnLr1q1dNhQAgBwGALOUe8hEmzZt1KhRo3MGsc1m02effeby4ThkAmbhkAmYobKHTFSHHOaQCZiBQyZghooyuNw9xEFBQVq+fLkr5gEAnAdyGADM4fQ8xAAAAEBNVm4h7ty5s5lzAAD+hBwGAHOUewxxdcAxxDALxxDDDJU9hrg64BhimIFjiGGGCzrtGgAAAGAFFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpXq564bi4OC1btqzc+5OSkhQTE+Oq1QOApZHBAHD+XHbp5ry8PBUVFUmSNm7cqKFDh+rrr7923O/n56fatWtX+Bpcuhlm4dLNMIOZl26uigyWuHQzzMGlm2EGt1y62c/PT4GBgQoMDFT9+vUlyXE7MDDwvIIYlRcecZf2H0x39xiowa5v3UIrP16gL9et0Odrl6l9h9buHgnnQAabL6zHHfrxhzRlbF6r99+bKT8/X3ePhBqIDHYNjiGuQa655m8an5ggm83m7lFQQ9WpU1tLUudp6mspuv0fvfTKy68rZc4kd48FuF3DhgGa9dYk3f/AALVuc5t27dqjxPEJ7h4LNQwZ7DoU4hqiTp3amjXnNcXHjXf3KKjBut4RrN079yrtP19Kkj7+8FM90neIm6cC3O+uu27Xxo0/a/v2XZKkGTP/rQd7R7t5KtQ0ZLDrUIhriKnTEjVn9rvanP6Lu0dBDRYU1EwHDx3R1NeT9PnaZVq28m15ernsu7nAJaPJ1Y2Vue83x+19+/arfv3LOGwCVYoMdh0KcQ3w2IA+KrGXaP6/F7l7FNRwtWp56a67b9fbc99Xt9uilTJjvj5YOkve3t7uHg1wKw8PD53rO+p2u90N06CmIoNdh0JcA/yzz73q9Pd2+ubbD7V02VzVqVNb33z7oa648nJ3j4YaZv/+Q/p12w79sPFnSac/rvP09NTfmjVx82SAe+3NzFLjxo0ct6+66grl5BxVYeEJN06FmoYMdh0KcQ0QcluUbryhu269uadiovvrxIki3XpzTx3Yf8jdo6GG+fQ/X6pp06sd32q+9R83yDAM7dmd6ebJAPdKS/tSN934dwUFnT5d6OMD+mrFyv+4eSrUNGSw63DgCYDzdujQEfXpPVCvvvai6tWrq5Mni/XQg4N08mSxu0cD3Orw4Ww9+tgzWvh+iry9a2nnjj16+JGn3D0Wahgy2HUoxDXM3r1ZuuLyNu4eAzXYN+u+111d73X3GEC18/Hqz/Xx6s/dPQZqODLYNVx2pbqqwJXqYBauVAczmHmluqrClepgBq5UBzO45Up1AAAAwKWAQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0myGYRjuHgIAAABwF/YQAwAAwNIoxAAAALA0CjEAAAAsjUIMAAAAS6MQAwAAwNIoxAAAALA0CjEAAAAsjUIMAAAAS6MQAwAAwNIoxJcALiYIs2zatEn5+fnuHgOodshhmIEMdh8K8SVg27Zt7h4BFvDCCy9o9OjRstvt7h4FqHbIYbgaGexeFOJqbvz48Ro6dCi/McKlxo8fr9WrV2vs2LGqX7++u8cBqhVyGK5GBrufl7sHQPkSExO1fPlyzZ8/X76+vu4eBzXUjBkzNH/+fH3xxRe64oordOrUKdWqVcvdYwHVAjkMVyODqwf2EFdTiYmJWrZsmebPn69WrVqppKTE3SOhBkpKStL06dPl7e2tGTNmSJJq1arFR3aAyGG4HhlcfbCHuBqaNGmSlixZokWLFql58+ZlflvMyclRQECAmydETZCcnKwPPvhAH3zwgfLz8zVw4ECdPHlSSUlJ8vT0lN1ul6enp7vHBNyCHIarkcHVC3uIq5lDhw4pJSVF9957r66++mpJcoTw1KlT1a9fPxUUFLhzRNQAOTk52r17t9577z1df/316tixoyZOnKi0tDTFx8dLkiOQAashh+FqZHD1YzM4l0y1s3HjRsXHx+uBBx5QTEyMAgIClJKSonnz5ikxMVEhISHuHhE1QHFxsby9vWUYhmw2m+x2u7766is9++yzuvvuu5WUlCRJ7KWAJZHDcDUyuHqhEFdTGzdu1PDhw/Xkk08qKytL7777riZOnKjg4GB3j4YarLS0VGvXriWQAZHDMB8Z7D4U4mrs+++/1+DBg1VUVKTk5GT16NHD3SPBAs4E8rBhw9S9e3eNGzfO3SMBbkMOw2xksHtwDHE1dsMNNyglJUV+fn46cuSIcnJy3D0SLMDDw0O33XabJk6cqMWLF2vs2LHuHglwG3IYZiOD3YM9xJeAMx/bPfTQQ4qMjOTbzTCF3W7X+vXr1bhxYzVv3tzd4wBuRQ7DbGSwuSjEl4gzX/CIiYlRbGysGjRo4O6RAMBSyGGg5uKQiUtE586dNXbsWH300Uey2WzuHgcALIccBmou9hBfYk6cOKE6deq4ewwAsCxyGKh5KMQAAACwNA6ZAAAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhhin27dun6667TpGRkY4/vXr10uLFiy/6tR9//HEtXbpUkhQZGanc3NxyH5uXl6eHHnqo0utYvXq1+vbte9byDRs2KDw83OnzW7ZsWekrXMXFxWn27NmVeg4AnAsZTAajYl7uHgDWUbt2baWmpjpuHzx4UOHh4WrTpo1atWpVJev44+ufy/Hjx5Wenl4l6wKASwkZDJSPQgy3adSokZo2bardu3dry5YtWrx4sU6cOCFfX1/Nnz9fixYt0nvvvafS0lL5+/vr+eef1zXXXKODBw8qLi5Ohw4dUuPGjZWdne14zZYtW2r9+vUKCAjQzJkztWzZMnl5ealp06ZKTk5WfHy8ioqKFBkZqaVLl2r37t0aP368jh07Jrvdrr59++ree++VJE2ZMkUrV66Uv7+/mjZt6nR7du3apbFjx6qgoECHDx9Wq1atNHnyZPn4+EiSJk+erPT0dJWWlmro0KHq2rWrJJW7nQDgSmQwGYw/MAATZGZmGh06dCiz7McffzRuuOEG47fffjOWLFli3HDDDUZeXp5hGIaxYcMG48EHHzQKCwsNwzCMr776yujevbthGIYxaNAg47XXXjMMwzB2795tdOjQwViyZIlhGIbRokULIzs72/j000+Nu+++2zh27JhhGIaRmJhovPHGG2XmOHXqlBEWFmZs3rzZMAzDyM3NNXr06GH89NNPRlpamhEWFmbk5eUZp06dMgYMGGD06dPnrO369ttvjZ49exqGYRjJycnG8uXLDcMwjOLiYiM8PNxYvXq1Y66ZM2cahmEY27ZtM2688UYjOzu7wu0cMWKEMWvWrIv6uQOAYZDBZDCcYQ8xTHNmr4Ak2e12NWjQQK+88oquvPJKSaf3LPj6+kqSvvjiC+3Zs0exsbGO5+fm5urYsWP65ptvNGLECElS06ZNddNNN521rvXr16t79+6qX7++JCk+Pl7S6ePozti9e7f27t2rhISEMjNu2bJFO3bs0F133eWY55577tH8+fMr3L7hw4dr3bp1euutt7R7924dOnRIhYWFjvt79+4tSWrRooWuueYa/fTTT/rhhx/K3U4AqEpkMBmM8lGIYZo/H7/2Z3Xr1nX8vbS0VJGRkRo+fLjj9qFDh1S/fn3ZbDYZf7jAopfX2f8Ze3p6ymazOW7n5uae9UUPu90uPz+/MjMdOXJEfn5+mjBhQpl1eHp6Ot2+Z555Rna7XT169FBISIj2799f5jU8PH7/Dmtpaam8vLwq3E4AqEpkMBmM8nGWCVRLwcHB+vDDD3Xo0CFJ0nvvvad+/fpJkrp06aKFCxdKkn777Tdt2LDhrOffeuutSktLU35+viRp2rRpmjdvnry8vGS322UYhpo1a1bmH4j9+/crPDxcmzdv1m233abVq1crNzdXpaWlTr8oIklff/21nnzySYWFhUmSfv75Z9ntdsf9y5YtkyRlZGRo7969at++fYXbCQDuQgbDathDjGopODhYjz32mB555BHZbDb5+vpq+vTpstlseuGFFxQfH68ePXroiiuuOOe3o2+//XZt377d8RFZUFCQXnrpJdWpU0ft2rVTz549tWDBAr3xxhsaP368Zs2apZKSEj311FPq1KmTJGnbtm265557dNlll6lVq1Y6evRohTM//fTTevLJJ1W3bl35+vrqhhtu0N69ex33Z2ZmKioqSjabTZMmTZK/v3+F2wkA7kIGk8FWYzP++HkCAAAAYDEcMgEAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAA4YbfbNXfuXMXExCgyMlJhYWF65ZVXVFxcfFGvOXDgQIWGhuqdd96p9PPT09M1ZMiQC17/n3Xr1k0dOnRQQUFBmeVLly5Vy5YttXr16gqfn5eXp4ceeqjc+yMjI5Wbm3ve8yxdulQhISH617/+dd7P+bNNmzZp9OjRkqQNGzYoPDz8gl+rItOmTdPYsWNd8trnY8OGDWrXrp0iIyMdf+6880498cQTOnr0qNvmupRQiC8BBDFBXBF3B7Ek5eTkaMyYMQoNDVWvXr0UFRWlWbNmqaSkxK1zAVVlzJgx+umnn/T2228rNTVVixcv1q5duzRy5MgLfs2DBw/q66+/1kcffaQ+ffpU+vlt27bV1KlTL3j959KgQQOlpaWVWbZ8+XI1bNjQ6XOPHz+u9PT0cu9PTU3VZZdddt6zLF++XE8//bRmz5593s/5s+3bt+vgwYMX/PxLyV//+lelpqY6/nzyySfy8PDQnDlz3D3aJYFCfAkgiAni6iw/P1+9e/dW48aN9eGHH2rFihV6++23lZ6ermHDhrl7POCi7du3TytXrlRiYqL8/PwkSXXr1tWLL76oO++8U9LpX8qHDRum8PBwRUREaMKECY5fCNu2batp06YpNjZW3bp107vvvqv8/Hw9+uijKikpUUxMjPbu3auWLVsqJyfHsd4ztwsKCjRkyBBFRkYqOjpao0aNUmlpaZlftCu7/vL06tVLK1ascNzOyspSYWGhmjdv7li2ePFi3XfffYqKilLXrl0drxcfH6+ioiJFRkbKbrerTZs2euqppxQaGqr09HTH9kyfPl2xsbGy2+06fPiwgoOD9e2335aZIzExUenp6ZoyZYrmzZtX4fb9eT1n7N+/X1OnTtXGjRsVHx8vSSosLNTTTz+tyMhIde/eXRs3bpQkFRcXKzExUdHR0erVq5fi4uKUn59/1s+npKRESUlJCg0NVVhYmEaOHHnWzqk1a9YoNjZWMTExCgkJ0eTJkyWp3PexvOUXKz8/Xzk5Oapfv/5Fv5YVUIirOYKYID6jugbx+++/r2bNmmnAgAHy8vKSJNWvX18TJkzQd999p02bNlXq9YDqJiMjQ0FBQfL19S2zPDAwUKGhoZKkcePGyd/fXytXrtSSJUu0bds2x5654uJiNWjQQO+//76mTp2qpKQk1apVSykpKapdu7ZSU1P117/+tdz1p6WlqaCgwLFDRJIyMzPLPKay6z958uQ513X77bdr69atOnTokKTTOxOioqIc9xcUFGjRokVKSUnR8uXL9dprr+mVV16RJCUlJTm2x9PTU6dOnVLXrl31ySefqG3bto7XGDhwoLy8vDR79mw999xz6tOnj26++eYycyQkJKhNmzZ67rnn9PDDD1e4feWt58orr9SQIUPUuXNnJSUlSZIOHDighx9+WKmpqYqNjdW0adMkSSkpKfL09NTSpUu1YsUKXX755Xr11VfP+vm8++67ysjIUGpqqlatWqWCggJ99NFHjvsNw9CcOXOUnJyspUuXauHChUpJSVFOTk657+P5vL/nY+/evYqMjFTPnj11yy236OGHH1a3bt3Ur1+/Sr+WFVGIqzmCOMpxP0FcPYP4hx9+0I033njWch8fH3Xu3Fk//vhjpV4PqG48PDyc/qK4du1a9enTRzabTd7e3oqNjdXatWsd999xxx2SpNatW6u4uFiFhYXnvf5OnTpp+/bt6tu3r1JSUtSvXz81bdrUJeuvVauWQkNDtWrVKknSxx9/XOZwr3r16mnGjBn68ssvNXnyZM2YMaPCbencufNZyzw9PfXqq6/qrbfekmEYevzxx53+DJxt37nWcy5NmjRR+/btJUmtWrVy7Aj64osv9PnnnysqKkqRkZH69NNPtWPHjrOe/8033ygyMlK1a9eWh4eHJk+eXObfKZvNphkzZigjI0PTp09XcnKyDMPQiRMnyn0fz+f9PR9nDpn48MMPNWzYMB0+fFg9evRQrVq1Kv1aVkQhruYIYoL4jOocxBWpio/+AHdq166ddu7cedYnNwcPHtSAAQNUVFSk0tJS2Ww2x32lpaVljqH38fGRJMdjDMOocJ1//PSnSZMmSktL04ABA5Sfn6/+/fvr888/L/P4qlx/VFSUVqxYoR9//FHNmjWTv7+/474DBw4oKipKWVlZ6tSpk4YOHVrhdtStW/ecy7OysuTj46O9e/fq+PHjFb7Gme2paPvKW8+f/bEc2mw2x8+htLRUCQkJjuNvFy1apClTppz1/DOfgp1x5MgRx04c6fQngdHR0crIyND111+v5557Tl5eXjIMo9z38Xze3/T09DJfmHPmnnvuUbdu3fTUU0/xXY7zRCGu5ghif8d9BHH1DOK///3v+u677xy3jx07puLiYhUXF+vHH390/BIAXKoaNWqkiIgIJSQkOLI4Pz9fY8aMkb+/v2rXrq3g4GC98847MgxDxcXF+uCDD3TrrbdWaj0BAQGOQ6/O7BiQTn86FB8fr+DgYA0fPlzBwcHasmVLmedWxfrPaN++vYqKivTaa68pOjq6zH2bN29WQECABg0apODgYK1Zs0bS6S9qe3l5yW63O/03Jjc3V8OHD1dycrLCw8PP6/swF7p9np6e51UIg4ODtWDBAhUXF6u0tFTPP/+8Jk2adNbjbrnlFq1atcrxuDFjxujDDz903L9nzx7l5+dr6NCh6tatmzZs2OB4bHnv4/m8v23bti3zhbnzMWzYMO3fv18LFiw4r8dbHYW4miOIf0cQV88g7t27t3bt2qWUlBTZ7XatX79eEREReuKJJ9ShQwd16tTJ6c8AqO5eeOEFBQUFKTY2VpGRkbrvvvsUFBSkcePGSZJGjRqlnJwcRUREKCIiQs2aNdMTTzxRqXWMGjVKY8eOVXR0tHbs2KHAwEBJp3cU2O12hYWFKSYmRnl5eerbt+9Zz73Y9f9RZGSkdu3apS5dupRZ/o9//EONGjVS9+7d1aNHD+3fv18BAQHas2ePAgMD1a5dO/Xs2bPCU32NGjVKISEhCg4O1uDBg5WZmem0tF3o9nXo0EGZmZkaPHhwhY8bNGiQrrrqKkVHRyssLEyGYSguLu6sx8XGxqp169aKiYlRRESEAgMDy7wXLVu2VEhIiHr06KEePXpozZo1CgoK0p49e8p9H8/n/b0Ql112mYYNG6Zp06bpyJEjF/16NZ3NcNYg4HYlJSV644039J///Eeenp4qLi7WnXfeqf/7v/+Tt7e3jh49qnHjxmnbtm06deqUunTpoueee07e3t5q2bKl1q9fr4CAAEly3C4sLFRERIR++uknSdKHH36oSZMm6bLLLtOtt96q1NRUrVixQrVr11ZCQoK2bdumOnXq6Morr1RiYqK2bt2ql156SatWrbqg9Z+5fUa3bt00ZcoUtW3bVm+++aYWLFigL774Ql5eXurbt6/++c9/6vbbb9fTTz+tXbt2yWaz6cYbb1RaWpoWLFigpk2bql+/fsrJydGCBQt08803n3O9Y8aMUcOGDTV69GgVFxfr3nvv1QMPPKB//vOfZeY5s87u3btXavv+aM+ePXrsscfUokUL9e3b1/Hzkk6fhu3M7aKiIr388sv67rvvZLfbdd111+mll14667hxu92uiRMnau3atTIMQzfeeKNGjhypN998U0ePHtWoUaM0atQobdiwQd7e3mrRooW2b9+uuLg4derU6ZzvY61atc65vLLfSj569KimTJmi9evXq1atWrLb7WrRooUOHz6sZ599llIMAKjWKMQAXCYzM1O5ublq3bq1u0cBAKBcFGIAAABYGscQAwAAwNIoxAAAALA0CjEAAAAszcv5Q9zn1JGd7h4BFlG3cRfnDwIu0qniLHePUGnkMMxQhwyGCUoqyGD2EAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSvFz1wt26dVNWVtZZy6+99lqtWrXKVasFAPwPOQwA58dlhViS4uLiFB4eXnaFXi5dJQDgD8hhAHDOpano6+urwMBAV67CkgzD0MhxE3XtNX9T/wfvlSQFhz2gRoENHY/p/+A9Cg/tpvRftunlKSk6caJIpaWleqTPfYoI7eau0VGDzJk9Wembf9Frr8109yioADlc9SqTwWcsXfWJPlv7jV6f8KLp86JmCetxh8aNi5OPj4/S03/RYwOeVV5evrvHuuSxm+ASs2P3Xo2f+IbSt2zVtdf8TZK0a88+1b/MT0vefr3MYw3D0NMjx+ul+Kd1yw0ddeDQYd3f///U7vqWatrkKjdMj5qgVasgTZ2SqBtv7Kj0zb+4exzAVJXJYEk6npunyTPm6cP/rFHnjm1NnhY1TcOGAZr11iTdFhKl7dt3KSkxQYnjE/R/QxLcPdolj0J8iXl/ySrdExGqKxv9vsfnv5u3yMPDQw8NHKa8ggLdHRKsAf1iVVJi18D+/9QtN3SUJF1xeaAa+NfXwUNHKMS4YAOfeFhz5r6rzMyzj00FarrKZLCnp6dWf7ZWlzcM0LDBj+qLdRvcODlqgrvuul0bN/6s7dt3SZJmzPy3ftyYRiGuAi4txGPHjlViYmKZZZ9++qn+8pe/uHK1NdrIZwdJkr757kfHMrvdrls6d9DQgY+opKREg4a/IN96ddX3gWjdExHqeNyi1I9UcOKE2rVpZfrcqDmeGjpKknTXnbe7eRKcD3K4alU2gx+I7ilJWv5hmlvmRc3S5OrGytz3m+P2vn37Vb/+ZfLz8+WwiYvk0kI8ePBgde/evcwyf39/V67Sku7t1aPM7X4PRGvB4lT1fSDasWzW/A/0zqLlmjFxnGr7+Jg9IgA3IYdd73wyGKgKHh4eMgzjrOV2u90N09QsLi3EAQEBatq0qStXAUkrVn+mlkHN1TKomSTJkOH4FnlxcbFGjp+kHbv3asHM13TVlY3cOSoAk5HDrldRBgNVaW9mlm68saPj9lVXXaGcnKMqLDzhxqlqBi7MUQNs37lbr8+aL7vdrqKTJ/XukpXqfsdtkqS4sa8ov6BQ78yYRBkGABeoKIOBqpSW9qVuuvHvCvrfL1+PD+irFSv/4+apagZ+ha0BBj7yT42f9IaiHxqokhK77u7aRfdEdNd/N/+i/6z5Wn9rcpX6PvGs4/HPDHpE/7ipkxsnBoCao7wMBqra4cPZevSxZ7Tw/RR5e9fSzh179PAjT7l7rBrBZpzrYJQq0K1bNw0cOFD33XffBb/GqSM7q3AioHx1G3dx9wiwgFPF5p6ZgxzGpaIOGQwTlFSQwS4rxFWBIIZZKMQwg9mFuCqQwzADhRhmqKgQcwwxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEvzKu+OY8eOVfhEf3//Kh4FAPBH5DAAmKPcQnzzzTfLZrPJMIyz7rPZbPrll19cOhgAWB05DADmKLcQb9261cw5AAB/Qg4DgDmcHkNcWlqq2bNnKy4uTvn5+Zo5c6bsdrsZswEARA4DgKs5LcQTJkzQtm3b9PPPP8swDH311VdKSkoyYzYAgMhhAHA1p4V4/fr1Sk5Olo+Pj/z8/DRnzhytW7fOjNkAACKHAcDVnBZiLy8veXj8/jBvb295eZV76DEAoIqRwwDgWk4TtUWLFlqwYIHsdrt27typefPmqVWrVmbMBgAQOQwAruZ0D/HIkSOVkZGh7Oxs9e7dWwUFBUpISDBjNgCAyGEAcDWbca4TXFYTp47sdPcIsIi6jbu4ewRYwKniLHePUGnkMMxQhwyGCUoqyGCne4izs7P1zDPP6KabblJwcLASEhKUm5tbpQMCAMpHDgOAazktxKNGjVKTJk20ePFivfPOO6pfv75Gjx5txmwAAJHDAOBqTr9Ul5WVpTfffNNxe8SIEYqIiHDpUACA35HDAOBaTvcQX3755crMzHTcPnDggAIDA106FADgd+QwALhWuXuIn3jiCUlSTk6OoqKidOutt8rDw0MbNmxQy5YtTRsQAKyKHAYAc5RbiENDQ8+5PCQkxFWzAAD+gBwGAHOUW4ijo6PPudwwDO3Zs8dlAwEATiOHAcAcTr9U9/7772vChAk6ceKEY1lAQIDWrVvn0sEAAKeRwwDgWk4LcUpKiubOnas333xTQ4cO1Zo1a3TgwAEzZgMAiBwGAFdzepYJf39/tW/fXtddd52ys7M1cOBAff/992bMBgAQOQwArua0EHt5een48eNq2rSpNm3aJEmy2+0uHwwAcBo5DACu5bQQ33///Xr88ccVEhKihQsXKiYmRs2bNzdjNgCAyGEAcDWbYRiGswcVFhaqbt26OnjwoNLT09WlSxf5+Pi4fLhTR3a6fB2AJNVt3MXdI8ACThVnXfBzyWHUZHXIYJigpIIMLrcQz507t8IX7d+//8VNdR4IYpiFQgwzVLYQk8OwCgoxzFBRIS73LBO//vqrS4YBAJwfchgAzHFeh0y4i5f3Ve4eARZRy9PpGQiBi3bixKV3MQ1yGGaoW8v1h/8AuQXlf+Ll9Et1AAAAQE1GIQYAAIClUYgBAABgaU4LcWlpqWbNmqURI0YoPz9fM2fO5ITwAGAichgAXMtpIZ4wYYJ+/fVXx9WRvvrqKyUlJbl8MADAaeQwALiW00K8fv16JScny8fHR76+vpozZ47WrVtnxmwAAJHDAOBqTguxl5eXPDx+f5i3t7e8vDhFFQCYhRwGANdymqgtWrTQggULZLfbtXPnTs2bN0+tWrUyYzYAgMhhAHA1p3uIR44cqYyMDGVnZ6t3794qKChQQkKCGbMBAEQOA4CrcaU6QFypDubgSnXAuXGlOpihoivVOW0B48aNO+fyUaNGXfhEAIDzRg4DgGs5PWTC39/f8adevXr67rvvzJgLAPA/5DAAuFalD5nIz8/XwIEDNX/+fFfN5MBHdTALh0zADFV1yAQ5jJqGQyZghooOmaj0pZt9fX116NChixoIAHDhyGEAqFpOd4u99NJLstlskiTDMJSRkaHmzZu7fDAAwGnkMAC4ltNC3KBBgzK3e/XqpV69erlsIABAWeQwALiW00K8d+9eTZgwwYxZAADnQA4DgGs5PYZ469atqsanKgaAGo8cBgDXcrqHODAwUD179lT79u1Vr149x3LOfwkA5iCHAcC1yi3ExcXF8vb2VseOHdWxY0czZwIAiBwGALOUex7i6OhoLVu2zOx5yuD8lzAL5yGGGSp7HmJyGFbBeYhhhgs6DzHHqwGAe5HDAGCOcneLnTx5Ulu2bCk3kFu3bu2yoQAA5DAAmKXcQybatGmjRo0anTOIbTabPvvsM5cPx0d1MAuHTMAMlT1kghyGVXDIBMxQ0SET5baAoKAgLV++3BXzAADOAzkMAOZweh5iAAAAoCYrtxB37tzZzDkAAH9CDgOAOco9hrg64Ng1mIVjiGGGyh5DXB2QwzADxxDDDBd02jUAAADACijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgwAAABLoxADAADA0lx2ea64uDgtW7as3PuTkpIUExPjqtUDgKWRwQBw/lx26ea8vDwVFRVJkjZu3KihQ4fq66+/dtzv5+en2rVrV/gaXDIUZuHSzTCDmZdurooMlshhmINLN8MMFV262WUtwM/PT35+fpKk+vXrS5ICAwNdtTpICutxh8aNi5OPj4/S03/RYwOeVV5evrvHQg3zxBP99NhjfWQYhnbu3KMnn4zT4cPZ7h4Lf0IGm48MhhnGJyUoKjpMR48ekyT9v193qn+/Ie4dqgbgGOIaomHDAM16a5Luf2CAWre5Tbt27VHi+AR3j4UapmPHNho69DF17Rqjzp3v1o4duzV69LPuHgtwOzIYZrnppr+rf78hCr4lXMG3hFOGqwiFuIa4667btXHjz9q+fZckacbMf+vB3tFungo1zU8/bVabNiHKzc2Tj4+PGjdupJyco+4eC3A7Mhhm8Pb2Vrv2rTX06QFa/93Hmr/gDV19dWN3j1UjUIhriCZXN1bmvt8ct/ft26/69S+Tn5+vG6dCTVRSUqKIiLu1ffu3Cg6+Sf/+9yJ3jwS4HRkMM1x55eVa++V6vTR2km65sYe+//4nvffBTHePVSNQiGsIDw8Pnev7kXa73Q3ToKZbufI/atKko8aNe00rV86XzWZz90iAW5HBMMOePft0b8wj+mXLr5KkqZPfUrNmf1XTple7ebJLH4W4htibmaXGjRs5bl911RXKyTmqwsITbpwKNU3z5k11662dHbfffvsD/fWvV6lBg/punApwPzIYZmjdppVie0eVWWaz2XTqVIl7BqpBKMQ1RFral7rpxr8rKKiZJOnxAX21YuV/3DwVaporr7xc//73dP3lLw0kSbGxUcrI2KacnGPuHQxwMzIYZigtLdXLr7zg2CP86GN9lLF5q3777YCbJ7v0cfLVGuLw4Ww9+tgzWvh+iry9a2nnjj16+JGn3D0Waph1677Xyy9P1yefLFRJSYn27z+k++8f4O6xALcjg2GGX7b8queGjdHCxW/J08NTWb8d0CMPD3X3WDWCyy7M8UfffPON+vfvr23btlXqeZwQHmbhwhwwg5kX5vijC81giRyGObgwB8xQ0YU5TCnEF4oghlkoxDCDuwrxxSCHYQYKMcxQUSHmGGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKXZDMMw3D0EAAAA4C7sIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgvAVxMEGbZtGmT8vPz3T0GUO2QwzADGew+FOJLwLZt29w9AizghRde0OjRo2W32909ClDtkMNwNTLYvSjE1dz48eM1dOhQfmOES40fP16rV6/W2LFjVb9+fXePA1Qr5DBcjQx2Py93D4DyJSYmavny5Zo/f758fX3dPQ5qqBkzZmj+/Pn64osvdMUVV+jUqVOqVauWu8cCqgVyGK5GBlcP7CGuphITE7Vs2TLNnz9frVq1UklJibtHQg2UlJSk6dOny9vbWzNmzJAk1apVi4/sAJHDcD0yuPpgD3E1NGnSJC1ZskSLFi1S8+bNy/y2mJOTo4CAADdPiJogOTlZH3zwgT744APl5+dr4MCBOnnypJKSkuTp6Sm73S5PT093jwm4BTkMVyODqxf2EFczhw4dUkpKiu69915dffXVkuQI4alTp6pfv34qKChw54ioAXJycrR792699957uv7669WxY0dNnDhRaWlpio+PlyRHIANWQw7D1cjg6sdmcC6Zamfjxo2Kj4/XAw88oJiYGAUEBCglJUXz5s1TYmKiQkJC3D0iaoDi4mJ5e3vLMAzZbDbZ7XZ99dVXevbZZ3X33XcrKSlJkthLAUsih+FqZHD1QiGupjZu3Kjhw4frySefVFZWlt59911NnDhRwcHB7h4NNVhpaanWrl1LIAMih2E+Mth9KMTV2Pfff6/BgwerqKhIycnJ6tGjh7tHggWcCeRhw4ape/fuGjdunLtHAtyGHIbZyGD34BjiauyGG25QSkqK/Pz8dOTIEeXk5Lh7JFiAh4eHbrvtNk2cOFGLFy/W2LFj3T0S4DbkMMxGBrsHe4gvAWc+tnvooYcUGRnJt5thCrvdrvXr16tx48Zq3ry5u8cB3IochtnIYHNRiC8RZ77gERMTo9jYWDVo0MDdIwGApZDDQM3FIROXiM6dO2vs2LH66KOPZLPZ3D0OAFgOOQzUXOwhvsScOHFCderUcfcYAGBZ5DBQ81CIAQAAYGkcMgEAAABLoxADAADA0ijEAAAAsDQKMQAAACyNQgxT7Nu3T9ddd50iIyMdf3r16qXFixdf9Gs//vjjWrp0qSQpMjJSubm55T42Ly9PDz30UKXXsXr1avXt2/es5Rs2bFB4eLjT57ds2bLSV7iKi4vT7NmzK/UcADgXMpgMRsW83D0ArKN27dpKTU113D548KDCw8PVpk0btWrVqkrW8cfXP5fjx48rPT29StYFAJcSMhgoH4UYbtOoUSM1bdpUu3fv1pYtW7R48WKdOHFCvr6+mj9/vhYtWqT33ntPpaWl8vf31/PPP69rrrlGBw8eVFxcnA4dOqTGjRsrOzvb8ZotW7bU+vXrFRAQoJkzZ2rZsmXy8vJS06ZNlZycrPj4eBUVFSkyMlJLly7V7t27NX78eB07dkx2u119+/bVvffeK0maMmWKVq5cKX9/fzVt2tTp9uzatUtjx45VQUGBDh8+rFatWmny5Mny8fGRJE2ePFnp6ekqLS3V0KFD1bVrV0kqdzsBwJXIYDIYf2AAJsjMzDQ6dOhQZtmPP/5o3HDDDcZvv/1mLFmyxLjhhhuMvLw8wzAMY8OGDcaDDz5oFBYWGoZhGF999ZXRvXt3wzAMY9CgQcZrr71mGIZh7N692+jQoYOxZMkSwzAMo0WLFkZ2drbx6aefGnfffbdx7NgxwzAMIzEx0XjjjTfKzHHq1CkjLCzM2Lx5s2EYhpGbm2v06NHD+Omnn4y0tDQjLCzMyMvLM06dOmUMGDDA6NOnz1nb9e233xo9e/Y0DMMwkpOTjeXLlxuGYRjFxcVGeHi4sXr1asdcM2fONAzDMLZt22bceOONRnZ2doXbOWLECGPWrFkX9XMHAMMgg8lgOMMeYpjmzF4BSbLb7WrQoIFeeeUVXXnllZJO71nw9fWVJH3xxRfas2ePYmNjHc/Pzc3VsWPH9M0332jEiBGSpKZNm+qmm246a13r169X9+7dVb9+fUlSfHy8pNPH0Z2xe/du7d27VwkJCWVm3LJli3bs2KG77rrLMc8999yj+fPnV7h9w4cP17p16/TWW29p9+7dOnTokAoLCx339+7dW5LUokULXXPNNfrpp5/0ww8/lLudAFCVyGAyGOWjEMM0fz5+7c/q1q3r+HtpaakiIyM1fPhwx+1Dhw6pfv36stlsMv5wgUUvr7P/M/b09JTNZnPczs3NPeuLHna7XX5+fmVmOnLkiPz8/DRhwoQy6/D09HS6fc8884zsdrt69OihkJAQ7d+/v8xreHj8/h3W0tJSeXl5VbidAFCVyGAyGOXjLBOoloKDg/Xhhx/q0KFDkqT33ntP/fr1kyR16dJFCxculCT99ttv2rBhw1nPv/XWW5WWlqb8/HxJ0rRp0zRv3jx5eXnJbrfLMAw1a9aszD8Q+/fvV3h4uDZv3qzbbrtNq1evVm5urkpLS51+UUSSvv76az355JMKCwuTJP3888+y2+2O+5ctWyZJysjI0N69e9W+ffsKtxMA3IUMhtWwhxjVUnBwsB577DE98sgjstls8vX11fTp02Wz2fTCCy8oPj5ePXr00BVXXHHOb0fffvvt2r59u+MjsqCgIL300kuqU6eO2rVrp549e2rBggV64403NH78eM2aNUslJSV66qmn1KlTJ0nStm3bdM899+iyyy5Tq1atdPTo0Qpnfvrpp/Xkk0+qbt268vX11Q033KC9e/c67s/MzFRUVJRsNpsmTZokf3//CrcTANyFDCaDrcZm/PHzBAAAAMBiOGQCAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiC8Rdrtdc+fOVUxMjCIjIxUWFqZXXnlFxcXFF/WaAwcOVGhoqN55551KPz89PV1Dhgy54PX/Wbdu3dShQwcVFBSUWb506VK1bNlSq1evrvD5eXl5euihh8q9PzIyUrm5uec9z9KlSxUSEqJ//etf5/2cP9u0aZNGjx4tSdqwYYPCw8Mv+LUqMm3aNI0dO9Ylr32+li5dqpiYGPXq1Us9e/bUyJEjlZeX59aZgKpEDpPDFXFnDm/fvl2RkZGKjIxUSEiIOnXq5Lg9b948t8x0qfFy9wA4P2PGjNHx48f19ttvy8/PT4WFhRo2bJhGjhypV1555YJe8+DBg/r666/13//+V56enpV+ftu2bTV16tQLWnd5GjRooLS0NEVFRTmWLV++XA0bNnT63OPHjys9Pb3c+1NTUys1y/Lly/X0008rMjKyUs/7o+3bt+vgwYMX/PxLxaZNm/T6669ryZIl8vf3l91u14svvqgxY8Zo4sSJ7h4PqBLkMDlcXQUFBTl+tkuXLtUnn3yimTNnunmqSwt7iC8B+/bt08qVK5WYmCg/Pz9JUt26dfXiiy/qzjvvlHT6t/Jhw4YpPDxcERERmjBhgkpKSiSdDsxp06YpNjZW3bp107vvvqv8/Hw9+uijKikpUUxMjPbu3auWLVsqJyfHsd4ztwsKCjRkyBBFRkYqOjpao0aNUmlpaZnftCu7/vL06tVLK1ascNzOyspSYWGhmjdv7li2ePFi3XfffYqKilLXrl0drxcfH6+ioiJFRkbKbrerTZs2euqppxQaGqr09HTH9kyfPl2xsbGy2+06fPiwgoOD9e2335aZIzExUenp6ZoyZYrmzZtX4fb9eT1n7N+/X1OnTtXGjRsVHx8vSSosLHSEe/fu3bVx40ZJUnFxsRITExUdHa1evXopLi5O+fn5Z/18SkpKlJSUpNDQUIWFhWnkyJFn7Z1as2aNYmNjFRMTo5CQEE2ePFmSyn0fy1teGYcPH5ZhGCoqKpIkeXp66qmnntJ9991XqdcBqitymBw+o7rmMC6SgWpv9erVxj333FPhY5577jnjpZdeMkpLS42TJ08ajzzyiDFz5kzDMAyjRYsWxvz58w3DMIz09HSjTZs2RlFRkZGZmWl06NDB8RotWrQwsrOzz7q9bNky45FHHjEMwzBKSkqMkSNHGrt37za+/fZbo2fPnhe8/j/r2rWr8cMPPxi33HKLcfDgQcMwDOP111835s+fb/Tp08f4+OOPjfz8fOP+++83cnJyDMMwjJ9++smxDefanmXLlp21PSUlJcY///lPY+bMmcbDDz9svPnmm+f8mZ5Z5/ls3x/X80dLliwxBgwYYBiGYXz77bfGddddZ/z3v/81DMMw5s6dazz00EOGYRjGtGnTjOTkZKO0tNQwDMOYOHGi8cILL5z1em+//bbxz3/+0zhx4oRht9uNp556yli2bJkxdepU48UXXzRKS0uNPn36GLt27TIMwzAOHDhgXHfddRW+j+Utr4zi4mLjmWeeMa677jojKirKePHFF401a9Y4tge41JHD5PAZ1TWHz7W9OH/sIb4EeHh4OP1Nce3aterTp49sNpu8vb0VGxurtWvXOu6/4447JEmtW7dWcXGxCgsLz3v9nTp10vbt29W3b1+lpKSoX79+atq0qUvWX6tWLYWGhmrVqlWSpI8//rjM8V716tXTjBkz9OWXX2ry5MmaMWNGhdvSuXPns5Z5enrq1Vdf1VtvvSXDMPT44487/Rk4275zredcmjRpovbt20uSWrVq5dgT9MUXX+jzzz9XVFSUIiMj9emnn2rHjh1nPf+bb75RZGSkateuLQ8PD02ePLnMx5o2m00zZsxQRkaGpk+fruTkZBmGoRMnTpT7Pp7P++tMrVq1NHHiRK1Zs0b9+/fXqVOnNGLECD399NOVeh2guiKHyeEzqmsO4+JQiC8B7dq1086dO8/66ObgwYMaMGCAioqKVFpaKpvN5rivtLTU8VGSJPn4+EiS4zGGYVS4zj9+/NOkSROlpaVpwIABys/PV//+/fX555+XeXxVrj8qKkorVqzQjz/+qGbNmsnf399x34EDBxQVFaWsrCx16tRJQ4cOrXA76tate87lWVlZ8vHx0d69e3X8+PEKX+PM9lS0feWt589q1arl+LvNZnP8HEpLS5WQkKDU1FSlpqZq0aJFmjJlylnP9/Iqe9j/kSNHdOjQIcftwsJCRUdHKyMjQ9dff72ee+45eXl5yTCMct/H83l/09PTHV/QONexfIsXL9Znn32mRo0aqVevXnrppZe0bNkyrV69uszHv8Clihz2d9xHDlfPHMbFoRBfAho1aqSIiAglJCQ4wjg/P19jxoyRv7+/ateureDgYL3zzjsyDEPFxcX64IMPdOutt1ZqPQEBAY5jr87sGZCkd999V/Hx8QoODtbw4cMVHBysLVu2lHluVaz/jPbt26uoqEivvfaaoqOjy9y3efNmBQQEaNCgQQoODtaaNWsknf6mtpeXl+x2u9N/ZHJzczV8+HAlJycrPDxcI0eOdDrThW6fp6dnmcCu6PUXLFig4uJilZaW6vnnn9ekSZPOetwtt9yiVatWOR43ZswYffjhh4779+zZo/z8fA0dOlTdunXThg0bHI8t7308n/e3bdu2jn8kzvWlGA8PD7366qs6cOCAY9n/+3//T40bN1b9+vWdbj9Q3ZHDvyOHq2cO4+JQiC8RL7zwgoKCghQbG6vIyEjdd999CgoK0rhx4yRJo0aNUk5OjiIiIhQREaFmzZrpiSeeqNQ6Ro0apbFjxyo6Olo7duxQYGCgpNN7Cux2u8LCwhQTE6O8vDz17dv3rOde7Pr/KDIyUrt27VKXLl3KLP/HP/6hRo0aqXv37urRo4f279+vgIAA7dmzR4GBgWrXrp169uypo0ePVridISEhCg4O1uDBg5WZmakFCxZUOM+Fbl+HDh2UmZmpwYMHV/i4QYMG6aqrrlJ0dLTCwsJkGIbi4uLOelxsbKxat26tmJgYRUREKDAwsMx70bJlS4WEhKhHjx7q0aOH1qxZo6CgIO3Zs6fc9/F83l9nYmJi1KdPHz322GMKDQ1V9+7d9d5772n27NkX9M15oDoih08jh6tnDuPi2Axnv8YBAAAANRh7iAEAAGBpFGIAAABYGoUYAAAAlkYhBgAAgKVRiAEAAGBpXs4f4j6njux09wiwiDqNuzh/EHCRSoqz3D1CpZHDMAMZDDNUlMHsIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClebnqhbt166asrKyzll977bVatWqVq1YLAPgfchgAzo/LCrEkxcXFKTw8vOwKvVy6SgDAH5DDAOCcS1PR19dXgYGBrlyFJRmGoZHjJuraa/6m/g/eK0kKDntAjQIbOh7T/8F7FB7aTd/98LNefX22Suwlqu3trfinB6rt9S3dNTpqgLAed2jcuDj5+PgoPf0XPTbgWeXl5bt7LJSDHK56lcngM5au+kSfrf1Gr0940fR5UbOQwa7BboJLzI7dezV+4htK37JV117zN0nSrj37VP8yPy15+/Uyjz116pSGjU7SzNfG6boWQfpi3QbFj31Fq96f5YbJURM0bBigWW9N0m0hUdq+fZeSEhOUOD5B/zckwd2jAaaoTAZL0vHcPE2eMU8f/meNOndsa/K0qGnIYNfhS3WXmPeXrNI9EaG6u2sXx7L/bt4iDw8PPTRwmKIfGqg35yyQ3W5XrVq19FnqO7quRZAMw9C+3w6ofv3L3Dg9LnV33XW7Nm78Wdu375IkzZj5bz3YO9rNUwHmqUwGS9Lqz9bq8oYBGjb4UXeNjBqEDHYdl+4hHjt2rBITE8ss+/TTT/WXv/zFlaut0UY+O0iS9M13PzqW2e123dK5g4YOfEQlJSUaNPwF+darq74PRKuWl5eO5BzV/f3/T0ePH9erY+PdNTpqgCZXN1bmvt8ct/ft26/69S+Tn58vH9lVU+Rw1apsBj8Q3VOStPzDNLfMi5qFDHYdlxbiwYMHq3v37mWW+fv7u3KVlnRvrx5lbvd7IFoLFqeq7wOnf2tsGNBAn6e+oy3btuvRp+J1zd/+qr/99Wp3jIpLnIeHhwzDOGv5mb1hqH7IYddzlsFAVSGDXcelh0wEBASoadOmZf54enq6cpWWtGL1Z9r2v49PJMmQIS8vL+XlF+jTL9c5ll/fMkgtgprp/+3Y7YYpURPszcxS48aNHLevuuoK5eQcVWHhCTdOhYqQw65XXgYDVY0Mdh2OIa4Btu/crddnzZfdblfRyZN6d8lKdb/jNnl6eGh00mT9uCnjf4/bo1179qlta84ygQuTlvalbrrx7woKaiZJenxAX61Y+R83TwW4V3kZDFQ1Mth1+BW2Bhj4yD81ftIbin5ooEpK7Lq7axfdE9FdNptNU5Ke18tTZqqkxC5v71qaMOY5XXE5p2DChTl8OFuPPvaMFr6fIm/vWtq5Y48efuQpd48FuFV5GQxUNTLYdWzGuQ5GqQLdunXTwIEDdd99913wa5w6srMKJwLKV6dxF+cPAi5SSfHZV41zJXIYlwoyGGaoKINdVoirAkEMsxDGMIPZhbgqkMMwAxkMM1SUwRxDDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSKMQAAACwNAoxAAAALI1CDAAAAEujEAMAAMDSvMq749ixYxU+0d/fv4pHAQD8ETkMAOYotxDffPPNstlsMgzjrPtsNpt++eUXlw4GAFZHDgOAOcotxFu3bjVzDgDAn5DDAGAOp8cQl5aWavbs2YqLi1N+fr5mzpwpu91uxmwAAJHDAOBqTgvxhAkTtG3bNv38888yDENfffWVkpKSzJgNACByGABczWkhXr9+vZKTk+Xj4yM/Pz/NmTNH69atM2M2AIDIYQBwNaeF2MvLSx4evz/M29tbXl7lHnoMAKhi5DAAuJbTRG3RooUWLFggu92unTt3at68eWrVqpUZswEARA4DgKs53UM8cuRIZWRkKDs7W71791ZBQYESEhLMmA0AIHIYAFzNZpzrBJfVxKkjO909AiyiTuMu7h4BFlBSnOXuESqNHIYZyGCYoaIMdrqHODs7W88884xuuukmBQcHKyEhQbm5uVU6IACgfOQwALiW00I8atQoNWnSRIsXL9Y777yj+vXra/To0WbMBgAQOQwArub0S3VZWVl68803HbdHjBihiIgIlw4FAPgdOQwAruV0D/Hll1+uzMxMx+0DBw4oMDDQpUMBAH5HDgOAa5W7h/iJJ56QJOXk5CgqKkq33nqrPDw8tGHDBrVs2dK0AQHAqshhADBHuYU4NDT0nMtDQkJcNQsA4A/IYQAwR7mFODo6+pzLDcPQnj17XDYQAOA0chgAzOH0S3Xvv/++JkyYoBMnTjiWBQQEaN26dS4dDABwGjkMAK7ltBCnpKRo7ty5evPNNzV06FCtWbNGBw4cMGM2AIDIYQBwNadnmfD391f79u113XXXKTs7WwMHDtT3339vxmwAAJHDAOBqTguxl5eXjh8/rqZNm2rTpk2SJLvd7vLBAACnkcMA4FpOC/H999+vxx9/XCEhIVq4cKFiYmLUvHlzM2YDAIgcBgBXsxmGYTh7UGFhoerWrauDBw8qPT1dXbp0kY+Pj8uHO3Vkp8vXAUhSncZd3D0CLKCkOOuCn0sOoyYjg2GGijK43EI8d+7cCl+0f//+FzfVeSCIYRbCGGaobCEmh2EVZDDMUFEGl3uWiV9//dUlwwAAzg85DADmOK9DJtzFy/sqd48Ai6jl6fQMhMBFO3Hi0ruYRi1yGCbw9qrl7hFgAQWFu8u9z+mX6gAAAICajEIMAAAAS6MQAwAAwNKcFuLS0lLNmjVLI0aMUH5+vmbOnMkJ4QHAROQwALiW00I8YcIE/frrr46rI3311VdKSkpy+WAAgNPIYQBwLaeFeP369UpOTpaPj498fX01Z84crVu3zozZAAAihwHA1ZwWYi8vL3l4/P4wb29veXlxiioAMAs5DACu5TRRW7RooQULFshut2vnzp2aN2+eWrVqZcZsAACRwwDgak73EI8cOVIZGRnKzs5W7969VVBQoISEBDNmAwCIHAYAV+NKdYC4Uh3MwZXqgHPjSnUwQ0VXqnPaAsaNG3fO5aNGjbrggQAA548cBgDXcnrIhL+/v+NPvXr19N1335kxFwDgf8hhAHCtSh8ykZ+fr4EDB2r+/PmumsmBQyZgFg6ZgBmq6pAJM3OYQyZgBg6ZgBkqOmSi0pdu9vX11aFDhy5mHgDARSCHAaBqOd0t9tJLL8lms0mSDMNQRkaGmjdv7vLBAACnkcMA4FpOC3GDBg3K3O7Vq5d69erlsoEAAGWRwwDgWk4L8d69ezVhwgQzZgEAnAM5DACu5fQY4q1bt6oan6oYAGo8chgAXMvpHuLAwED17NlT7du3V7169RzLOf8lAJiDHAYA1yq3EBcXF8vb21sdO3ZUx44dzZwJACByGADMUu55iKOjo7Vs2TKz5ymD8xDDLJyHGGao7HmIq0MOcx5imIHzEMMMF3QeYo5XAwD3IocBwBzl7hY7efKktmzZUm4gt27d2mVDAQDIYQAwS7mHTLRp00aNGjU6ZxDbbDZ99tlnLh+OQyZgFg6ZgBkqe8hEdchhDpmAGThkAmao6JCJcltAUFCQli9f7oJxAADngxwGAHM4PQ8xAAAAUJOVW4g7d+5s5hwAgD8hhwHAHOUeQ1wdcAwxzMIxxDBDZY8hrg44hhhm4BhimOGCTrsGAAAAWAGFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWBqFGAAAAJZGIQYAAIClUYgBAABgaRRiAAAAWJrLLs8VFxenZcuWlXt/UlKSYmJiXLV6ALA0MhgAzp/LLt2cl5enoqIiSdL/b+/u46Kq8///PwcRL4JENrIsl9VcxTIvNq2tRUN3U0EUwTIstXQ3y4tv2oUJalqkyNpH82pLzdKWzDIVzS78rLVZampZVqhlPy9QvEQhRURCZt6/P/o4SQqIOecg53G/3bzdmjMz57wOY0+fnDkzZ9OmTRo+fLjWrl3rvT8oKEg1a9Yscx1cuhlW4dLNsIKVl26+FBkscelmWINLN8MKtly6OSgoSKGhoQoNDVWdOnUkyXs7NDT0goIYFRMd9Vd99eUqbd3yqd5cOFtBQYF2j4Qq6JFHHtCXX67Spk3/0aJFLys09Hd2j4TzIIPt8+orU/XYYw/bPQaquJhunXTo8Ba7x6gyOIe4irjqqhDNfXmKet07UDc1b6/du/coZcIou8dCFdO6dXMNH/6QOnSIV5s2nbRzZ6bGjn3C7rGASiE8vLH+87+LFB/f1e5RUMXdcMMflJIySi6Xy+5RqgwKcRVx1113atOmb7Rjx25J0qzZ/9Z9veNsngpVzebNW9S8eaTy8k6oRo0aql+/nnJzf7R7LKBSGPTIg3p13htasuRdu0dBFVarVk298upUJSaOt3uUKoVCXEU0uL6+svYd8N7et++g6tS5ktMmcMkVFxerW7dO2rFjgyIibtO///223SMBlcKw4WP05pvL7B4DVdyMGSl69ZUF2pLxvd2jVCkU4irCz89P5/t8pNvttmEaVHUrVvxHDRq01vjxL2jFijTetgMACzw0sI+K3W4ORPgAhbiK2Ju1X/Xr1/Pevu66a5Sb+6MKCk7ZOBWqmkaNwnTHHW28t197bZF+//vrVLduHRunAgBn6NPnbt3ypxZav+F9LU2fp1q1amr9hvd1zbVX2z3aZY9CXEWsWvWJbrv1T2rcuKEk6eGBffXOiv/YPBWqmmuvvVr//vdM/e53dSVJCQk9tHXrduXmHrN3MABwgDvb91Dbtp11+5+jFR/XX6dOFer2P0fr0MFsu0e77PHlq1XEkSM5+sdDj+utN+coIKC6du3cowcHDLN7LFQx69Z9oX/+c6b+93/fUnFxsQ4ezFavXgPtHgsAgN/EZxfmONtnn32m/v37a/v27RV6HhfmgFW4MAesYOWFOc52sRkscWEOWIMLc8AKZV2Yw5JCfLEoxLAKhRhWsKsQ/xYUYliBQgwr2HKlOgAAAOByQCEGAACAo1GIAQAA4GgUYgAAADgahRgAAACORiEGAACAo1GIAQAA4GgUYgAAADgahRgAAACORiEGAACAo1GIAQAA4GgUYgAAADgahRgAAACORiEGAACAo1GIAQAA4GgUYgAAADgahRgAAACORiEGAACAo1GIAQAA4GgUYgAAADgahRgAAACORiEGAACAo1GIAQAA4GgUYgAAADgahRgAAACORiEGAACAo1GIAQAA4GgUYgAAADgahRgAAACORiEGAACAo1GIAQAA4GgUYgAAADgahRgAAACORiEGAACAo1GIAQAA4GgUYgAAADgahRgAAACORiEGAACAo1GIAQAA4GguY4yxewgAAADALhwhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiC8DXEwQVvn222+Vn59v9xhApUMOwwpksH0oxJeB7du32z0CHGDcuHEaO3as3G633aMAlQ45DF8jg+1FIa7kJkyYoOHDh/MbI3xqwoQJWrlypZKTk1WnTh27xwEqFXIYvkYG28/f7gFQupSUFC1btkxpaWkKDAy0exxUUbNmzVJaWppWr16ta665RqdPn1b16tXtHguoFMhh+BoZXDlwhLiSSklJUXp6utLS0hQeHq7i4mK7R0IVNHHiRM2cOVMBAQGaNWuWJKl69eq8ZQeIHIbvkcGVB0eIK6EpU6ZoyZIlevvtt9WoUaMSvy3m5uYqJCTE5glRFaSmpmrRokVatGiR8vPzNWjQIP3000+aOHGiqlWrJrfbrWrVqtk9JmALchi+RgZXLhwhrmSys7M1Z84c3X333br++uslyRvC06dP1wMPPKCTJ0/aOSKqgNzcXGVmZmrhwoW68cYb1bp1a02ePFmrVq1SUlKSJHkDGXAachi+RgZXPi7Dd8lUOps2bVJSUpLuvfdexcfHKyQkRHPmzNH8+fOVkpKiyMhIu0dEFVBUVKSAgAAZY+RyueR2u7VmzRo98cQT6tSpkyZOnChJHKWAI5HD8DUyuHKhEFdSmzZt0ogRIzRkyBDt379fb7zxhiZPnqyIiAi7R0MV5vF49OmnnxLIgMhhWI8Mtg+FuBL74osvNHToUBUWFio1NVVRUVF2jwQHOBPITz75pLp06aLx48fbPRJgG3IYViOD7cE5xJVY27ZtNWfOHAUFBeno0aPKzc21eyQ4gJ+fn9q3b6/Jkydr8eLFSk5OtnskwDbkMKxGBtuDI8SXgTNv2/Xr10+xsbF8uhmWcLvdWr9+verXr69GjRrZPQ5gK3IYViODrUUhvkyc+YBHfHy8EhISVLduXbtHAgBHIYeBqotTJi4Tbdq0UXJyst5//325XC67xwEAxyGHgaqLI8SXmVOnTqlWrVp2jwEAjkUOA1UPhRgAAACOxikTAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEsMS+ffvUrFkzxcbGev90795dixcv/s3rfvjhh7V06VJJUmxsrPLy8kp97IkTJ9SvX78Kb2PlypXq27fvOcs3btyomJiYcp/ftGnTCl/hKjExUa+88kqFngMA50MGk8Eom7/dA8A5atasqeXLl3tvHz58WDExMWrevLnCw8MvyTbOXv/5HD9+XBkZGZdkWwBwOSGDgdJRiGGbevXqKSwsTJmZmdq2bZsWL16sU6dOKTAwUGlpaXr77be1cOFCeTweBQcH6+mnn9YNN9ygw4cPKzExUdnZ2apfv75ycnK862zatKnWr1+vkJAQzZ49W+np6fL391dYWJhSU1OVlJSkwsJCxcbGaunSpcrMzNSECRN07Ngxud1u9e3bV3fffbckadq0aVqxYoWCg4MVFhZW7v7s3r1bycnJOnnypI4cOaLw8HBNnTpVNWrUkCRNnTpVGRkZ8ng8Gj58uDp06CBJpe4nAPgSGUwG4ywGsEBWVpZp1apViWVfffWVadu2rTlw4IBZsmSJadu2rTlx4oQxxpiNGzea++67zxQUFBhjjFmzZo3p0qWLMcaYwYMHmxdeeMEYY0xmZqZp1aqVWbJkiTHGmCZNmpicnBzz4Ycfmk6dOpljx44ZY4xJSUkxL774Yok5Tp8+baKjo82WLVuMMcbk5eWZqKgos3nzZrNq1SoTHR1tTpw4YU6fPm0GDhxo+vTpc85+bdiwwXTt2tUYY0xqaqpZtmyZMcaYoqIiExMTY1auXOmda/bs2cYYY7Zv325uvfVWk5OTU+Z+jhw50sydO/c3/dwBwBgymAxGeThCDMucOSogSW63W3Xr1tXzzz+va6+9VtLPRxYCAwMlSatXr9aePXuUkJDgfX5eXp6OHTumzz77TCNHjpQkhYWF6bbbbjtnW+vXr1eXLl1Up04dSVJSUpKkn8+jOyMzM1N79+7VqFGjSsy4bds27dy5U3fddZd3np49eyotLa3M/RsxYoTWrVunl19+WZmZmcrOzlZBQYH3/t69e0uSmjRpohtuuEGbN2/Wl19+Wep+AsClRAaTwSgdhRiW+fX5a79Wu3Zt7397PB7FxsZqxIgR3tvZ2dmqU6eOXC6XzFkXWPT3P/evcbVq1eRyuby38/Lyzvmgh9vtVlBQUImZjh49qqCgIE2aNKnENqpVq1bu/j3++ONyu92KiopSZGSkDh48WGIdfn6/fIbV4/HI39+/zP0EgEuJDCaDUTq+ZQKVUkREhN577z1lZ2dLkhYuXKgHHnhAktSuXTu99dZbkqQDBw5o48aN5zz/jjvu0KpVq5Sfny9JmjFjhubPny9/f3+53W4ZY9SwYcMS/0AcPHhQMTEx2rJli9q3b6+VK1cqLy9PHo+n3A+KSNLatWs1ZMgQRUdHS5K++eYbud1u7/3p6emSpK1bt2rv3r1q2bJlmfsJAHYhg+E0HCFGpRQREaGHHnpIAwYMkMvlUmBgoGbOnCmXy6Vx48YpKSlJUVFRuuaaa8776eg777xTO3bs8L5F1rhxYz333HOqVauWWrRooa5du2rBggV68cUXNWHCBM2dO1fFxcUaNmyYbrnlFknS9u3b1bNnT1155ZUKDw/Xjz/+WObMjz32mIYMGaLatWsrMDBQbdu21d69e733Z2VlqUePHnK5XJoyZYqCg4PL3E8AsAsZTAY7jcuc/X4CAAAA4DCcMgEAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjElwm326158+YpPj5esbGxio6O1vPPP6+ioqLftM5Bgwapc+fOev311yv8/IyMDD366KMXvf1f69ixo1q1aqWTJ0+WWL506VI1bdpUK1euLPP5J06cUL9+/Uq9PzY2Vnl5eRc8z9KlSxUZGam///3vF/ycX/v22281duxYSdLGjRsVExNz0esqy4wZM5ScnOyTdV+I0vYtOTlZM2bMsGEi4NIjh8nhstiZwydPntSf/vQnff311+fc98gjj2j+/PmWz3S58bd7AFyYZ555RsePH9drr72moKAgFRQU6Mknn9To0aP1/PPPX9Q6Dx8+rLVr1+rrr79WtWrVKvz8m2++WdOnT7+obZembt26WrVqlXr06OFdtmzZMl111VXlPvf48ePKyMgo9f7ly5dXaJZly5bpscceU2xsbIWed7YdO3bo8OHDF/18AJUHOUwOV1ZXXHGFYmNjtXjxYrVq1cq7/NChQ/r88881adIk+4a7THCE+DKwb98+rVixQikpKQoKCpIk1a5dW88++6z+9re/Sfr5t/Inn3xSMTEx6tatmyZNmqTi4mJJPwfmjBkzlJCQoI4dO+qNN95Qfn6+/vGPf6i4uFjx8fHau3evmjZtqtzcXO92z9w+efKkHn30UcXGxiouLk5jxoyRx+Mp8Zt2Rbdfmu7du+udd97x3t6/f78KCgrUqFEj77LFixfrnnvuUY8ePdShQwfv+pKSklRYWKjY2Fi53W41b95cw4YNU+fOnZWRkeHdn5kzZyohIUFut1tHjhxRRESENmzYUGKOlJQUZWRkaNq0aZo/f36Z+/fr7Zxx8OBBTZ8+XZs2bVJSUpIkqaCgwBvuXbp00aZNmyRJRUVFSklJUVxcnLp3767ExETl5+ef8/MpLi7WxIkT1blzZ0VHR2v06NHnHJ36+OOPlZCQoPj4eEVGRmrq1KmSVOrrWNpyAL8gh8nhMyprDt9///364IMPVFBQUOJ16tq1q6688soKrcuRDCq9lStXmp49e5b5mKeeeso899xzxuPxmJ9++skMGDDAzJ492xhjTJMmTUxaWpoxxpiMjAzTvHlzU1hYaLKyskyrVq2862jSpInJyck553Z6eroZMGCAMcaY4uJiM3r0aJOZmWk2bNhgunbtetHb/7UOHTqYL7/80tx+++3m8OHDxhhj/vWvf5m0tDTTp08f88EHH5j8/HzTq1cvk5uba4wxZvPmzd59ON/+pKenn7M/xcXF5v777zezZ882Dz74oHnppZfO+zM9s80L2b+zt3O2JUuWmIEDBxpjjNmwYYNp1qyZ+frrr40xxsybN8/069fPGGPMjBkzTGpqqvF4PMYYYyZPnmzGjRt3zvpee+01c//995tTp04Zt9tthg0bZtLT08306dPNs88+azwej+nTp4/ZvXu3McaYQ4cOmWbNmpX5Opa2vCLO/rtwtmeffdZMnz69QusCKiNymBw+o7Lm8Jmf15IlS4wxxrjdbhMZGWm+++67Cq/HiThCfBnw8/Mr9zfFTz/9VH369JHL5VJAQIASEhL06aefeu//61//Kkm66aabVFRUVOI3yPLccsst2rFjh/r27as5c+bogQceUFhYmE+2X716dXXu3FnvvvuuJOmDDz4ocb7XFVdcoVmzZumTTz7R1KlTNWvWrDL3pU2bNucsq1atmv7nf/5HL7/8sowxevjhh8v9GZS3f+fbzvk0aNBALVu2lCSFh4d7jwStXr1a//3vf9WjRw/Fxsbqww8/1M6dO895/meffabY2FjVrFlTfn5+mjp1aom3NV0ul2bNmqWtW7dq5syZSk1NlTFGp06dKvV1vJDXtzx+fuePEo/HU+p9wOWEHCaHz6isOSxJ9913n5YsWeL9eV177bUKDw+v8HqciH+pLgMtWrTQrl27znnr5vDhwxo4cKAKCwvl8Xjkcrm893k8Hu9bSZJUo0YNSfI+xhhT5jbPfvunQYMGWrVqlQYOHKj8/Hz1799f//3vf0s8/lJuv0ePHnrnnXf01VdfqWHDhgoODvbed+jQIfXo0UP79+/XLbfcouHDh5e5H7Vr1z7v8v3796tGjRrau3evjh8/XuY6zuxPWftX2nZ+rXr16t7/drlc3p+Dx+PRqFGjtHz5ci1fvlxvv/22pk2bds7z/f1LnvZ/9OhRZWdne28XFBQoLi5OW7du1Y033qinnnpK/v7+MsaU+jpeyOubkZGh2NhY759fq1u3ro4dO3bO8pycnBKvH3C5IoeDvfeRw5UzhyXprrvu0t69e5WZmalFixbp/vvvv6CfCSjEl4V69eqpW7duGjVqlDeM8/Pz9cwzzyg4OFg1a9ZURESEXn/9dRljVFRUpEWLFumOO+6o0HZCQkK8516dOTIgSW+88YaSkpIUERGhESNGKCIiQtu2bSvx3Eux/TNatmypwsJCvfDCC4qLiytx35YtWxQSEqLBgwcrIiJCH3/8saSfP6nt7+8vt9td7j8yeXl5GjFihFJTUxUTE6PRo0eXO9PF7l+1atVKBHZZ61+wYIGKiork8Xj09NNPa8qUKec87vbbb9e7777rfdwzzzyj9957z3v/nj17lJ+fr+HDh6tjx47auHGj97GlvY4X8vrefPPN3n8kzvehmEaNGikgIEDvv/++d9mOHTu0ceNG/eUvfyl3/4HKjhz+BTlcOXNY+rms9+rVS//+97+1bds2derUqdz9xs8oxJeJcePGqXHjxkpISFBsbKzuueceNW7cWOPHj5ckjRkzRrm5uerWrZu6deumhg0b6pFHHqnQNsaMGaPk5GTFxcVp586dCg0NlfTzkQK3263o6GjFx8frxIkT6tu37znP/a3bP1tsbKx2796tdu3alVj+l7/8RfXq1VOXLl0UFRWlgwcPKiQkRHv27FFoaKhatGihrl276scffyxzPyMjIxUREaGhQ4cqKytLCxYsKHOei92/Vq1aKSsrS0OHDi3zcYMHD9Z1112nuLg4RUdHyxijxMTEcx6XkJCgm266SfHx8erWrZtCQ0NLvBZNmzZVZGSkoqKiFBUVpY8//liNGzfWnj17Sn0dL+T1LY+fn59mz56tJUuWqFu3boqJidGoUaM0adIk/eEPf6jQuoDKihz+GTlcOXP4jF69emnRokWKj48vcTQcZXOZ8n6NAwAAAKowjhADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0fzLf4h9Th/dZfcIcIha9duV/yDgNyou2m/3CBVGDsMKtclgWOB0GRnMEWIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4mr+vVtyxY0ft37//nOV//OMf9e677/pqswCA/0MOA8CF8VkhlqTExETFxMSU3KC/TzcJADgLOQwA5fNpKgYGBio0NNSXm3AkY4xGj5+sP97wB/W/725JUkT0vaoXepX3Mf3v66mYzh2V8d12/XPaHJ06VSiPx6MBfe5Rt84d7RodVUB01F81fnyiatSooYyM7/TQwCd04kS+3WOhFOTwpXe+DD5jWNJzuvqq32n0E4MlSTt379Ezk6aroKBQLpf02KAB+sttt9gxNqqYV1+Zqowt3+mFF2bbPUqVwGGCy8zOzL2aMPlFZWz7Xn+84Q+SpN179qnOlUFa8tq/SjzWGKPHRk/Qc0mP6fa2rXUo+4h69f9/anFjU4U1uM6G6XG5u+qqEM19eYraR/bQjh27NTFllFImjNL/e3SU3aMBljhfBp/x6oK39dW3W9Sl453eZc9N/pfiunZSfExnfffDDvUfOlJr318kf/9qFk+OqiI8vLGmT0vRrbe2VsaW7+wep8qgEF9m3lzyrnp266xr6/1yxOfrLdvk5+enfoOe1ImTJ9UpMkIDH0hQcbFbg/rfr9vbtpYkXXN1qOoG19Hh7KMUYlyUu+66U5s2faMdO3ZLkmbN/re+2rSKQgzHOF8GS9LnX32rtRu+VK/Yrso76x0Tj9vjvX2y4JQCAgIsnRdVz6BHHtSr895QVta5nw/AxfNpIU5OTlZKSkqJZR9++KF+97vf+XKzVdqZt+E++/wr7zK3263b27TS8EEDVFxcrMEjxinwitrqe2+cenbr7H3c28vf18lTp9Siebjlc6NqaHB9fWXtO+C9vW/fQdWpc6WCggI5baKSIocvrfNlcPaRHKVOm6XZk8dr0fL3f/X4Ifr7o4lKeytdOT8e1/PPJnJ0GL/JsOFjJEl3/e3Och6JivBpIR46dKi6dOlSYllwcLAvN+lId3ePKnH7gXvjtGDxcvW9N867bG7aIr3+9jLNmjxeNWvUsHpEVBF+fn4yxpyz3O122zANLgQ57Funi4v11DOpGvnoQIVeFVLivp9+KtKTYydq/OjHFfmX2/TNlu80dOQzat6syTlHmAHYy6eFOCQkRGFhYb7cBCS9s/IjNW3cSE0bN5QkGRnvp8iLioo0esIU7czcqwWzX9B119azc1Rc5vZm7dett7b23r7uumuUm/ujCgpO2TgVykIO+9bW7/8/ZR04pEnTX5YkHc39UR6PWz8VFalXj2gVFv6kyL/cJklq2byZbmgYpoxt31OIgUqGc4irgB27MvXh6nV6YcJonS4u1htLViimUwdJUmLy8zpV+JNenzVFtWvVtHlSXO5WrfpEz/9zrBo3bqgdO3br4YF99c6K/9g9FmCbVs2b6aP0NO/tf73yuo4dy9PoJwYr70S+8k+e1OaMbWp9843au++Adu3eq/A/3mDjxADOh0JcBQwacL8mTHlRcf0GqbjYrU4d2qlnty76est3+s/Ha/WHBtep7yNPeB//+GC+9gcX58iRHP3jocf11ptzFBBQXbt27tGDA4bZPRZQKV0ZFKhpKU8rdeosFRWdVrVqfho38lH9/vr6do8G4Fdc5nwnBF4CHTt21KBBg3TPPfdc9DpOH911CScCSlerfju7R4ADFBdZ+6lwchiXi9pkMCxwuowM9lkhvhQIYliFQgwrWF2ILwVyGFagEMMKZRViPwvnAAAAACodCjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAczb+0O44dO1bmE4ODgy/xKACAs5HDAGCNUgvxn//8Z7lcLhljzrnP5XLpu+++8+lgAOB05DAAWKPUQvz9999bOQcA4FfIYQCwRrnnEHs8Hr3yyitKTExUfn6+Zs+eLbfbbcVsAACRwwDga+UW4kmTJmn79u365ptvZIzRmjVrNHHiRCtmAwCIHAYAXyu3EK9fv16pqamqUaOGgoKC9Oqrr2rdunVWzAYAEDkMAL5WbiH29/eXn98vDwsICJC/f6mnHgMALjFyGAB8q9xEbdKkiRYsWCC3261du3Zp/vz5Cg8Pt2I2AIDIYQDwtXKPEI8ePVpbt25VTk6OevfurZMnT2rUqFFWzAYAEDkMAL7mMuf7gstK4vTRXXaPAIeoVb+d3SPAAYqL9ts9QoWRw7BCbTIYFjhdRgaXe4Q4JydHjz/+uG677TZFRERo1KhRysvLu6QDAgBKRw4DgG+VW4jHjBmjBg0aaPHixXr99ddVp04djR071orZAAAihwHA18r9UN3+/fv10ksveW+PHDlS3bp18+lQAIBfkMMA4FvlHiG++uqrlZWV5b196NAhhYaG+nQoAMAvyGEA8K1SjxA/8sgjkqTc3Fz16NFDd9xxh/z8/LRx40Y1bdrUsgEBwKnIYQCwRqmFuHPnzuddHhkZ6atZAABnIYcBwBqlFuK4uLjzLjfGaM+ePT4bCADwM3IYAKxR7ofq3nzzTU2aNEmnTp3yLgsJCdG6det8OhgA4GfkMAD4VrmFeM6cOZo3b55eeuklDR8+XB9//LEOHTpkxWwAAJHDAOBr5X7LRHBwsFq2bKlmzZopJydHgwYN0hdffGHFbAAAkcMA4GvlFmJ/f38dP35cYWFh+vbbbyVJbrfb54MBAH5GDgOAb5VbiHv16qWHH35YkZGReuuttxQfH69GjRpZMRsAQOQwAPiayxhjyntQQUGBateurcOHDysjI0Pt2rVTjRo1fD7c6aO7fL4NQJJq1W9n9whwgOKi/Rf9XHIYVVltMhgWOF1GBpdaiOfNm1fmSvv37//bproABDGsQiGGFSpaiMlhOAWFGFYoqxCX+i0TP/zwg0+GAQBcGHIYAKxxQadM2KV6wHV2jwCH8K9W7jcQAr/ZqVOX38U0/MlhWCC45hV2jwAHOJpX+kGGcj9UBwAAAFRlFGIAAAA4GoUYAAAAjlZuIfZ4PJo7d65Gjhyp/Px8zZ49my+EBwALkcMA4FvlFuJJkybphx9+8F4dac2aNZo4caLPBwMA/IwcBgDfKrcQr1+/XqmpqapRo4YCAwP16quvat26dVbMBgAQOQwAvlZuIfb395ef3y8PCwgIkL8/X1EFAFYhhwHAt8pN1CZNmmjBggVyu93atWuX5s+fr/DwcCtmAwCIHAYAXyv3CPHo0aO1detW5eTkqHfv3jp58qRGjRplxWwAAJHDAOBrXKkOEFeqgzW4Uh1wflypDlYo60p15baA8ePHn3f5mDFjLn4iAMAFI4cBwLfKPWUiODjY++eKK67Q559/bsVcAID/Qw4DgG9V+JSJ/Px8DRo0SGlpab6ayYtTJmAVTpmAFS7VKRNW5jCnTMAKnDIBK5R1ykSFL90cGBio7Ozs3zQQAODikcMAcGmVe1jsueeek8vlkiQZY7R161Y1atTI54MBAH5GDgOAb5VbiOvWrVvidvfu3dW9e3efDQQAKIkcBgDfKrcQ7927V5MmTbJiFgDAeZDDAOBb5Z5D/P3336sSf1UxAFR55DAA+Fa5R4hDQ0PVtWtXtWzZUldc8cunQPn+SwCwBjkMAL5VaiEuKipSQECAWrdurdatW1s5EwBA5DAAWKXU7yGOi4tTenq61fOUwPcQwyp8DzGsUNHvIa4MOcz3EMMKfA8xrHBR30PM+WoAYC9yGACsUephsZ9++knbtm0rNZBvuukmnw0FACCHAcAqpZ4y0bx5c9WrV++8QexyufTRRx/5fDhOmYBVOGUCVqjoKROVIYc5ZQJW4JQJWKGsUyZKbQGNGzfWsmXLfDEPAOACkMMAYI1yv4cYAAAAqMpKLcRt2rSxcg4AwK+QwwBgjVLPIa4MOIcYVuEcYlihoucQVwacQwwrcA4xrHBRX7sGAAAAOAGFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOJrPLs+VmJio9PT0Uu+fOHGi4uPjfbV5AHA0MhgALpzPLt184sQJFRYWSpI2bdqk4cOHa+3atd77g4KCVLNmzTLXwaWbYRUu3QwrWHnp5kuRwRKXboY1uHQzrFDWpZt91gKCgoIUFBQkSapTp44kKTQ01Febw/959ZWpytjynV54Ybbdo6CKeuSRB/TQQ31kjNGuXXs0ZEiijhzJsXss/AoZbL3oqL9q/PhE1ahRQxkZ3+mhgU/oxIl8u8dCFdKrdw8NGtLfe/vKKwNV/7pr1CK8PTn8G3EOcRURHt5Y//nfRYqP72r3KKjCWrduruHDH1KHDvFq06aTdu7M1NixT9g9FmC7q64K0dyXp6jXvQN1U/P22r17j1ImjLJ7LFQxixYuU4eIWHWIiNVdkT2VnX1UiU8mU4YvAQpxFTHokQf16rw3tGTJu3aPgips8+Ytat48Unl5J1SjRg3Vr19Pubk/2j0WYLu77rpTmzZ9ox07dkuSZs3+t+7rHWfzVKjKHn3sIR09kqPX5r1l9yhVAidOVhHDho+RJN31tzttngRVXXFxsbp166QXX/ynioqKlJw8xe6RANs1uL6+svYd8N7et++g6tS5UkFBgZw2gUsuJKSuBg8doL/eyQdjLxWOEAOosBUr/qMGDVpr/PgXtGJFmlwul90jAbby8/PT+T6j7na7bZgGVV2//vfqg/c/0p7MLLtHqTIoxAAuWKNGYbrjjjbe26+9tki///11qlu3jo1TAfbbm7Vf9evX896+7rprlJv7owoKTtk4FaqqHvHRWvj6ErvHqFIoxAAu2LXXXq1//3umfve7upKkhIQe2rp1u3Jzj9k7GGCzVas+0W23/kmNGzeUJD08sK/eWfEfm6dCVVQn+Eo1bPR7fb5xs92jVCmcQwzggq1b94X++c+Z+t//fUvFxcU6eDBbvXoNtHsswHZHjuToHw89rrfenKOAgOratXOPHhwwzO6xUAU1ahSmw4ePqLi42O5RqhSfXZjjbJ999pn69++v7du3V+h5XJgDVuHCHLCClRfmONvFZrDEhTlgDS7MASuUdWEOSwrxxaIQwyoUYljBrkL8W1CIYQUKMaxQViHmHGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKO5jDHG7iEAAAAAu3CEGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIb4McDFBWOXbb79Vfn6+3WMAlQ45DCuQwfahEF8Gtm/fbvcIcIBx48Zp7Nixcrvddo8CVDrkMHyNDLYXhbiSmzBhgoYPH85vjPCpCRMmaOXKlUpOTladOnXsHgeoVMhh+BoZbD9/uwdA6VJSUrRs2TKlpaUpMDDQ7nFQRc2aNUtpaWlavXq1rrnmGp0+fVrVq1e3eyygUiCH4WtkcOXAEeJKKiUlRenp6UpLS1N4eLiKi4vtHglV0MSJEzVz5kwFBARo1qxZkqTq1avzlh0gchi+RwZXHhwhroSmTJmiJUuW6O2331ajRo1K/LaYm5urkJAQmydEVZCamqpFixZp0aJFys/P16BBg/TTTz9p4sSJqlatmtxut6pVq2b3mIAtyGH4GhlcuXCEuJLJzs7WnDlzdPfdd+v666+XJG8IT58+XQ888IBOnjxp54ioAnJzc5WZmamFCxfqxhtvVOvWrTV58mStWrVKSUlJkuQNZMBpyGH4Ghlc+bgM3yVT6WzatElJSUm69957FR8fr5CQEM2ZM0fz589XSkqKIiMj7R4RVUBRUZECAgJkjJHL5ZLb7daaNWv0xBNPqFOnTpo4caIkcZQCjkQOw9fI4MqFQlxJbdq0SSNGjNCQIUO0f/9+vfHGG5o8ebIiIiLsHg1VmMfj0aeffkogAyKHYT0y2D4U4krsiy++0NChQ1VYWKjU1FRFRUXZPRIc4EwgP/nkk+rSpYvGjx9v90iAbchhWI0MtgfnEFdibdu21Zw5cxQUFKSjR48qNzfX7pHgAH5+fmrfvr0mT56sxYsXKzk52e6RANuQw7AaGWwPjhBfBs68bdevXz/Fxsby6WZYwu12a/369apfv74aNWpk9ziArchhWI0MthaF+DJx5gMe8fHxSkhIUN26de0eCQAchRwGqi5OmbhMtGnTRsnJyXr//fflcrnsHgcAHIccBqoujhBfZk6dOqVatWrZPQYAOBY5DFQ9FGIAAAA4GqdMAAAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQwxL79u1Ts2bNFBsb6/3TvXt3LV68+Dev++GHH9bSpUslSbGxscrLyyv1sSdOnFC/fv0qvI2VK1eqb9++5yzfuHGjYmJiyn1+06ZNK3yFq8TERL3yyisVeg4AnA8ZTAajbP52DwDnqFmzppYvX+69ffjwYcXExKh58+YKDw+/JNs4e/3nc/z4cWVkZFySbQHA5YQMBkpHIYZt6tWrp7CwMGVmZmrbtm1avHixTp06pcDAQKWlpentt9/WwoUL5fF4FBwcrKefflo33HCDDh8+rMTERGVnZ6t+/frKycnxrrNp06Zav369QkJCNHv2bKWnp8vf319hYWFKTU1VUlKSCgsLFRsbq6VLlyozM1MTJkzQsWPH5Ha71bdvX919992SpGnTpmnFihUKDg5WWFhYufuze/duJScn6+TJkzpy5IjCw8M1depU1ahRQ5I0depUZWRkyOPxaPjw4erQoYMklbqfAOBLZDAZjLMYwAJZWVmmVatWJZZ99dVXpm3btubAgQNmyZIlpm3btubEiRPGGGM2btxo7rvvPlNQUGCMMWbNmjWmS5cuxhhjBg8ebF544QVjjDGZmZmmVatWZsmSJcYYY5o0aWJycnLMhx9+aDp16mSOHTtmjDEmJSXFvPjiiyXmOH36tImOjjZbtmwxxhiTl5dnoqKizObNm82qVatMdHS0OXHihDl9+rQZOHCg6dOnzzn7tWHDBtO1a1djjDGpqalm2bJlxhhjioqKTExMjFm5cqV3rtmzZxtjjNm+fbu59dZbTU5OTpn7OXLkSDN37tzf9HMHAGPIYDIY5eEIMSxz5qiAJLndbtWtW1fPP/+8rr32Wkk/H1kIDAyUJK1evVp79uxRQkKC9/l5eXk6duyYPvvsM40cOVKSFBYWpttuu+2cba1fv15dunRRnTp1JElJSUmSfj6P7ozMzEzt3btXo0aNKjHjtm3btHPnTt11113eeXr27Km0tLQy92/EiBFat26dXn75ZWVmZio7O1sFBQXe+3v37i1JatKkiW644QZt3rxZX375Zan7CQCXEhlMBqN0FGJY5tfnr/1a7dq1vf/t8XgUGxurESNGeG9nZ2erTp06crlcMmddYNHf/9y/xtWqVZPL5fLezsvLO+eDHm63W0FBQSVmOnr0qIKCgjRp0qQS26hWrVq5+/f444/L7XYrKipKkZGROnjwYIl1+Pn98hlWj8cjf3//MvcTAC4lMpgMRun4lglUShEREXrvvfeUnZ0tSVq4cKEeeOABSVK7du301ltvSZIOHDigjRs3nvP8O+64Q6tWrVJ+fr4kacaMGZo/f778/f3ldrtljFHDhg1L/ANx8OBBxcTEaMuWLWrfvr1WrlypvLw8eTyecj8oIklr167VkCFDFB0dLUn65ptv5Ha7vfenp6dLkrZu3aq9e/eqZcuWZe4nANiFDIbTcIQYlVJERIQeeughDRgwQC6XS4GBgZo5c6ZcLpfGjRunpKQkRUVF6Zprrjnvp6PvvPNO7dixw/sWWePGjfXcc8+pVq1aatGihbp27aoFCxboxRdf1IQJEzR37lwVFxdr2LBhuuWWWyRJ27dvV8+ePXXllVcqPDxcP/74Y5kzP/bYYxoyZIhq166twMBAtW3bVnv37vXen5WVpR49esjlcmnKlCkKDg4ucz8BwC5kMBnsNC5z9vsJAAAAgMNwygQAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQV3Jut1vz5s1TfHy8YmNjFR0dreeff15FRUW/aZ2DBg1S586d9frrr1f4+RkZGXr00Ucvevu/1rFjR7Vq1UonT54ssXzp0qVq2rSpVq5cWebzT5w4oX79+pV6f2xsrPLy8i54nqVLlyoyMlJ///vfL/g5v/btt99q7NixkqSNGzcqJibmotdVlhkzZig5Odkn6y7P6dOn9ac//Unff/+9d9mbb76ppk2bau3atd5l77//vu655x47RgQuKfKYPC6LnXksSQsWLNDf/va3Ej/fr776Su3bt9eBAwdsm+tyQSGu5J555hlt3rxZr732mpYvX67Fixdr9+7dGj169EWv8/Dhw1q7dq3ef/999enTp8LPv/nmmzV9+vSL3v751K1bV6tWrSqxbNmyZbrqqqvKfe7x48eVkZFR6v3Lly/XlVdeecGzLFu2TI899pheeeWVC37Or+3YsUOHDx++6OdfDqpXr67bb79dGzZs8C5bvXq1OnTooI8++si7bMOGDbrzzjvtGBG4pMhj8rgyu//++9WiRQslJSVJ+vnv1mOPPabnn39e9evXt3m6yo9CXInt27dPK1asUEpKioKCgiRJtWvX1rPPPqu//e1vkn7+bfzJJ59UTEyMunXrpkmTJqm4uFjSz0E5Y8YMJSQkqGPHjnrjjTeUn5+vf/zjHyouLlZ8fLz27t2rpk2bKjc317vdM7dPnjypRx99VLGxsYqLi9OYMWPk8XhK/IZd0e2Xpnv37nrnnXe8t/fv36+CggI1atTIu2zx4sW655571KNHD3Xo0MG7vqSkJBUWFio2NlZut1vNmzfXsGHD1LlzZ2VkZHj3Z+bMmUpISJDb7daRI0cUERFRosxJUkpKijIyMjRt2jTNnz+/zP379XbOOHjwoKZPn65NmzZ5g6mgoECPPfaYYmNj1aVLF23atEmSVFRUpJSUFMXFxal79+5KTExUfn7+OT+f4uJiTZw4UZ07d1Z0dLRGjx59zlGpjz/+WAkJCYqPj1dkZKSmTp0qSaW+jqUtr4j27dvr888/lyQVFhbqm2++0ZNPPqmPP/7Y+5gNGzYoMjKyQusFKhvymDw+o7LmsSQ999xz2rVrl1555RU9+uij+vvf/67bbrutwutxJINKa+XKlaZnz55lPuapp54yzz33nPF4POann34yAwYMMLNnzzbGGNOkSROTlpZmjDEmIyPDNG/e3BQWFpqsrCzTqlUr7zqaNGlicnJyzrmdnp5uBgwYYIwxpri42IwePdpkZmaaDRs2mK5du1709n+tQ4cO5ssvvzS33367OXz4sDHGmH/9618mLS3N9OnTx3zwwQcmPz/f9OrVy+Tm5hpjjNm8ebN3H863P+np6efsT3Fxsbn//vvN7NmzzYMPPmheeuml8/5Mz2zzQvbv7O2cbcmSJWbgwIHGGGM2bNhgmjVrZr7++mtjjDHz5s0z/fr1M8YYM2PGDJOammo8Ho8xxpjJkyebcePGnbO+1157zdx///3m1KlTxu12m2HDhpn09HQzffp08+yzzxqPx2P69Oljdu/ebYwx5tChQ6ZZs2Zlvo6lLa+IAwcOmFtvvdW43W7z0UcfmSFDhhhjjOncubPZunWrOXDggPnLX/7i3T/gckUek8dnVNY8PuOHH34wN910kxk6dOhFPd+pOEJcifn5+ZX7G+Knn36qPn36yOVyKSAgQAkJCfr000+99//1r3+VJN10000qKipSQUHBBW//lltu0Y4dO9S3b1/NmTNHDzzwgMLCwnyy/erVq6tz58569913JUkffPBBifO8rrjiCs2aNUuffPKJpk6dqlmzZpW5L23atDlnWbVq1fQ///M/evnll2WM0cMPP1zuz6C8/Tvfds6nQYMGatmypSQpPDzcewRo9erV+u9//6sePXooNjZWH374oXbu3HnO8z/77DPFxsaqZs2a8vPz09SpU9WjRw/v/S6XS7NmzdLWrVs1c+ZMpaamyhijU6dOlfo6XsjrW55rr71WoaGh2r59uz7++GPvkeAOHTpo7dq1Wr9+vdq3by+Xy1Wh9QKVDXlMHp9RWfP4jM8//1zBwcH6+uuvlZOTc1HrcCIKcSXWokUL7dq165y3bA4fPqyBAweqsLBQHo+nRNnweDzet5AkqUaNGpLkfYwxpsxtnv22T4MGDbRq1SoNHDhQ+fn56t+/v/773/+WePyl3H6PHj30zjvv6KuvvlLDhg0VHBzsve/QoUPq0aOH9u/fr1tuuUXDhw8vcz9q16593uX79+9XjRo1tHfvXh0/frzMdZzZn7L2r7Tt/Fr16tW9/+1yubw/B4/Ho1GjRmn58uVavny53n77bU2bNu2c5/v7+5e4ffToUWVnZ3tvFxQUKC4uTlu3btWNN96op556Sv7+/jLGlPo6Xsjrm5GRodjYWO+f82nXrp0+//xzffLJJ95CfOedd+qrr77idAlUGeRxsPc+8rjy5vGXX36p6dOnKy0tTXfccYcef/xxud3uC/q5OB2FuBKrV6+eunXrplGjRnlDOD8/X88884yCg4NVs2ZNRURE6PXXX5cxRkVFRVq0aJHuuOOOCm0nJCTEe87VmSMCkvTGG28oKSlJERERGjFihCIiIrRt27YSz70U2z+jZcuWKiws1AsvvKC4uLgS923ZskUhISEaPHiwIiIivOeout1u+fv7y+12l/uPS15enkaMGKHU1FTFxMRc0AdhLnb/qlWrViKoy1r/ggULVFRUJI/Ho6efflpTpkw553G333673n33Xe/jnnnmGb333nve+/fs2aP8/HwNHz5cHTt21MaNG72PLe11vJDX9+abb/b+47B8+fLz7kP79u21ZMkSXX311d4P3bRp00Y//PCDNm/efNF/H4DKhDz+BXlcOfP48OHDGjZsmJ599lk1bNhQzzzzjHJyci75hy6rKgpxJTdu3Dg1btxYCQkJio2N1T333KPGjRtr/PjxkqQxY8YoNzdX3bp1U7du3dSwYUM98sgjFdrGmDFjlJycrLi4OO3cuVOhoaGSfj5C4Ha7FR0drfj4eJ04cUJ9+/Y957m/dftni42N1e7du9WuXbsSy//yl7+oXr166tKli6KionTw4EGFhIRoz549Cg0NVYsWLdS1a1f9+OOPZe5nZGSkIiIiNHToUGVlZWnBggVlznOx+9eqVStlZWVp6NChZT5u8ODBuu666xQXF6fo6GgZY5SYmHjO4xISEnTTTTcpPj5e3bp1U2hoaInXomnTpoqMjFRUVJSioqL08ccfq3HjxtqzZ0+pr+OFvL4Xok2bNtq3b1+JI8H+/v66+eabVb9+fQUGBlZ4nUBlRB7/jDyufHlcVFSkRx99VF27dlWXLl0kSbVq1dK0adOUlpam1atXX/C6nMplyvs1DgAAAKjCOEIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR/Mv/yH2OX10l90jwCFq1W9X/oOA36i4aL/dI1QYOQwrkMGwQlkZzBFiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOJq/r1bcsWNH7d+//5zlf/zjH/Xuu+/6arMAgP9DDgPAhfFZIZakxMRExcTElNygv083CQA4CzkMAOXzaSoGBgYqNDTUl5twJGOMRo+frD/e8Af1v+9uSVJE9L2qF3qV9zH97+upmM4dvbf3HTikXgP+n+a8MEHNmzWxfGZUHdFRf9X48YmqUaOGMjK+00MDn9CJE/l2j4VSkMOX3vky+IxhSc/p6qt+p9FPDJYkff7lN3p+5ssqdrsVfOWVGjnsYYX/sZEdY6OKIIN9g3OILzM7M/fq748madXqtd5lu/fsU50rg7TktX95/5xdhn/6qUiJyc/rdHGxHSOjCrnqqhDNfXmKet07UDc1b6/du/coZcIou8cCLHO+DD7j1QVv66tvt3hvn8g/qeGjx+uJIX9X+r9f0tMjhurJp1NUVFRk5cioQshg36EQX2beXPKuenbrrE4d2nmXfb1lm/z8/NRv0JOK6zdIL726QG6323v/+Cn/Uo/ov6lunSvtGBlVyF133alNm77Rjh27JUmzZv9b9/WOs3kqwDrny2BJ+vyrb7V2w5fqFdvVu2xP1n4FXlFbf27TWpLUKKyBrriitr7e8r2lM6PqIIN9x6eFODk5Wa1bty7xJycnx5ebrPJGPzFYXTt1KLHM7Xbr9jatNGvKeL32r+e17vOv9MbidyRJi99ZqeJit+7uHmXHuKhiGlxfX1n7Dnhv79t3UHXqXKmgoEAbp0JZyOFL63wZnH0kR6nTZumf456SX7Vf/ln9w++v06nCQq3b+KUkKeO77dq5e6+O5uRaOjOqDjLYd3x6DvHQoUPVpUuXEsuCg4N9uUlH+nXZfeDeOC1YvFy3tLpZi5a9r9denGTTZKhq/Pz8ZIw5Z/nZ70igciGHfet0cbGeeiZVIx8dqNCrQkrcF3jFFZo2caymz3lNk198RW1aNtett7RUdT7UiItEBvuOT/+vDAkJUVhYmC83AUnvrPxITRs3UtPGDSVJRkb+/v5654MPdbKgQH0efkKSlH00V4nPTtITQ/6hDu3+bOfIuEztzdqvW29t7b193XXXKDf3RxUUnLJxKpSFHPatrd//f8o6cEiTpr8sSTqa+6M8Hrd+KirSMyMfVe1atTR/5i8HJbom/EMNrq9v17i4zJHBvsOvqVXAjl2Z+nD1Or0wYbROFxfrjSUrFNOpg+7uHqXEsx7XqecDSh33FN8ygYu2atUnev6fY9W4cUPt2LFbDw/sq3dW/MfusQDbtGreTB+lp3lv/+uV13XsWJ5GPzFYxhgNfnKspqeOVfNmTfTBh58oIKC69+AFUFFksO9QiKuAQQPu14QpLyqu3yAVF7vVqUM79ezWpfwnAhV05EiO/vHQ43rrzTkKCKiuXTv36MEBw+weC6iUXC6X/vnMU3rmn9N0+nSxQq8K0fSJY+VyueweDZcpMth3XOZ8J6NcAh07dtSgQYN0zz33XPQ6Th/ddQknAkpXq3678h8E/EbFRedeNc6XyGFcLshgWKGsDPZZIb4UCGJYhTCGFawuxJcCOQwrkMGwQlkZzPcQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0/9LuOHbsWJlPDA4OvsSjAADORg4DgDVKLcR//vOf5XK5ZIw55z6Xy6XvvvvOp4MBgNORwwBgjVIL8ffff2/lHACAXyGHAcAa5Z5D7PF49MorrygxMVH5+fmaPXu23G63FbMBAEQOA4CvlVuIJ02apO3bt+ubb76RMUZr1qzRxIkTrZgNACByGAB8rdxCvH79eqWmpqpGjRoKCgrSq6++qnXr1lkxGwBA5DAA+Fq5hdjf319+fr88LCAgQP7+pZ56DAC4xMhhAPCtchO1SZMmWrBggdxut3bt2qX58+crPDzcitkAACKHAcDXyj1CPHr0aG3dulU5OTnq3bu3Tp48qVGjRlkxGwBA5DAA+JrLnO8LLiuJ00d32T0CHKJW/XZ2jwAHKC7ab/cIFUYOwwpkMKxQVgaXe4Q4JydHjz/+uG677TZFRERo1KhRysvLu6QDAgBKRw4DgG+VW4jHjBmjBg0aaPHixXr99ddVp04djR071orZAAAihwHA18r9UN3+/fv10ksveW+PHDlS3bp18+lQAIBfkMMA4FvlHiG++uqrlZWV5b196NAhhYaG+nQoAMAvyGEA8K1SjxA/8sgjkqTc3Fz16NFDd9xxh/z8/LRx40Y1bdrUsgEBwKnIYQCwRqmFuHPnzuddHhkZ6atZAABnIYcBwBqlFuK4uLjzLjfGaM+ePT4bCADwM3IYAKxR7ofq3nzzTU2aNEmnTp3yLgsJCdG6det8OhgA4GfkMAD4VrmFeM6cOZo3b55eeuklDR8+XB9//LEOHTpkxWwAAJHDAOBr5X7LRHBwsFq2bKlmzZopJydHgwYN0hdffGHFbAAAkcMA4GvlFmJ/f38dP35cYWFh+vbbbyVJbrfb54MBAH5GDgOAb5VbiHv16qWHH35YkZGReuuttxQfH69GjRpZMRsAQOQwAPiayxhjyntQQUGBateurcOHDysjI0Pt2rVTjRo1fD7c6aO7fL4NQJJq1W9n9whwgOKi/Rf9XHIYVRkZDCuUlcGlFuJ58+aVudL+/fv/tqkuAEEMqxDGsEJFCzE5DKcgg2GFsjK41G+Z+OGHH3wyDADgwpDDAGCNCzplwi7+AdfZPQIcoppfuafTA7/ZT4VZdo9QYeQwrBBc8wq7R4ADHM0r/SADLQAAAACORiEGAACAo1GIAQAA4GjlFmKPx6O5c+dq5MiRys/P1+zZs/lCeACwEDkMAL5VbiGeNGmSfvjhB+/VkdasWaOJEyf6fDAAwM/IYQDwrXIL8fr165WamqoaNWooMDBQr776qtatW2fFbAAAkcMA4GvlFmJ/f3/5nfWVVAEBAfL3L/XriwEAlxg5DAC+VW6iNmnSRAsWLJDb7dauXbs0f/58hYeHWzEbAEDkMAD4WrlHiEePHq2tW7cqJydHvXv31smTJzVq1CgrZgMAiBwGAF/jSnWAuFIdrMGV6oDz40p1sEJZV6or95SJ8ePHn3f5mDFjLn4iAMAFI4cBwLfKPSwWHBzs/XPFFVfo888/t2IuAMD/IYcBwLcqfMpEfn6+Bg0apLS0NF/N5MVbdbAKp0zACpfqlAlyGFUNp0zACmWdMlHhFhAYGKjs7OzfNBAA4OKRwwBwaZV7DvFzzz0nl8slSTLGaOvWrWrUqJHPBwMA/IwcBgDfKrcQ161bt8Tt7t27q3v37j4bCABQEjkMAL5VbiHeu3evJk2aZMUsAIDzIIcBwLfKPYf4+++/VyX+qmIAqPLIYQDwrXKPEIeGhqpr165q2bKlrrjil0+B8v2XAGANchgAfKvUQlxUVKSAgAC1bt1arVu3tnImAIDIYQCwSqnfQxwXF6f09HSr5ymB77+EVfgeYlihot9DTA7DKfgeYljhor6HmPPVAMBe5DAAWKPUUyZ++uknbdu2rdRAvummm3w2FACAHAYAq5R6ykTz5s1Vr1698waxy+XSRx995PPheKsOVuGUCVihoqdMkMNwCk6ZgBXKOmWi1CPEjRs31rJly3wxDwDgApDDAGANDosBAADA0UotxG3atLFyDgDAr5DDAGCNUs8hrgw4dw1W4RxiWKGi5xBXBuQwrMA5xLDCRX3tGgAAAOAEFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBo/r5acWJiotLT00u9f+LEiYqPj/fV5gHA0chgALhwPrt084kTJ1RYWChJ2rRpk4YPH661a9d67w8KClLNmjXLXAeXDIVVuHQzrGDlpZsvRQZL5DCswaWbYYWyLt3ssyPEQUFBCgoKkiTVqVNHkhQaGuqrzUFSdNRfNX58omrUqKGMjO/00MAndOJEvt1joYrp3TtOjz/2iIwxKig4pcefGKevvvrW7rHwK2Sw9chg+Fqv3j00aEh/7+0rrwxU/euuUYvw9jpyJMfGyS5/HBarIq66KkRzX56iXvcO1E3N22v37j1KmTDK7rFQxTT5YyNNTBmtbt376tbbuig1dbreemuO3WMBtiODYYVFC5epQ0SsOkTE6q7InsrOPqrEJ5Mpw5cAhbiKuOuuO7Vp0zfasWO3JGnW7H/rvt5xNk+FquanoiINGvSUDh3KliR9+dW3uqZeqKpXr27zZIC9yGBY7dHHHtLRIzl6bd5bdo9SJfjslAlYq8H19ZW174D39r59B1WnzpUKCgrkLTtcMnv27NOePfu8tydNGqt3312l06dP2zgVYD8yGFYKCamrwUMH6K938sHYS4VCXEX4+fnpfJ+PdLvdNkyDqq527Vqa+/IUXX99fXXr3tfucQDbkcGwUr/+9+qD9z/SnkzrPqhb1XHKRBWxN2u/6tev57193XXXKDf3RxUUnLJxKlRFDRrU1yerl8nt9qhT53t1/Hie3SMBtiODYaUe8dFa+PoSu8eoUijEVcSqVZ/otlv/pMaNG0qSHh7YV++s+I/NU6GqCQy8Qqv+s0jLln+gvv2GeL/WC3A6MhhWqRN8pRo2+r0+37jZ7lGqFE6ZqCKOHMnRPx56XG+9OUcBAdW1a+cePThgmN1joYoZNOhB/f731yu2exfFdu/iXd4lKkG5ucfsGwywGRkMqzRqFKbDh4+ouLjY7lGqFJ9dmONsn332mfr376/t27dX6Hl8ITyswoU5YAUrL8xxtovNYIkchjW4MAesUNaFOSwpxBeLIIZVKMSwgl2F+Lcgh2EFCjGsUFYhpgUAAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAABzNZYwxdg8BAAAA2IUjxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CvFlgIsJwirffvut8vPz7R4DqHTIYViBDLYPhfgysH37drtHgAOMGzdOY8eOldvttnsUoNIhh+FrZLC9KMSV3IQJEzR8+HB+Y4RPTZgwQStXrlRycrLq1Klj9zhApUIOw9fIYPv52z0ASpeSkqJly5YpLS1NgYGBdo+DKmrWrFlKS0vT6tWrdc011+j06dOqXr263WMBlQI5DF8jgysHjhBXUikpKUpPT1daWprCw8NVXFxs90iogiZOnKiZM2cqICBAs2bNkiRVr16dt+wAkcPwPTK48uAIcSU0ZcoULVmyRG+//bYaNWpU4rfF3NxchYSE2DwhqoLU1FQtWrRIixYtUn5+vgYNGqSffvpJEydOVLVq1eR2u1WtWjW7xwRsQQ7D18jgyoUjxJVMdna25syZo7vvvlvXX3+9JHlDePr06XrggQd08uRJO0dEFZCbm6vMzEwtXLhQN954o1q3bq3Jkydr1apVSkpKkiRvIANOQw7D18jgysdl+C6ZSmfTpk1KSkrSvffeq/j4eIWEhGjOnDmaP3++UlJSFBkZafeIqAKKiooUEBAgY4xcLpfcbrfWrFmjJ554Qp06ddLEiRMliaMUcCRyGL5GBlcuFOJKatOmTRoxYoSGDBmi/fv364033tDkyZMVERFh92iowjwejz799FMCGRA5DOuRwfahEFdiX3zxhYYOHarCwkKlpqYqKirK7pHgAGcC+cknn1SXLl00fvx4u0cCbEMOw2pksD04h7gSa9u2rebMmaOgoCAdPXpUubm5do8EB/Dz81P79u01efJkLV68WMnJyXaPBNiGHIbVyGB7cIT4MnDmbbt+/fopNjaWTzfDEm63W+vXr1f9+vXVqFEju8cBbEUOw2pksLUoxJeJMx/wiI+PV0JCgurWrWv3SADgKOQwUHVxysRlok2bNkpOTtb7778vl8tl9zgA4DjkMFB1cYT4MnPq1CnVqlXL7jEAwLHIYaDqoRADAADA0ThlAgAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGJbYt2+fmjVrptjYWO+f7t27a/Hixb953Q8//LCWLl0qSYqNjVVeXl6pjz1x4oT69etX4W2sXLlSffv2PWf5xo0bFRMTU+7zmzZtWuErXCUmJuqVV16p0HMA4HzIYDIYZfO3ewA4R82aNbV8+XLv7cOHDysmJkbNmzdXeHj4JdnG2es/n+PHjysjI+OSbAsALidkMFA6CjFsU69ePYWFhSkzM1Pbtm3T4sWLderUKQUGBiotLU1vv/22Fi5cKI/Ho+DgYD399NO64YYbdPjwYSUmJio7O1v169dXTk6Od51NmzbV+vXrFRISotmzZys9PV3+/v4KCwtTamqqkpKSVFhYqNjYWC1dulSZmZmaMGGCjh07Jrfbrb59++ruu++WJE2bNk0rVqxQcHCwwsLCyt2f3bt3Kzk5WSdPntSRI0cUHh6uqVOnqkaNGpKkqVOnKiMjQx6PR8OHD1eHDh0kqdT9BABfIoPJYJzFABbIysoyrVq1KrHsq6++Mm3btjUHDhwwS5YsMW3btjUnTpwwxhizceNGc99995mCggJjjDFr1qwxXbp0McYYM3jwYPPCCy8YY4zJzMw0rVq1MkuWLDHGGNOkSROTk5NjPvzwQ9OpUydz7NgxY4wxKSkp5sUXXywxx+nTp010dLTZsmWLMcaYvLw8ExUVZTZv3mxWrVploqOjzYkTJ8zp06fNwIEDTZ8+fc7Zrw0bNpiuXbsaY4xJTU01y5YtM8YYU1RUZGJiYszKlSu9c82ePdsYY8z27dvNrbfeanJycsrcz5EjR5q5c+f+pp87ABhDBpPBKA9HiGGZM0cFJMntdqtu3bp6/vnnde2110r6+chCYGCgJGn16tXas2ePEhISvM/Py8vTsWPH9Nlnn2nkyJGSpLCwMN12223nbGv9+vXq0qWL6tSpI0lKSkqS9PN5dGdkZmZq7969GjVqVIkZt23bpp07d+quu+7yztOzZ0+lpaWVuX8jRozQunXr9PLLLyszM1PZ2dkqKCjw3t+7d29JUpMmTXTDDTdo8+bN+vLLL0vdTwC4lMhgMhiloxDDMr8+f+3Xateu7f1vj8ej2NhYjRgxwns7OztbderUkcvlkjnrAov+/uf+Na5WrZpcLpf3dl5e3jkf9HC73QoKCiox09GjRxUUFKRJkyaV2Ea1atXK3b/HH39cbrdbUVFRioyM1MGDB0usw8/vl8+wejwe+fv7l7mfAHApkcFkMErHt0ygUoqIiNB7772n7OxsSdLChQv1wAMPSJLatWunt956S5J04MABbdy48Zzn33HHHVq1apXy8/MlSTNmzND8+fPl7+8vt9stY4waNmxY4h+IgwcPKiYmRlu2bFH79u21cuVK5eXlyePxlPtBEUlau3athgwZoujoaEnSN998I7fb7b0/PT1dkrR161bt3btXLVu2LHM/AcAuZDCchiPEqJQiIiL00EMPacCAAXK5XAoMDNTMmTPlcrk0btw4JSUlKSoqStdcc815Px195513aseOHd63yBo3bqznnntOtWrVUosWLdS1a1ctWLBAL774oiZMmKC5c+equLhYw4YN0y233CJJ2r59u3r27Kkrr7xS4eHh+vHHH8uc+bHHHtOQIUNUu3ZtBQYGqm3bttq7d6/3/qysLPXo0UMul0tTpkxRcHBwmfsJAHYhg8lgp3GZs99PAAAAAByGUyYAAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqF+DLhdrs1b948xcfHKzY2VtHR0Xr++edVVFT0m9Y5aNAgde7cWa+//nqFn5+RkaFHH330orf/ax07dlSrVq108uTJEsuXLl2qpk2bauXKlWU+/8SJE+rXr1+p98fGxiovL++C51m6dKkiIyP197///YKf82vffvutxo4dK0nauHGjYmJiLnpdZZkxY4aSk5N9su7yZGVl6ZZbbtHHH39cYvknn3yiO+64Q4cPH7ZlLuBSI4fJ4bLYmcOStHDhQsXGxpb406JFC40ePdq2mS4n/nYPgAvzzDPP6Pjx43rttdcUFBSkgoICPfnkkxo9erSef/75i1rn4cOHtXbtWn399deqVq1ahZ9/8803a/r06Re17dLUrVtXq1atUo8ePbzLli1bpquuuqrc5x4/flwZGRml3r98+fIKzbJs2TI99thjio2NrdDzzrZjx44qXwgbNGigp59+WmPGjNGKFSsUEhKiH3/8UWPGjNE///lP1atXz+4RgUuCHCaHK7PevXurd+/e3tvvvvuuJkyYoEceecTGqS4fHCG+DOzbt08rVqxQSkqKgoKCJEm1a9fWs88+q7/97W+Sfv6t/Mknn1RMTIy6deumSZMmqbi4WNLPgTljxgwlJCSoY8eOeuONN5Sfn69//OMfKi4uVnx8vPbu3aumTZsqNzfXu90zt0+ePKlHH31UsbGxiouL05gxY+TxeEr8pl3R7Zeme/fueuedd7y39+/fr4KCAjVq1Mi7bPHixbrnnnvUo0cPdejQwbu+pKQkFRYWKjY2Vm63W82bN9ewYcPUuXNnZWRkePdn5syZSkhIkNvt1pEjRxQREaENGzaUmCMlJUUZGRmaNm2a5s+fX+b+/Xo7Zxw8eFDTp0/Xpk2blJSUJEkqKCjwhnuXLl20adMmSVJRUZFSUlIUFxen7t27KzExUfn5+ef8fIqLizVx4kR17txZ0dHRGj169DlHpz7++GMlJCQoPj5ekZGRmjp1qiSV+jqWtrwievToodtvv13PPPOMJGncuHGKi4tTu3btKrQeoLIih8nhMyprDp/tm2++0dixYzVt2jQ1aNDgotfjKAaV3sqVK03Pnj3LfMxTTz1lnnvuOePxeMxPP/1kBgwYYGbPnm2MMaZJkyYmLS3NGGNMRkaGad68uSksLDRZWVmmVatW3nU0adLE5OTknHM7PT3dDBgwwBhjTHFxsRk9erTJzMw0GzZsMF27dr3o7f9ahw4dzJdffmluv/12c/jwYWOMMf/6179MWlqa6dOnj/nggw9Mfn6+6dWrl8nNzTXGGLN582bvPpxvf9LT08/Zn+LiYnP//feb2bNnmwcffNC89NJL5/2Zntnmhezf2ds525IlS8zAgQONMcZs2LDBNGvWzHz99dfGGGPmzZtn+vXrZ4wxZsaMGSY1NdV4PB5jjDGTJ08248aNO2d9r732mrn//vvNqVOnjNvtNsOGDTPp6elm+vTp5tlnnzUej8f06dPH7N692xhjzKFDh0yzZs3KfB1LW15RJ06cMB07djSJiYmmd+/e5vTp0xVeB1BZkcPk8BmVOYfPbO8vf/mLeeutty7q+U7FEeLLgJ+fX7m/KX766afq06ePXC6XAgIClJCQoE8//dR7/1//+ldJ0k033aSioiIVFBRc8PZvueUW7dixQ3379tWcOXP0wAMPKCwszCfbr169ujp37qx3331XkvTBBx+UON/riiuu0KxZs/TJJ59o6tSpmjVrVpn70qZNm3OWVatWTf/zP/+jl19+WcYYPfzww+X+DMrbv/Nt53waNGigli1bSpLCw8O9R4JWr16t//73v+rRo4diY2P14YcfaufOnec8/7PPPlNsbKxq1qwpPz8/TZ06tcTbmi6XS7NmzdLWrVs1c+ZMpaamyhijU6dOlfo6XsjreyECAwM1fvx4rVixQlOmTJG/P2dkoeogh8nhMypzDhcWFmrw4MGKiopSr169Kvx8J6MQXwZatGihXbt2nfPWzeHDhzVw4EAVFhbK4/HI5XJ57/N4PN63kiSpRo0akuR9jDGmzG2e/fZPgwYNtGrVKg0cOFD5+fnq37+//vvf/5Z4/KXcfo8ePfTOO+/oq6++UsOGDRUcHOy979ChQ+rRo4f279+vW265RcOHDy9zP2rXrn3e5fv371eNGjW0d+9eHT9+vMx1nNmfsvavtO38WvXq1b3/7XK5vD8Hj8ejUaNGafny5Vq+fLnefvttTZs27Zzn/7pkHj16VNnZ2d7bBQUFiouL09atW3XjjTfqqaeekr+/v4wxpb6OF/L6ZmRklPigRmkaNGig6tWr65prrrmgnwdwuSCHg733kcOVN4dHjx6t4OBgJSYmXtDPAr+gEF8G6tWrp27dumnUqFHeMM7Pz9czzzyj4OBg1axZUxEREXr99ddljFFRUZEWLVqkO+64o0LbCQkJ8Z57debIgCS98cYbSkpKUkREhEaMGKGIiAht27atxHMvxfbPaNmypQoLC/XCCy8oLi6uxH1btmxRSEiIBg8erIiICO83G7jdbvn7+8vtdpf7j0xeXp5GjBih1NRUxcTEXNAncC92/6pVq1YisMta/4IFC1RUVCSPx6Onn35aU6ZMOedxt99+u959913v45555hm999573vv37Nmj/Px8DR8+XB07dtTGjRu9jy3tdbyQ1/fmm2/2/iNR0Q/FAFUBOfwLcrhy5vCsWbP03XffaerUqRf1AU2noxBfJsaNG6fGjRsrISFBsbGxuueee9S4cWONHz9ekjRmzBjl5uaqW7du6tatmxo2bFjhT5aOGTNGycnJiouL086dOxUaGirp5yMFbrdb0dHRio+P14kTJ9S3b99znvtbt3+22NhY7d69+5wPZf3lL39RvXr11KVLF0VFRengwYMKCQnRnj17FBoaqhYtWqhr16768ccfy9zPyMhIRUREaOjQocrKytKCBQvKnOdi969Vq1bKysrS0KFDy3zc4MGDdd111ykuLk7R0dEyxpz3N/yEhATddNNNio+PV7du3RQaGlritWjatKkiIyMVFRWlqKgoffzxx2rcuLH27NlT6ut4Ia8vAHL4DHK4cubwtGnTVFBQoD59+pQ4knzmw4Qom8uU92scAAAAUIVxhBgAAACORiEGAACAo1GIAQAA4GgUYgAAADgahRgAAACOVqkvJXX66C67R4BD1KrfrvwHAb9RcdF+u0eoMHIYViCDYYWyMpgjxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0f1+tuGPHjtq/f/85y//4xz/q3Xff9dVmAQD/hxwGgAvjs0IsSYmJiYqJiSm5QX+fbhIAcBZyGADK59NUDAwMVGhoqC834UjGGI0eP1l/vOEP6n/f3ZKkiOh7VS/0Ku9j+t/XUzGdO2pP1n6NnThVPx4/rtq1ainl6SfVKKyBXaOjCoiO+qvGj09UjRo1lJHxnR4a+IROnMi3eyyUghy+9CqSwWcsffd/9dGnn+lfk561fF5ULWSwb3CY4DKzM3OvJkx+URnbvtcfb/iDJGn3nn2qc2WQlrz2r3MeP/LZSerbq4e6duqgNeu/0OOjJyg97SW5XC6LJ0dVcNVVIZr78hS1j+yhHTt2a2LKKKVMGKX/9+gou0cDLFHRDD6ed0JTZ83Xe//5WG1a32zxtKhqyGDf4UN1l5k3l7yrnt06q1OHdt5lX2/ZJj8/P/Ub9KTi+g3SS68ukNvt1uEjR7V7T5ai/nanJKnd7W1VcOqUvvthp13j4zJ31113atOmb7Rjx25J0qzZ/9Z9veNsngqwTkUyWJJWfvSprr4qRE8O/YddI6MKIYN9x6dHiJOTk5WSklJi2Ycffqjf/e53vtxslTb6icGSpM8+/8q7zO126/Y2rTR80AAVFxdr8IhxCryitlrcFK6rr/qd/Px++b2n3tVX6XD2Ud3YtLHls+Py1+D6+srad8B7e9++g6pT50oFBQXyll0lRQ5fWhXJ4L73xuneuK6SpGXvrbJlXlQtZLDv+LQQDx06VF26dCmxLDg42JebdKS7u0eVuP3AvXFasHi5mt/YVPrVqRHGSH7VeGMAF8fPz0/GmHOWnzkahsqHHPa90jK4770cucOlRQb7jk8LcUhIiMLCwny5CUh6Z+VHatq4kZo2bihJMjLy9/fXtfVCdTQnV8YY7znDR47mlPjgB1ARe7P269ZbW3tvX3fdNcrN/VEFBadsnAplIYd9r7QMBi41Mth3OFRYBezYlal/zU2T2+1W4U8/6Y0lK9Tlr+11zdWhanBdfX3w0SeSpHUbv5TL5VKT//sgCFBRq1Z9ottu/ZMa/98//A8P7Kt3VvzH5qkAe5WWwcClRgb7Dr/CVgGDBtyvCVNeVFy/QSoudqtTh3bq2e3nt0iff3akxv1zmubMf1MBAQGaMn50iXOKgYo4ciRH/3jocb315hwFBFTXrp179OCAYXaPBdiqrAwGLiUy2Hdc5nwno1wCHTt21KBBg3TPPfdc9DpOH911CScCSlerfrvyHwT8RsVF5141zpfIYVwuyGBYoawM9lkhvhQIYliFMIYVrC7ElwI5DCuQwbBCWRnMe+cAAABwNAoxAAAAHI1CDAAAAEejEAMAAMDRKMQAAABwNAoxAAAAHI1CDAAAAEejEAMAAMDRKMQAAABwNAoxAAAAHI1CDAAAAEejEAMAAMDRKMQAAABwNAoxAAAAHM2/tDuOHTtW5hODg4Mv8SgAgLORwwBgjVIL8Z///Ge5XC4ZY865z+Vy6bvvvvPpYADgdOQwAFij1EL8/fffWzkHAOBXyGEAsEa55xB7PB698sorSkxMVH5+vmbPni23223FbAAAkcMA4GvlFuJJkyZp+/bt+uabb2SM0Zo1azRx4kQrZgMAiBwGAF8rtxCvX79eqampqlGjhoKCgvTqq69q3bp1VswGABA5DAC+Vm4h9vf3l5/fLw8LCAiQv3+ppx4DAC4xchgAfKvcRG3SpIkWLFggt9utXbt2af78+QoPD7diNgCAyGEA8LVyjxCPHj1aW7duVU5Ojnr37q2TJ09q1KhRVswGABA5DAC+5jLn+4LLSuL00V12jwCHqFW/nd0jwAGKi/bbPUKFkcOwAhkMK5SVweUeIc7JydHjjz+u2267TRERERo1apTy8vIu6YAAgNKRwwDgW+UW4jFjxqhBgwZavHixXn/9ddWpU0djx461YjYAgMhhAPC1cj9Ut3//fr300kve2yNHjlS3bt18OhQA4BfkMAD4VrlHiK+++mplZWV5bx86dEihoaE+HQoA8AtyGAB8q9QjxI888ogkKTc3Vz169NAdd9whPz8/bdy4UU2bNrVsQABwKnIYAKxRaiHu3LnzeZdHRkb6ahYAwFnIYQCwRqmFOC4u7rzLjTHas2ePzwYCAPyMHAYAa5T7obo333xTkyZN0qlTp7zLQkJCtG7dOp8OBgD4GTkMAL5VbiGeM2eO5s2bp5deeknDhw/Xxx9/rEOHDlkxGwBA5DAA+Fq53zIRHBysli1bqlmzZsrJydGgQYP0xRdfWDEbAEDkMAD4WrmF2N/fX8ePH1dYWJi+/fZbSZLb7fb5YACAn5HDAOBb5RbiXr166eGHH1ZkZKTeeustxcfHq1GjRlbMBgAQOQwAvuYyxpjyHlRQUKDatWvr8OHDysjIULt27VSjRg2fD3f66C6fbwOQpFr129k9AhyguGj/RT+XHEZVRgbDCmVlcKmFeN68eWWutH///r9tqgtAEMMqhDGsUNFCTA7DKchgWKGsDC71WyZ++OEHnwwDALgw5DAAWOOCTpmwS/WA6+weAQ5Rq7rv33oG8k5efkdb/clhWKA2GQwLlJXB5X6oDgAAAKjKKMQAAABwNAoxAAAAHK3cQuzxeDR37lyNHDlS+fn5mj17Nl8IDwAWIocBwLfKLcSTJk3SDz/84L060po1azRx4kSfDwYA+Bk5DAC+VW4hXr9+vVJTU1WjRg0FBgbq1Vdf1bp166yYDQAgchgAfK3cQuzv7y8/v18eFhAQIH//Ur++GABwiZHDAOBb5SZqkyZNtGDBArndbu3atUvz589XeHi4FbMBAEQOA4CvlXuEePTo0dq6datycnLUu3dvnTx5UqNGjbJiNgCAyGEA8DWuVAeIK9XBGlypDjg/rlQHK5SVweWeMjF+/PjzLh8zZszFTwQAuGDkMAD4VrmnTAQHB3v/XHHFFfr888+tmAsA8H/IYQDwrQqfMpGfn69BgwYpLS3NVzN5ccoErMIpE7DCpTplwsoc5pQJWIFTJmCFsjK4wpduDgwMVHZ29m8aCABw8chhALi0yj2H+LnnnpPL5ZIkGWO0detWNWrUyOeDAQB+Rg4DgG+VW4jr1q1b4nb37t3VvXt3nw0EACiJHAYA3yq3EO/du1eTJk2yYhYAwHmQwwDgW+WeQ/z999+rEn9VMQBUeeQwAPhWuUeIQ0ND1bVrV7Vs2VJXXHGFdznffwkA1iCHAcC3Si3ERUVFCggIUOvWrdW6dWsrZwIAiBwGAKuU+j3EcXFxSk9Pt3qeEvgeYliF7yGGFSr6PcSVIYf5HmJYge8hhhUu6nuIOV8NAOxFDgOANUo9ZeKnn37Stm3bSg3km266yWdDAQDIYQCwSqmnTDRv3lz16tU7bxC7XC599NFHPh+OUyZgFU6ZgBUqespEZchhTpmAFThlAlYoK4NLPULcuHFjLVu2zBfzAAAuADkMANYo93uIAQAAgKqs1ELcpk0bK+cAAPwKOQwA1ij1HOLKgHOIYRXOIYYVKnoOcWXAOcSwAucQwwoX9bVrAAAAgBNQiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKNRiAEAAOBoFGIAAAA4GoUYAAAAjkYhBgAAgKP5+2rFiYmJSk9PL/X+iRMnKj4+3lebBwBHI4MB4ML57NLNJ06cUGFhoSRp06ZNGj58uNauXeu9PygoSDVr1ixzHVy6GVbh0s2wgpWXbr4UGSxx6WZYg0s3wwplZbDPjhAHBQUpKChIklSnTh1JUmhoqK82h//z6itTlbHlO73wwmy7R0EVNWHiKPWIi9aPPx6TJP1/P+xS/wcetXconIMMtl501F81fnyiatSooYyM7/TQwCd04kS+3WOhiiGDfcNnhRjWCg9vrOnTUnTrra2VseU7u8dBFXbbbX9S/wce1ecbv7J7FKDSuOqqEM19eYraR/bQjh27NTFllFImjNL/e3SU3aOhiiGDfYMP1VURgx55UK/Oe0NLlrxr9yiowgICAtSi5U0a/thArf/8A6UteFHXX1/f7rEA2911153atOkb7dixW5I0a/a/dV/vOJunQlVDBvsOhbiKGDZ8jN58c5ndY6CKu/baq/XpJ+v1XPIU3X5rlL74YrMWLuL0HKDB9fWVte+A9/a+fQdVp86VCgoKtHEqVDVksO9QiAFcsD179unu+AH6btsPkqTpU19Ww4a/V1jY9TZPBtjLz89P5/uMutvttmEaVFVksO9QiAFcsJuahyuhd48Sy1wul06fLrZnIKCS2Ju1X/Xr1/Pevu66a5Sb+6MKCk7ZOBWqGjLYdyjEAC6Yx+PRP58f5z0a8Y+H+mjrlu914MAhmycD7LVq1Se67dY/qXHjhpKkhwf21Tsr/mPzVKhqyGDf4VsmAFyw77b9oKeefEZvLX5Z1fyqaf+BQxrw4HC7xwJsd+RIjv7x0ON66805Cgiorl079+jBAcPsHgtVDBnsOz67MMfZPvvsM/Xv31/bt2+v0PO4MAeswoU5YAUrL8xxtovNYIkLc8AaXJgDVigrgy0pxBeLQgyrUIhhBbsK8W9BIYYVKMSwQlkZzDnEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHoxADAADA0SjEAAAAcDQKMQAAAByNQgwAAABHcxljjN1DAAAAAHbhCDEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUIMAAAAR6MQAwAAwNEoxAAAAHA0CjEAAAAcjUJ8GeBigrDKt99+q/z8fLvHACodchhWIIPtQyG+DGzfvt3uEeAA48aN09ixY+V2u+0eBah0yGH4GhlsLwpxJTdhwgQNHz6c3xjhUxMmTNDKlSuVnJysOnXq2D0OUKmQw/A1Mth+/nYPgNKlpKRo2bJlSktLU2BgoN3joIqaNWuW0tLStHr1al1zzTU6ffq0qlevbvdYQKVADsPXyODKgSPElVRKSorS09OVlpam8PBwFRcX2z0SqqCJEydq5syZCggI0KxZsyRJ1atX5y07QOQwfI8Mrjw4QlwJTZkyRUuWLNHbb7+tRo0alfhtMTc3VyEhITZPiKogNTVVixYt0qJFi5Sfn69Bgwbpp59+0sSJE1WtWjW53W5Vq1bN7jEBW5DD8DUyuHLhCHElk52drTlz5ujuu+/W9ddfL0neEJ4+fboeeOABnTx50s4RUQXk5uYqMzNTCxcu1I033qjWrVtr8uTJWrVqlZKSkiTJG8iA05DD8DUyuPJxGb5LptLZtGmTkpKSdO+99yo+Pl4hISGaM2eO5s+fr5SUFEVGRto9IqqAoqIiBQQEyBgjl8slt9utNWvW6IknnlCnTp00ceJESeIoBRyJHIavkcGVC4W4ktq0aZNGjBihIUOGaP/+/XrjjTc0efJkRURE2D0aqjCPx6NPP/2UQAZEDsN6ZLB9KMSV2BdffKGhQ4eqsLBQqampioqKsnskOMCZQH7yySfVpUsXjR8/3u6RANuQw7AaGWwPziGuxNq2bas5c+YoKChIR48eVW5urt0jwQH8/PzUvn17TZ48WYsXL1ZycrLdIwG2IYdhNTLYHhwhvgyceduuX79+io2N5dPNsITb7db69etVv359NWrUyO5xAFuRw7AaGWwtCvFl4swHPOLj45WQkKC6devaPRIAOAo5DFRdnDJxmWjTpo2Sk5P1/vvvy+Vy2T0OADgOOQxUXRwhvsycOnVKtWrVsnsMAHAschioeijEAAAAcDROmQAAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIYYl9u3bp2bNmik2Ntb7p3v37lq8ePFvXvfDDz+spUuXSpJiY2OVl5dX6mNPnDihfv36VXgbK1euVN++fc9ZvnHjRsXExJT7/KZNm1b4CleJiYl65ZVXKvQcADgfMpgMRtn87R4AzlGzZk0tX77ce/vw4cOKiYlR8+bNFR4efkm2cfb6z+f48ePKyMi4JNsCgMsJGQyUjkIM29SrV09hYWHKzMzUtm3btHjxYp06dUqBgYFKS0vT22+/rYULF8rj8Sg4OFhPP/20brjhBh0+fFiJiYnKzs5W/fr1lZOT411n06ZNtX79eoWEhGj27NlKT0+Xv7+/wsLClJqaqqSkJBUWFio2NlZLly5VZmamJkyYoGPHjsntdqtv3766++67JUnTpk3TihUrFBwcrLCwsHL3Z/fu3UpOTtbJkyd15MgRhYeHa+rUqapRo4YkaerUqcrIyJDH49Hw4cPVoUMHSSp1PwHAl8hgMhhnMYAFsrKyTKtWrUos++qrr0zbtm3NgQMHzJIlS0zbtm3NiRMnjDHGbNy40dx3332moKDAGGPMmjVrTJcuXYwxxgwePNi88MILxhhjMjMzTatWrcySJUuMMcY0adLE5OTkmA8//NB06tTJHDt2zBhjTEpKinnxxRdLzHH69GkTHR1ttmzZYowxJi8vz0RFRZnNmzebVatWmejoaHPixAlz+vRpM3DgQNOnT59z9mvDhg2ma9euxhhjUlNTzbJly4wxxhQVFZmYmBizcuVK71yzZ882xhizfft2c+utt5qcnJwy93PkyJFm7ty5v+nnDgDGkMFkMMrDEWJY5sxRAUlyu92qW7eunn/+eV177bWSfj6yEBgYKElavXq19uzZo4SEBO/z8/LydOzYMX322WcaOXKkJCksLEy33XbbOdtav369unTpojp16kiSkpKSJP18Ht0ZmZmZ2rt3r0aNGlVixm3btmnnzp266667vPP07NlTaWlpZe7fiBEjtG7dOr388svKzMxUdna2CgoKvPf37t1bktSkSRPdcMMN2rx5s7788stS9xMALiUymAxG6SjEsMyvz1/7tdq1a3v/2+PxKDY2ViNGjPDezs7OVp06deRyuWTOusCiv/+5f42rVasml8vlvZ2Xl3fOBz3cbreCgoJKzHT06FEFBQVp0qRJJbZRrVq1cvfv8ccfl9vtVlRUlCIjI3Xw4MES6/Dz++UzrB6PR/7+/mXuJwBcSmQwGYzS8S0TqJQiIiL03nvvKTs7W5K0cOFCPfDAA5Kkdu3a6a233pIkHThwQBs3bjzn+XfccYdWrVql/Px8SdKMGTM0f/58+fv7y+12yxijhg0blvgH4uDBg4qJidGWLVvUvn17rVy5Unl5efJ4POV+UESS1q5dqyFDhig6OlqS9M0338jtdnvvT09PlyRt3bpVe/fuVcuWLcvcTwCwCxkMp+EIMSqliIgIPfTQQxowYIBcLpcCAwM1c+ZMuVwujRs3TklJSYqKitI111xz3k9H33nnndqxY4f3LbLGjRvrueeeU61atdSiRQt17dpVCxYs0IsvvqgJEyZo7ty5Ki4u1rBhw3TLLbdIkrZv366ePXvqyiuvVHh4uH788ccyZ37sscc0ZMgQ1a5dW4GBgWrbtq327t3rvT8rK0s9evSQy+XSlClTFBwcXOZ+AoBdyGAy2Glc5uz3EwAAAACH4ZQJAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaBRiAAAAOBqFGAAAAI5GIQYAAICjUYgBAADgaP8/hzNx3S0rYy4AAAAASUVORK5CYII=\n", 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\n", 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" ] @@ -1292,7 +2127,7 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 117, "id": "fa10e646", "metadata": {}, "outputs": [], @@ -1303,125 +2138,125 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 118, "id": "f8250c41", "metadata": {}, "outputs": [], "source": [ - "import tensorflow as tf\n", - "import tensorflow_hub as hub\n", - "from tensorflow import lite\n", + "# import tensorflow as tf\n", + "# import tensorflow_hub as hub\n", + "# from tensorflow import lite\n", "\n", - "SAVED_MODEL = \"saved_models\"\n", - "tf.saved_model.save(model, SAVED_MODEL)" + "# SAVED_MODEL = \"saved_models\"\n", + "# tf.saved_model.save(model, SAVED_MODEL)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 119, "id": "47dd0e88", "metadata": {}, "outputs": [], "source": [ - "#sigmodel = hub.load(SAVED_MODEL)\n", - "TFLITE_MODEL = \"tflite_models/sign.tflite\"\n", - "TFLITE_QUANT_MODEL = \"tflite_models/sign_quant.tflite\"" + "# #sigmodel = hub.load(SAVED_MODEL)\n", + "# TFLITE_MODEL = \"tflite_models/sign.tflite\"\n", + "# TFLITE_QUANT_MODEL = \"tflite_models/sign_quant.tflite\"" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 120, "id": "c3c36a2d", "metadata": {}, "outputs": [], "source": [ - "def convert_to_tflite():\n", - " converter = lite.TFLiteConverter.from_keras_model(model)\n", + "# def convert_to_tflite():\n", + "# converter = lite.TFLiteConverter.from_keras_model(model)\n", "\n", - " converter.optimizations = [tf.lite.Optimize.DEFAULT]\n", - " converter.experimental_new_converter = True\n", - " converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS,\n", - " tf.lite.OpsSet.SELECT_TF_OPS]\n", + "# converter.optimizations = [tf.lite.Optimize.DEFAULT]\n", + "# converter.experimental_new_converter = True\n", + "# converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS,\n", + "# tf.lite.OpsSet.SELECT_TF_OPS]\n", "\n", - " converted_tflite_model = converter.convert()\n", - " open(TFLITE_MODEL, \"wb\").write(converted_tflite_model)\n", + "# converted_tflite_model = converter.convert()\n", + "# open(TFLITE_MODEL, \"wb\").write(converted_tflite_model)\n", "\n", - " converter = lite.TFLiteConverter.from_keras_model(model)\n", - " converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_SIZE]\n", - " converter.experimental_new_converter = True\n", - " converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS,\n", - " tf.lite.OpsSet.SELECT_TF_OPS]\n", + "# converter = lite.TFLiteConverter.from_keras_model(model)\n", + "# converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_SIZE]\n", + "# converter.experimental_new_converter = True\n", + "# converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS,\n", + "# tf.lite.OpsSet.SELECT_TF_OPS]\n", "\n", - " tflite_quant_model = converter.convert()\n", - " open(TFLITE_QUANT_MODEL, \"wb\").write(tflite_quant_model)" + "# tflite_quant_model = converter.convert()\n", + "# open(TFLITE_QUANT_MODEL, \"wb\").write(tflite_quant_model)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 121, "id": "42a64831", "metadata": {}, "outputs": [], "source": [ - "convert_to_tflite()" + "#convert_to_tflite()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 122, "id": "a440220b", "metadata": {}, "outputs": [], "source": [ - "def use_tflite(X_test, y_test):\n", - " X_test = np.float32(X_test)\n", - " y_test = np.float32(y_test)\n", + "# def use_tflite(X_test, y_test):\n", + "# X_test = np.float32(X_test)\n", + "# y_test = np.float32(y_test)\n", " \n", - " tflite_interpreter = tf.lite.Interpreter(model_path=TFLITE_MODEL)\n", + "# tflite_interpreter = tf.lite.Interpreter(model_path=TFLITE_MODEL)\n", "\n", - " input_details = tflite_interpreter.get_input_details()\n", - " output_details = tflite_interpreter.get_output_details()\n", + "# input_details = tflite_interpreter.get_input_details()\n", + "# output_details = tflite_interpreter.get_output_details()\n", "\n", - " tflite_interpreter.resize_tensor_input(\n", - " input_details[0]['index'], X_test.shape)\n", - " tflite_interpreter.resize_tensor_input(\n", - " output_details[0]['index'], y_test.shape)\n", - " tflite_interpreter.allocate_tensors()\n", + "# tflite_interpreter.resize_tensor_input(\n", + "# input_details[0]['index'], X_test.shape)\n", + "# tflite_interpreter.resize_tensor_input(\n", + "# output_details[0]['index'], y_test.shape)\n", + "# tflite_interpreter.allocate_tensors()\n", "\n", - " input_details = tflite_interpreter.get_input_details()\n", - " output_details = tflite_interpreter.get_output_details()\n", + "# input_details = tflite_interpreter.get_input_details()\n", + "# output_details = tflite_interpreter.get_output_details()\n", "\n", - " # Load quantized TFLite model\n", - " tflite_interpreter_quant = tf.lite.Interpreter(\n", - " model_path=TFLITE_QUANT_MODEL)\n", + "# # Load quantized TFLite model\n", + "# tflite_interpreter_quant = tf.lite.Interpreter(\n", + "# model_path=TFLITE_QUANT_MODEL)\n", "\n", - " # Learn about its input and output details\n", - " input_details = tflite_interpreter_quant.get_input_details()\n", - " output_details = tflite_interpreter_quant.get_output_details()\n", + "# # Learn about its input and output details\n", + "# input_details = tflite_interpreter_quant.get_input_details()\n", + "# output_details = tflite_interpreter_quant.get_output_details()\n", "\n", - " # Resize input and output tensors\n", - " tflite_interpreter_quant.resize_tensor_input(\n", - " input_details[0]['index'], X_test.shape)\n", - " tflite_interpreter_quant.resize_tensor_input(\n", - " output_details[0]['index'], y_test.shape)\n", - " tflite_interpreter_quant.allocate_tensors()\n", + "# # Resize input and output tensors\n", + "# tflite_interpreter_quant.resize_tensor_input(\n", + "# input_details[0]['index'], X_test.shape)\n", + "# tflite_interpreter_quant.resize_tensor_input(\n", + "# output_details[0]['index'], y_test.shape)\n", + "# tflite_interpreter_quant.allocate_tensors()\n", "\n", - " input_details = tflite_interpreter_quant.get_input_details()\n", - " output_details = tflite_interpreter_quant.get_output_details()\n", + "# input_details = tflite_interpreter_quant.get_input_details()\n", + "# output_details = tflite_interpreter_quant.get_output_details()\n", "\n", - " # Run inference\n", - " tflite_interpreter_quant.set_tensor(input_details[0]['index'], X_test)\n", + "# # Run inference\n", + "# tflite_interpreter_quant.set_tensor(input_details[0]['index'], X_test)\n", "\n", - " tflite_interpreter_quant.invoke()\n", + "# tflite_interpreter_quant.invoke()\n", "\n", - " tflite_q_model_predictions = tflite_interpreter_quant.get_tensor(\n", - " output_details[0]['index'])\n", - "#print(\"\\nPrediction results shape:\", tflite_q_model_predictions.shape)" + "# tflite_q_model_predictions = tflite_interpreter_quant.get_tensor(\n", + "# output_details[0]['index'])\n", + "# #print(\"\\nPrediction results shape:\", tflite_q_model_predictions.shape)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 123, "id": "9f3171c2", "metadata": {}, "outputs": [], @@ -1736,13 +2571,7 @@ "2/2 [==============================] - 0s 11ms/step - loss: 0.0014 - categorical_accuracy: 1.0000\n", "Epoch 73/100\n", "2/2 [==============================] - 0s 14ms/step - loss: 7.9918e-04 - categorical_accuracy: 1.0000\n", - "Epoch 74/100\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Epoch 74/100\n", "2/2 [==============================] - 0s 14ms/step - loss: 0.0013 - categorical_accuracy: 1.0000\n", "Epoch 75/100\n", "2/2 [==============================] - 0s 16ms/step - loss: 9.2544e-04 - categorical_accuracy: 1.0000\n", @@ -2194,13 +3023,7 @@ "2/2 [==============================] - 0s 15ms/step - loss: 0.2208 - categorical_accuracy: 0.9286\n", "Epoch 73/100\n", "2/2 [==============================] - 0s 15ms/step - loss: 0.2832 - categorical_accuracy: 0.8810\n", - "Epoch 74/100\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Epoch 74/100\n", "2/2 [==============================] - 0s 16ms/step - loss: 0.0510 - categorical_accuracy: 0.9762\n", "Epoch 75/100\n", "2/2 [==============================] - 0s 15ms/step - loss: 0.1497 - categorical_accuracy: 0.9524\n", diff --git a/.ipynb_checkpoints/app-checkpoint.ipynb b/.ipynb_checkpoints/app-checkpoint.ipynb index 5012c49..371325f 100644 --- a/.ipynb_checkpoints/app-checkpoint.ipynb +++ b/.ipynb_checkpoints/app-checkpoint.ipynb @@ -149,7 +149,7 @@ "no_sequences = 1200\n", "\n", "# no of frames in each video\n", - "#sequence_length = 30\n", + "sequence_length = 30\n", "\n", "label_map = {label:num for num, label in enumerate(actions)}\n", "#label_map\n", @@ -171,7 +171,7 @@ "outputs": [], "source": [ "# change the .h5 file with the one you saved\n", - "model = load_model('models/weights_custom.h5')" + "model = load_model('weights_custom.h5')" ] }, { @@ -280,7 +280,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "b1950407", "metadata": { "scrolled": true @@ -294,8 +294,6 @@ "predictions = []\n", "lst = []\n", "threshold = 0.5\n", - "num_of_frames = 30\n", - "batch_size = 16\n", "\n", "cap = cv2.VideoCapture(0)\n", "# Set mediapipe model \n", @@ -318,10 +316,10 @@ " kp = extract_keypoints(results)\n", " sequence.append(kp)\n", " seq.append(keypoints)\n", - " sequence = sequence[-1*num_of_frames:]\n", - " seq = seq[-1*batch_size:]\n", + " sequence = sequence[-1*sequence_length:]\n", + " seq = seq[-1*sequence_length:]\n", " \n", - " if len(sequence) == num_of_frames:\n", + " if len(sequence) == sequence_length:\n", " res = model.predict(np.expand_dims(seq, axis=0))[0]\n", " #print(actions[np.argmax(res)])\n", "\n", diff --git a/PrepareModelBenchmark.ipynb b/PrepareModelBenchmark.ipynb index e12d8ba..fb14865 100644 --- a/PrepareModelBenchmark.ipynb +++ b/PrepareModelBenchmark.ipynb @@ -338,9 +338,11 @@ }, { "cell_type": "code", - "execution_count": 18, - "id": "19fcd4ea", - "metadata": {}, + "execution_count": 189, + "id": "f5774456", + "metadata": { + "scrolled": false + }, "outputs": [ { "data": { @@ -348,41 +350,49 @@ "30704" ] }, - "execution_count": 18, + "execution_count": 189, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "len(X)" + "len(y)" ] }, { "cell_type": "code", - "execution_count": 19, - "id": "f5774456", - "metadata": { - "scrolled": false - }, + "execution_count": 190, + "id": "130517cb", + "metadata": {}, + "outputs": [], + "source": [ + "X = X[:len(X)-(len(X)%30)]" + ] + }, + { + "cell_type": "code", + "execution_count": 191, + "id": "19fcd4ea", + "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "30704" + "30690" ] }, - "execution_count": 19, + "execution_count": 191, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "len(y)" + "len(X)" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 192, "id": "4098afde", "metadata": {}, "outputs": [], @@ -392,7 +402,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 193, "id": "799eec56", "metadata": {}, "outputs": [], @@ -402,7 +412,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 194, "id": "07af109c", "metadata": {}, "outputs": [ @@ -412,7 +422,7 @@ "(30704, 26)" ] }, - "execution_count": 22, + "execution_count": 194, "metadata": {}, "output_type": "execute_result" } @@ -423,17 +433,17 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 195, "id": "8bf41012", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(30704, 42, 3)" + "(30690, 42, 3)" ] }, - "execution_count": 23, + "execution_count": 195, "metadata": {}, "output_type": "execute_result" } @@ -444,7 +454,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 196, "id": "a524cb3f", "metadata": {}, "outputs": [], @@ -462,28 +472,28 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 197, "id": "b991ee9a", "metadata": {}, "outputs": [], "source": [ - "batch_size = 16\n", + "batch_size = 30\n", "X_total_batch, y_total_batch = batch_generate(X_total, y_total, batch_size)" ] }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 198, "id": "f59d541f", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(1919, 16, 42, 3)" + "(1023, 30, 42, 3)" ] }, - "execution_count": 26, + "execution_count": 198, "metadata": {}, "output_type": "execute_result" } @@ -494,7 +504,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 199, "id": "1f845381", "metadata": {}, "outputs": [], @@ -504,7 +514,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 200, "id": "00612e36", "metadata": {}, "outputs": [], @@ -514,17 +524,17 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 201, "id": "118e86a9", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(1919, 26)" + "(1023, 26)" ] }, - "execution_count": 29, + "execution_count": 201, "metadata": {}, "output_type": "execute_result" } @@ -535,7 +545,7 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 202, "id": "f8620c6b", "metadata": {}, "outputs": [], @@ -545,7 +555,7 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 203, "id": "43cecf26", "metadata": {}, "outputs": [], @@ -555,17 +565,17 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 204, "id": "a86cfe2b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(1535, 16, 42, 3)" + "(818, 30, 42, 3)" ] }, - "execution_count": 32, + "execution_count": 204, "metadata": {}, "output_type": "execute_result" } @@ -576,7 +586,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 205, "id": "8add1291", "metadata": {}, "outputs": [], @@ -586,17 +596,17 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 206, "id": "19d57590", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(384, 16, 42, 3)" + "(205, 30, 42, 3)" ] }, - "execution_count": 34, + "execution_count": 206, "metadata": {}, "output_type": "execute_result" } @@ -607,17 +617,17 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": 207, "id": "672571a1", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(1535, 26)" + "(818, 26)" ] }, - "execution_count": 35, + "execution_count": 207, "metadata": {}, "output_type": "execute_result" } @@ -628,17 +638,17 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": 208, "id": "cc3d2b9e", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(384, 26)" + "(205, 26)" ] }, - "execution_count": 36, + "execution_count": 208, "metadata": {}, "output_type": "execute_result" } @@ -649,7 +659,7 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": 209, "id": "6c5b0479", "metadata": {}, "outputs": [], @@ -662,7 +672,7 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": 210, "id": "a3dba74d", "metadata": {}, "outputs": [], @@ -674,7 +684,7 @@ }, { "cell_type": "code", - "execution_count": 241, + "execution_count": 211, "id": "493e3f91", "metadata": {}, "outputs": [], @@ -685,7 +695,62 @@ }, { "cell_type": "code", - "execution_count": 242, + "execution_count": 212, + "id": "6db54471", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Model: \"sequential_11\"\n", + "_________________________________________________________________\n", + " Layer (type) Output Shape Param # \n", + "=================================================================\n", + " conv2d_44 (Conv2D) (None, 30, 42, 32) 896 \n", + " \n", + " max_pooling2d_33 (MaxPoolin (None, 15, 21, 32) 0 \n", + " g2D) \n", + " \n", + " conv2d_45 (Conv2D) (None, 13, 19, 64) 18496 \n", + " \n", + " max_pooling2d_34 (MaxPoolin (None, 6, 9, 64) 0 \n", + " g2D) \n", + " \n", + " conv2d_46 (Conv2D) (None, 4, 7, 128) 73856 \n", + " \n", + " conv2d_47 (Conv2D) (None, 2, 5, 256) 295168 \n", + " \n", + " max_pooling2d_35 (MaxPoolin (None, 1, 2, 256) 0 \n", + " g2D) \n", + " \n", + " flatten_11 (Flatten) (None, 512) 0 \n", + " \n", + " dense_33 (Dense) (None, 128) 65664 \n", + " \n", + " dropout_22 (Dropout) (None, 128) 0 \n", + " \n", + " dense_34 (Dense) (None, 64) 8256 \n", + " \n", + " dropout_23 (Dropout) (None, 64) 0 \n", + " \n", + " dense_35 (Dense) (None, 26) 1690 \n", + " \n", + "=================================================================\n", + "Total params: 464,026\n", + "Trainable params: 464,026\n", + "Non-trainable params: 0\n", + "_________________________________________________________________\n" + ] + } + ], + "source": [ + "model.summary()" + ] + }, + { + "cell_type": "code", + "execution_count": 213, "id": "912211ea", "metadata": {}, "outputs": [ @@ -693,66 +758,546 @@ "name": "stdout", "output_type": "stream", "text": [ - "Epoch 1/25\n", - "39/39 [==============================] - 1s 22ms/step - loss: 3.8358 - categorical_accuracy: 0.1474 - val_loss: 2.2882 - val_categorical_accuracy: 0.2964\n", - "Epoch 2/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 1.8303 - categorical_accuracy: 0.4088 - val_loss: 1.1405 - val_categorical_accuracy: 0.6287\n", - "Epoch 3/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 1.0971 - categorical_accuracy: 0.6319 - val_loss: 0.5824 - val_categorical_accuracy: 0.8371\n", - "Epoch 4/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.6238 - categorical_accuracy: 0.7997 - val_loss: 0.3655 - val_categorical_accuracy: 0.8958\n", - "Epoch 5/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.4290 - categorical_accuracy: 0.8664 - val_loss: 0.1786 - val_categorical_accuracy: 0.9544\n", - "Epoch 6/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.2688 - categorical_accuracy: 0.9112 - val_loss: 0.1541 - val_categorical_accuracy: 0.9446\n", - "Epoch 7/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.2510 - categorical_accuracy: 0.9153 - val_loss: 0.1166 - val_categorical_accuracy: 0.9707\n", - "Epoch 8/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.1872 - categorical_accuracy: 0.9349 - val_loss: 0.0951 - val_categorical_accuracy: 0.9805\n", - "Epoch 9/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.1357 - categorical_accuracy: 0.9560 - val_loss: 0.0703 - val_categorical_accuracy: 0.9805\n", - "Epoch 10/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.1229 - categorical_accuracy: 0.9658 - val_loss: 0.1158 - val_categorical_accuracy: 0.9674\n", - "Epoch 11/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.1400 - categorical_accuracy: 0.9495 - val_loss: 0.1316 - val_categorical_accuracy: 0.9642\n", - "Epoch 12/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.1346 - categorical_accuracy: 0.9536 - val_loss: 0.0554 - val_categorical_accuracy: 0.9935\n", - "Epoch 13/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.0929 - categorical_accuracy: 0.9682 - val_loss: 0.0938 - val_categorical_accuracy: 0.9707\n", - "Epoch 14/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.1204 - categorical_accuracy: 0.9634 - val_loss: 0.0808 - val_categorical_accuracy: 0.9674\n", - "Epoch 15/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.0921 - categorical_accuracy: 0.9731 - val_loss: 0.0670 - val_categorical_accuracy: 0.9902\n", - "Epoch 16/25\n", - "39/39 [==============================] - 1s 19ms/step - loss: 0.0786 - categorical_accuracy: 0.9788 - val_loss: 0.0725 - val_categorical_accuracy: 0.9902\n", - "Epoch 17/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.0562 - categorical_accuracy: 0.9853 - val_loss: 0.0962 - val_categorical_accuracy: 0.9870\n", - "Epoch 18/25\n", - "39/39 [==============================] - 1s 18ms/step - loss: 0.0588 - categorical_accuracy: 0.9837 - val_loss: 0.0882 - val_categorical_accuracy: 0.9902\n", - "Epoch 19/25\n", - "39/39 [==============================] - 1s 20ms/step - loss: 0.0830 - categorical_accuracy: 0.9723 - val_loss: 0.0757 - val_categorical_accuracy: 0.9902\n", - "Epoch 20/25\n", - "39/39 [==============================] - 1s 21ms/step - loss: 0.1165 - categorical_accuracy: 0.9642 - val_loss: 0.0959 - val_categorical_accuracy: 0.9772\n", - "Epoch 21/25\n", - "39/39 [==============================] - 1s 22ms/step - loss: 0.0924 - categorical_accuracy: 0.9707 - val_loss: 0.0456 - val_categorical_accuracy: 0.9902\n", - "Epoch 22/25\n", - "39/39 [==============================] - 1s 21ms/step - loss: 0.0611 - categorical_accuracy: 0.9813 - val_loss: 0.0495 - val_categorical_accuracy: 0.9935\n", - "Epoch 23/25\n", - "39/39 [==============================] - 1s 21ms/step - loss: 0.0314 - categorical_accuracy: 0.9919 - val_loss: 0.0480 - val_categorical_accuracy: 0.9935\n", - "Epoch 24/25\n", - "39/39 [==============================] - 1s 21ms/step - loss: 0.0278 - categorical_accuracy: 0.9935 - val_loss: 0.0549 - val_categorical_accuracy: 0.9935\n", - "Epoch 25/25\n", - "39/39 [==============================] - 1s 22ms/step - loss: 0.0160 - categorical_accuracy: 0.9959 - val_loss: 0.0569 - val_categorical_accuracy: 0.9902\n" + "Epoch 1/250\n", + "21/21 [==============================] - 1s 27ms/step - loss: 4.6753 - categorical_accuracy: 0.1376 - val_loss: 2.6457 - val_categorical_accuracy: 0.2012\n", + "Epoch 2/250\n", + "21/21 [==============================] - 0s 21ms/step - loss: 2.1744 - categorical_accuracy: 0.3303 - val_loss: 1.4784 - val_categorical_accuracy: 0.5000\n", + "Epoch 3/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 1.4214 - categorical_accuracy: 0.5535 - val_loss: 0.8685 - val_categorical_accuracy: 0.7744\n", + "Epoch 4/250\n", + "21/21 [==============================] - 0s 21ms/step - loss: 1.0410 - categorical_accuracy: 0.6453 - val_loss: 0.5384 - val_categorical_accuracy: 0.8476\n", + "Epoch 5/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.7952 - categorical_accuracy: 0.7554 - val_loss: 0.3288 - val_categorical_accuracy: 0.9329\n", + "Epoch 6/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.5731 - categorical_accuracy: 0.8333 - val_loss: 0.2917 - val_categorical_accuracy: 0.9390\n", + "Epoch 7/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.4635 - categorical_accuracy: 0.8700 - val_loss: 0.1933 - val_categorical_accuracy: 0.9634\n", + "Epoch 8/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.3666 - categorical_accuracy: 0.9021 - val_loss: 0.2161 - val_categorical_accuracy: 0.9573\n", + "Epoch 9/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.3277 - categorical_accuracy: 0.9067 - val_loss: 0.1393 - val_categorical_accuracy: 0.9695\n", + "Epoch 10/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.3071 - categorical_accuracy: 0.9174 - val_loss: 0.1128 - val_categorical_accuracy: 0.9756\n", + "Epoch 11/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.2090 - categorical_accuracy: 0.9511 - val_loss: 0.1119 - val_categorical_accuracy: 0.9756\n", + "Epoch 12/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.2012 - categorical_accuracy: 0.9419 - val_loss: 0.0755 - val_categorical_accuracy: 0.9756\n", + "Epoch 13/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1497 - categorical_accuracy: 0.9587 - val_loss: 0.1092 - val_categorical_accuracy: 0.9695\n", + "Epoch 14/250\n", + "21/21 [==============================] - 0s 21ms/step - loss: 0.2278 - categorical_accuracy: 0.9235 - val_loss: 0.0737 - val_categorical_accuracy: 0.9756\n", + "Epoch 15/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1454 - categorical_accuracy: 0.9572 - val_loss: 0.1042 - val_categorical_accuracy: 0.9756\n", + "Epoch 16/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1029 - categorical_accuracy: 0.9725 - val_loss: 0.0979 - val_categorical_accuracy: 0.9756\n", + "Epoch 17/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1022 - categorical_accuracy: 0.9709 - val_loss: 0.1210 - val_categorical_accuracy: 0.9756\n", + "Epoch 18/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0927 - categorical_accuracy: 0.9725 - val_loss: 0.1178 - val_categorical_accuracy: 0.9695\n", + "Epoch 19/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1412 - categorical_accuracy: 0.9602 - val_loss: 0.1346 - val_categorical_accuracy: 0.9695\n", + "Epoch 20/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1014 - categorical_accuracy: 0.9679 - val_loss: 0.0620 - val_categorical_accuracy: 0.9756\n", + "Epoch 21/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1153 - categorical_accuracy: 0.9679 - val_loss: 0.0780 - val_categorical_accuracy: 0.9817\n", + "Epoch 22/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0763 - categorical_accuracy: 0.9740 - val_loss: 0.0767 - val_categorical_accuracy: 0.9878\n", + "Epoch 23/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0802 - categorical_accuracy: 0.9801 - val_loss: 0.0931 - val_categorical_accuracy: 0.9817\n", + "Epoch 24/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1222 - categorical_accuracy: 0.9709 - val_loss: 0.1875 - val_categorical_accuracy: 0.9512\n", + "Epoch 25/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0716 - categorical_accuracy: 0.9771 - val_loss: 0.0874 - val_categorical_accuracy: 0.9817\n", + "Epoch 26/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0851 - categorical_accuracy: 0.9740 - val_loss: 0.0924 - val_categorical_accuracy: 0.9817\n", + "Epoch 27/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.1095 - categorical_accuracy: 0.9709 - val_loss: 0.0583 - val_categorical_accuracy: 0.9939\n", + "Epoch 28/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0630 - categorical_accuracy: 0.9847 - val_loss: 0.0562 - val_categorical_accuracy: 0.9939\n", + "Epoch 29/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0674 - categorical_accuracy: 0.9817 - val_loss: 0.0858 - val_categorical_accuracy: 0.9817\n", + "Epoch 30/250\n", + "21/21 [==============================] - 0s 20ms/step - loss: 0.0779 - categorical_accuracy: 0.9832 - 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categorical_accuracy: 0.9954 - val_loss: 0.0872 - val_categorical_accuracy: 0.9939\n", + "Epoch 243/250\n", + "21/21 [==============================] - 0s 23ms/step - loss: 0.0223 - categorical_accuracy: 0.9954 - val_loss: 0.0664 - val_categorical_accuracy: 0.9878\n", + "Epoch 244/250\n", + "21/21 [==============================] - 0s 23ms/step - loss: 0.0263 - categorical_accuracy: 0.9924 - val_loss: 0.1150 - val_categorical_accuracy: 0.9939\n", + "Epoch 245/250\n", + "21/21 [==============================] - 0s 23ms/step - loss: 0.0132 - categorical_accuracy: 0.9924 - val_loss: 0.1034 - val_categorical_accuracy: 0.9878\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Epoch 246/250\n", + "21/21 [==============================] - 0s 22ms/step - loss: 0.0209 - categorical_accuracy: 0.9954 - val_loss: 0.0899 - val_categorical_accuracy: 0.9878\n", + "Epoch 247/250\n", + "21/21 [==============================] - 0s 22ms/step - loss: 0.0042 - categorical_accuracy: 0.9985 - val_loss: 0.1323 - val_categorical_accuracy: 0.9878\n", + "Epoch 248/250\n", + "21/21 [==============================] - 0s 23ms/step - loss: 0.0030 - categorical_accuracy: 0.9985 - val_loss: 0.1307 - val_categorical_accuracy: 0.9878\n", + "Epoch 249/250\n", + "21/21 [==============================] - 0s 23ms/step - loss: 0.0049 - categorical_accuracy: 0.9985 - val_loss: 0.1247 - val_categorical_accuracy: 0.9878\n", + "Epoch 250/250\n", + "21/21 [==============================] - 0s 22ms/step - loss: 0.0064 - categorical_accuracy: 0.9969 - val_loss: 0.1210 - val_categorical_accuracy: 0.9878\n" ] } ], "source": [ - "history = model.fit(X_train, y_train, validation_split=0.2, epochs=25)" + "history = model.fit(X_train, y_train, validation_split=0.2, epochs=250)" ] }, { "cell_type": "code", - "execution_count": 243, + "execution_count": 214, "id": "880c4b32", "metadata": {}, "outputs": [], @@ -762,7 +1307,7 @@ }, { "cell_type": "code", - "execution_count": 244, + "execution_count": 215, "id": "1184301b", "metadata": {}, "outputs": [ @@ -770,7 +1315,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy Score: 0.9921875\n" + "Accuracy Score: 0.9951219512195122\n" ] } ], @@ -784,7 +1329,7 @@ }, { "cell_type": "code", - "execution_count": 245, + "execution_count": 216, "id": "c600e018", "metadata": {}, "outputs": [ @@ -802,17 +1347,17 @@ }, { "cell_type": "code", - "execution_count": 246, + "execution_count": 217, "id": "4730fa35", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "25" + "250" ] }, - "execution_count": 246, + "execution_count": 217, "metadata": {}, "output_type": "execute_result" } @@ -823,13 +1368,13 @@ }, { "cell_type": "code", - "execution_count": 248, + "execution_count": 220, "id": "3b02b8f5", "metadata": {}, "outputs": [ { "data": { - "image/png": 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" ] @@ -852,13 +1397,13 @@ }, { "cell_type": "code", - "execution_count": 249, + "execution_count": 221, "id": "dd6f4b76", "metadata": {}, "outputs": [ { "data": { - "image/png": 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"text/plain": [ "
" ] @@ -908,7 +1453,7 @@ }, { "cell_type": "code", - "execution_count": 250, + "execution_count": 222, "id": "41873402", "metadata": {}, "outputs": [], @@ -921,7 +1466,7 @@ }, { "cell_type": "code", - "execution_count": 251, + "execution_count": 223, "id": "f73c99f3", "metadata": {}, "outputs": [], @@ -932,17 +1477,17 @@ }, { "cell_type": "code", - "execution_count": 252, + "execution_count": 224, "id": "050530cd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'L'" + "'D'" ] }, - "execution_count": 252, + "execution_count": 224, "metadata": {}, "output_type": "execute_result" } @@ -953,17 +1498,17 @@ }, { "cell_type": "code", - "execution_count": 253, + "execution_count": 225, "id": "3844a38d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'L'" + "'D'" ] }, - "execution_count": 253, + "execution_count": 225, "metadata": {}, "output_type": "execute_result" } @@ -974,13 +1519,13 @@ }, { "cell_type": "code", - "execution_count": 254, + "execution_count": 226, "id": "490d85d0", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1006,7 +1551,7 @@ }, { "cell_type": "code", - "execution_count": 255, + "execution_count": 227, "id": "3ee1d088", "metadata": {}, "outputs": [ @@ -1014,10 +1559,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "Precision Score: 0.9830128205128206\n", - "Recall Score: 0.9905982905982906\n", - "F1 Score: 0.9857885859914257\n", - "F Beta Score for Beta as 0.5 = 0.9839141601551946\n" + "Precision Score: 0.9967948717948717\n", + "Recall Score: 0.9945054945054945\n", + "F1 Score: 0.9953691793156676\n", + "F Beta Score for Beta as 0.5 = 0.9961517432813223\n" ] } ], @@ -1030,7 +1575,7 @@ }, { "cell_type": "code", - "execution_count": 256, + "execution_count": 228, "id": "66772715", "metadata": {}, "outputs": [ @@ -1040,36 +1585,36 @@ "text": [ " precision recall f1-score support\n", "\n", - " A 1.00 1.00 1.00 16\n", - " B 1.00 1.00 1.00 14\n", - " C 1.00 1.00 1.00 29\n", - " D 1.00 1.00 1.00 17\n", - " E 1.00 1.00 1.00 16\n", - " F 1.00 0.89 0.94 9\n", - " G 1.00 1.00 1.00 8\n", - " H 1.00 1.00 1.00 11\n", - " I 1.00 1.00 1.00 18\n", - " J 0.88 1.00 0.93 7\n", - " K 1.00 1.00 1.00 16\n", - " L 1.00 1.00 1.00 18\n", - " M 1.00 1.00 1.00 9\n", - " N 1.00 1.00 1.00 12\n", - " O 1.00 0.93 0.97 15\n", - " P 0.93 0.93 0.93 15\n", - " Q 0.75 1.00 0.86 3\n", - " R 1.00 1.00 1.00 16\n", - " S 1.00 1.00 1.00 17\n", - " T 1.00 1.00 1.00 17\n", - " U 1.00 1.00 1.00 14\n", + " A 1.00 1.00 1.00 4\n", + " B 1.00 1.00 1.00 8\n", + " C 1.00 1.00 1.00 4\n", + " D 1.00 1.00 1.00 12\n", + " E 1.00 1.00 1.00 5\n", + " F 1.00 1.00 1.00 10\n", + " G 0.92 1.00 0.96 11\n", + " H 1.00 1.00 1.00 8\n", + " I 1.00 1.00 1.00 10\n", + " J 1.00 1.00 1.00 8\n", + " K 1.00 1.00 1.00 9\n", + " L 1.00 1.00 1.00 9\n", + " M 1.00 1.00 1.00 8\n", + " N 1.00 1.00 1.00 7\n", + " O 1.00 1.00 1.00 8\n", + " P 1.00 1.00 1.00 8\n", + " Q 1.00 1.00 1.00 6\n", + " R 1.00 1.00 1.00 10\n", + " S 1.00 0.86 0.92 7\n", + " T 1.00 1.00 1.00 7\n", + " U 1.00 1.00 1.00 8\n", " V 1.00 1.00 1.00 11\n", - " W 1.00 1.00 1.00 19\n", - " X 1.00 1.00 1.00 18\n", - " Y 1.00 1.00 1.00 16\n", - " Z 1.00 1.00 1.00 23\n", + " W 1.00 1.00 1.00 5\n", + " X 1.00 1.00 1.00 4\n", + " Y 1.00 1.00 1.00 7\n", + " Z 1.00 1.00 1.00 11\n", "\n", - " accuracy 0.99 384\n", - " macro avg 0.98 0.99 0.99 384\n", - "weighted avg 0.99 0.99 0.99 384\n", + " accuracy 1.00 205\n", + " macro avg 1.00 0.99 1.00 205\n", + "weighted avg 1.00 1.00 1.00 205\n", "\n" ] } @@ -1081,7 +1626,7 @@ }, { "cell_type": "code", - "execution_count": 257, + "execution_count": 229, "id": "44f72c9f", "metadata": {}, "outputs": [ @@ -1089,7 +1634,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Hamming Loss: 0.0078125\n" + "Hamming Loss: 0.004878048780487805\n" ] } ], @@ -1100,7 +1645,7 @@ }, { "cell_type": "code", - "execution_count": 258, + "execution_count": 230, "id": "c1b71974", "metadata": {}, "outputs": [ @@ -1108,8 +1653,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "Jaccard Score: 0.9739316239316239\n", - "Matthews correlation coefficient: 0.9918501020941433\n" + "Jaccard Score: 0.9913003663003663\n", + "Matthews correlation coefficient: 0.9949345792170793\n" ] } ], @@ -1121,7 +1666,7 @@ }, { "cell_type": "code", - "execution_count": 259, + "execution_count": 231, "id": "6245c168", "metadata": {}, "outputs": [], @@ -1149,7 +1694,7 @@ }, { "cell_type": "code", - "execution_count": 260, + "execution_count": 232, "id": "be42467e", "metadata": {}, "outputs": [ @@ -1160,7 +1705,7 @@ " 'Z'], dtype='" ] @@ -1200,13 +1745,13 @@ }, { "cell_type": "code", - "execution_count": 262, + "execution_count": 234, "id": "7bdbc5a8", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ "
" ] @@ -1228,7 +1773,7 @@ }, { "cell_type": "code", - "execution_count": 263, + "execution_count": 235, "id": "fa10e646", "metadata": {}, "outputs": [], @@ -1239,7 +1784,7 @@ }, { "cell_type": "code", - "execution_count": 264, + "execution_count": 236, "id": "f8250c41", "metadata": {}, "outputs": [ @@ -1249,13 +1794,6 @@ "text": [ "INFO:tensorflow:Assets written to: saved_models_benchmark\\assets\n" ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "INFO:tensorflow:Assets written to: saved_models_benchmark\\assets\n" - ] } ], "source": [ @@ -1269,7 +1807,7 @@ }, { "cell_type": "code", - "execution_count": 265, + "execution_count": 237, "id": "47dd0e88", "metadata": {}, "outputs": [], @@ -1281,7 +1819,7 @@ }, { "cell_type": "code", - "execution_count": 266, + "execution_count": 238, "id": "c3c36a2d", "metadata": {}, "outputs": [], @@ -1309,7 +1847,7 @@ }, { "cell_type": "code", - "execution_count": 267, + "execution_count": 239, "id": "42a64831", "metadata": {}, "outputs": [ @@ -1317,14 +1855,13 @@ "name": "stdout", "output_type": "stream", "text": [ - "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmpto0yrz1c\\assets\n" + "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmpl7nu4ca2\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmpto0yrz1c\\assets\n", "WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded\n", "WARNING:absl:Optimization option OPTIMIZE_FOR_SIZE is deprecated, please use optimizations=[Optimize.DEFAULT] instead.\n" ] @@ -1333,14 +1870,14 @@ "name": "stdout", "output_type": "stream", "text": [ - "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmpm5ywhtaz\\assets\n" + "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmp6jt9dkh4\\assets\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ - "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmpm5ywhtaz\\assets\n", + "INFO:tensorflow:Assets written to: C:\\Users\\SHUBHAM\\AppData\\Local\\Temp\\tmp6jt9dkh4\\assets\n", "WARNING:absl:Optimization option OPTIMIZE_FOR_SIZE is deprecated, please use optimizations=[Optimize.DEFAULT] instead.\n", "WARNING:absl:Optimization option OPTIMIZE_FOR_SIZE is deprecated, please use optimizations=[Optimize.DEFAULT] instead.\n", "WARNING:absl:Buffer deduplication procedure will be skipped when flatbuffer library is not properly loaded\n" @@ -1353,7 +1890,7 @@ }, { "cell_type": "code", - "execution_count": 268, + "execution_count": 240, "id": "a440220b", "metadata": {}, "outputs": [], diff --git a/PrepareModelCustom.ipynb b/PrepareModelCustom.ipynb index 8fe9937..1f67752 100644 --- a/PrepareModelCustom.ipynb +++ b/PrepareModelCustom.ipynb @@ -167,7 +167,7 @@ "no_sequences = 30\n", "\n", "# no of frames in each video\n", - "sequence_length = 16" + "sequence_length = 30" ] }, { @@ -231,7 +231,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 13, "id": "7b4d65e2", "metadata": { "scrolled": false @@ -251,7 +251,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 14, "id": "17c51f1b", "metadata": {}, "outputs": [], @@ -262,7 +262,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 15, "id": "19fcd4ea", "metadata": {}, "outputs": [ @@ -272,7 +272,7 @@ "780" ] }, - "execution_count": 17, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -283,7 +283,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 16, "id": "f5774456", "metadata": { "scrolled": false @@ -295,7 +295,7 @@ "780" ] }, - "execution_count": 18, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -306,7 +306,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 17, "id": "4098afde", "metadata": {}, "outputs": [], @@ -316,7 +316,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 18, "id": "f8620c6b", "metadata": {}, "outputs": [], @@ -326,17 +326,17 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 19, "id": "a86cfe2b", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(624, 16, 42, 3)" + "(624, 30, 42, 3)" ] }, - "execution_count": 21, + "execution_count": 19, "metadata": {}, "output_type": "execute_result" } @@ -347,17 +347,17 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 20, "id": "19d57590", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "(156, 16, 42, 3)" + "(156, 30, 42, 3)" ] }, - "execution_count": 22, + "execution_count": 20, "metadata": {}, "output_type": "execute_result" } @@ -368,7 +368,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 21, "id": "672571a1", "metadata": {}, "outputs": [ @@ -378,7 +378,7 @@ "(624, 26)" ] }, - "execution_count": 23, + "execution_count": 21, "metadata": {}, "output_type": "execute_result" } @@ -389,7 +389,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 22, "id": "cc3d2b9e", "metadata": {}, "outputs": [ @@ -399,7 +399,7 @@ "(156, 26)" ] }, - "execution_count": 24, + "execution_count": 22, "metadata": {}, "output_type": "execute_result" } @@ -410,7 +410,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 23, "id": "6c5b0479", "metadata": {}, "outputs": [], @@ -423,7 +423,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 24, "id": "a3dba74d", "metadata": {}, "outputs": [], @@ -435,7 +435,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 25, "id": "9533039b", "metadata": {}, "outputs": [], @@ -446,7 +446,7 @@ }, { "cell_type": "code", - "execution_count": 57, + "execution_count": 92, "id": "493e3f91", "metadata": {}, "outputs": [], @@ -454,7 +454,7 @@ "model = Sequential()\n", "\n", "model.add(Conv2D(filters=32, kernel_size=(3,3), activation='relu', padding = 'same', input_shape=X_train.shape[1:]))\n", - "model.add(MaxPool2D(pool_size=(1,2), strides=None))\n", + "model.add(MaxPool2D(pool_size=(2,2), strides=None))\n", "\n", "model.add(Conv2D(filters=64, kernel_size=(3,3), activation='relu'))\n", "model.add(MaxPool2D(pool_size=(2,2), strides=None))\n", @@ -469,7 +469,6 @@ "\n", "\n", "\n", - "\n", "model.add(Flatten())\n", "\n", "model.add(Dense(128,activation =\"relu\"))\n", @@ -485,7 +484,7 @@ }, { "cell_type": "code", - "execution_count": 58, + "execution_count": 93, "id": "0e85302e", "metadata": {}, "outputs": [ @@ -493,38 +492,38 @@ "name": "stdout", "output_type": "stream", "text": [ - "Model: \"sequential_3\"\n", + "Model: \"sequential_11\"\n", "_________________________________________________________________\n", " Layer (type) Output Shape Param # \n", "=================================================================\n", - " conv2d_12 (Conv2D) (None, 16, 42, 32) 896 \n", + " conv2d_44 (Conv2D) (None, 30, 42, 32) 896 \n", " \n", - " max_pooling2d_9 (MaxPooling (None, 16, 21, 32) 0 \n", - " 2D) \n", + " max_pooling2d_33 (MaxPoolin (None, 15, 21, 32) 0 \n", + " g2D) \n", " \n", - " conv2d_13 (Conv2D) (None, 14, 19, 64) 18496 \n", + " conv2d_45 (Conv2D) (None, 13, 19, 64) 18496 \n", " \n", - " max_pooling2d_10 (MaxPoolin (None, 7, 9, 64) 0 \n", + " max_pooling2d_34 (MaxPoolin (None, 6, 9, 64) 0 \n", " g2D) \n", " \n", - " conv2d_14 (Conv2D) (None, 5, 7, 128) 73856 \n", + " conv2d_46 (Conv2D) (None, 4, 7, 128) 73856 \n", " \n", - " conv2d_15 (Conv2D) (None, 3, 5, 256) 295168 \n", + " conv2d_47 (Conv2D) (None, 2, 5, 256) 295168 \n", " \n", - " max_pooling2d_11 (MaxPoolin (None, 1, 2, 256) 0 \n", + " max_pooling2d_35 (MaxPoolin (None, 1, 2, 256) 0 \n", " g2D) \n", " \n", - " flatten_3 (Flatten) (None, 512) 0 \n", + " flatten_11 (Flatten) (None, 512) 0 \n", " \n", - " dense_9 (Dense) (None, 128) 65664 \n", + " dense_33 (Dense) (None, 128) 65664 \n", " \n", - " dropout_6 (Dropout) (None, 128) 0 \n", + " dropout_22 (Dropout) (None, 128) 0 \n", " \n", - " dense_10 (Dense) (None, 64) 8256 \n", + " dense_34 (Dense) (None, 64) 8256 \n", " \n", - " dropout_7 (Dropout) (None, 64) 0 \n", + " dropout_23 (Dropout) (None, 64) 0 \n", " \n", - " dense_11 (Dense) (None, 26) 1690 \n", + " dense_35 (Dense) (None, 26) 1690 \n", " \n", "=================================================================\n", "Total params: 464,026\n", @@ -540,7 +539,7 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": 94, "id": "a5bbb03d", "metadata": {}, "outputs": [], @@ -550,7 +549,7 @@ }, { "cell_type": "code", - "execution_count": 60, + "execution_count": 95, "id": "912211ea", "metadata": {}, "outputs": [ @@ -558,222 +557,1058 @@ "name": "stdout", "output_type": "stream", "text": [ - "Epoch 1/100\n", - "16/16 [==============================] - 1s 29ms/step - loss: 3.2229 - categorical_accuracy: 0.0721 - val_loss: 3.1005 - val_categorical_accuracy: 0.0800\n", - "Epoch 2/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 3.0234 - categorical_accuracy: 0.1082 - val_loss: 2.8460 - val_categorical_accuracy: 0.1760\n", - "Epoch 3/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 2.8585 - categorical_accuracy: 0.1403 - val_loss: 2.6667 - val_categorical_accuracy: 0.2320\n", - "Epoch 4/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 2.7114 - categorical_accuracy: 0.1924 - val_loss: 2.5688 - val_categorical_accuracy: 0.2080\n", - "Epoch 5/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 2.5513 - categorical_accuracy: 0.2365 - val_loss: 2.2031 - val_categorical_accuracy: 0.3440\n", - "Epoch 6/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 2.2395 - categorical_accuracy: 0.2806 - val_loss: 2.0264 - val_categorical_accuracy: 0.4160\n", - "Epoch 7/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 2.0219 - categorical_accuracy: 0.3327 - val_loss: 1.8286 - val_categorical_accuracy: 0.3920\n", - "Epoch 8/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.9193 - categorical_accuracy: 0.3407 - val_loss: 1.7887 - val_categorical_accuracy: 0.4400\n", - "Epoch 9/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.7239 - categorical_accuracy: 0.4409 - val_loss: 1.6786 - val_categorical_accuracy: 0.4720\n", - "Epoch 10/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.5966 - categorical_accuracy: 0.4629 - val_loss: 1.5551 - val_categorical_accuracy: 0.5520\n", - "Epoch 11/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.5733 - categorical_accuracy: 0.4569 - val_loss: 1.6099 - val_categorical_accuracy: 0.4960\n", - "Epoch 12/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.5050 - categorical_accuracy: 0.4930 - val_loss: 1.4998 - val_categorical_accuracy: 0.5600\n", - "Epoch 13/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 1.2710 - categorical_accuracy: 0.5792 - val_loss: 1.2563 - val_categorical_accuracy: 0.6320\n", - "Epoch 14/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 1.1448 - categorical_accuracy: 0.5892 - val_loss: 1.2611 - val_categorical_accuracy: 0.6080\n", - "Epoch 15/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 1.1093 - categorical_accuracy: 0.6112 - val_loss: 1.1743 - val_categorical_accuracy: 0.6560\n", - "Epoch 16/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 1.1377 - categorical_accuracy: 0.5832 - val_loss: 1.1630 - val_categorical_accuracy: 0.6960\n", - "Epoch 17/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.9505 - categorical_accuracy: 0.6633 - val_loss: 1.0647 - val_categorical_accuracy: 0.6480\n", - "Epoch 18/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.8373 - categorical_accuracy: 0.7074 - val_loss: 0.9812 - val_categorical_accuracy: 0.7680\n", - "Epoch 19/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.8333 - categorical_accuracy: 0.6914 - val_loss: 1.0481 - val_categorical_accuracy: 0.7280\n", - "Epoch 20/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.8526 - categorical_accuracy: 0.7014 - val_loss: 0.9702 - val_categorical_accuracy: 0.7280\n", - "Epoch 21/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.7415 - categorical_accuracy: 0.7415 - val_loss: 0.9232 - val_categorical_accuracy: 0.7520\n", - "Epoch 22/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.7063 - categorical_accuracy: 0.7635 - val_loss: 0.9633 - val_categorical_accuracy: 0.7520\n", - "Epoch 23/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.6511 - categorical_accuracy: 0.7796 - val_loss: 0.8636 - val_categorical_accuracy: 0.8160\n", - "Epoch 24/100\n", - "16/16 [==============================] - 0s 18ms/step - loss: 0.5929 - categorical_accuracy: 0.8056 - val_loss: 0.9440 - val_categorical_accuracy: 0.7520\n", - "Epoch 25/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.5736 - categorical_accuracy: 0.8036 - val_loss: 0.8064 - val_categorical_accuracy: 0.8000\n", - "Epoch 26/100\n", - "16/16 [==============================] - 0s 19ms/step - loss: 0.5017 - categorical_accuracy: 0.8156 - val_loss: 0.7988 - val_categorical_accuracy: 0.7840\n", - "Epoch 27/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.4334 - categorical_accuracy: 0.8317 - val_loss: 0.7012 - val_categorical_accuracy: 0.8320\n", - "Epoch 28/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.5081 - categorical_accuracy: 0.8236 - val_loss: 0.7811 - val_categorical_accuracy: 0.8080\n", - "Epoch 29/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.4240 - categorical_accuracy: 0.8437 - val_loss: 0.6682 - val_categorical_accuracy: 0.8160\n", - "Epoch 30/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.3713 - categorical_accuracy: 0.8677 - val_loss: 0.7253 - val_categorical_accuracy: 0.8480\n", - "Epoch 31/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.3603 - categorical_accuracy: 0.8717 - val_loss: 0.7806 - val_categorical_accuracy: 0.8000\n", - "Epoch 32/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.3508 - categorical_accuracy: 0.8697 - val_loss: 0.7556 - val_categorical_accuracy: 0.8240\n", - "Epoch 33/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.3315 - categorical_accuracy: 0.8918 - val_loss: 0.7645 - val_categorical_accuracy: 0.8400\n", - "Epoch 34/100\n", - "16/16 [==============================] - 0s 24ms/step - loss: 0.2965 - categorical_accuracy: 0.9038 - val_loss: 0.8480 - val_categorical_accuracy: 0.8400\n", - "Epoch 35/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.3715 - categorical_accuracy: 0.8838 - val_loss: 0.6484 - val_categorical_accuracy: 0.8720\n", - "Epoch 36/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.2969 - categorical_accuracy: 0.8858 - val_loss: 0.6275 - val_categorical_accuracy: 0.8560\n", - "Epoch 37/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.2123 - categorical_accuracy: 0.9339 - val_loss: 0.7202 - val_categorical_accuracy: 0.8640\n", - "Epoch 38/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.2941 - categorical_accuracy: 0.8978 - val_loss: 0.8392 - val_categorical_accuracy: 0.8320\n", - "Epoch 39/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.2526 - categorical_accuracy: 0.9238 - val_loss: 0.6771 - val_categorical_accuracy: 0.8560\n", - "Epoch 40/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.3140 - categorical_accuracy: 0.8858 - val_loss: 0.8108 - val_categorical_accuracy: 0.8080\n", - "Epoch 41/100\n", - "16/16 [==============================] - 0s 29ms/step - loss: 0.2606 - categorical_accuracy: 0.9319 - val_loss: 0.6298 - val_categorical_accuracy: 0.8560\n", - "Epoch 42/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.2204 - categorical_accuracy: 0.9218 - val_loss: 0.6714 - val_categorical_accuracy: 0.8560\n", - "Epoch 43/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.1692 - categorical_accuracy: 0.9339 - val_loss: 0.5969 - val_categorical_accuracy: 0.8640\n", - "Epoch 44/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.2055 - categorical_accuracy: 0.9319 - val_loss: 0.6999 - val_categorical_accuracy: 0.8800\n", - "Epoch 45/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.1948 - categorical_accuracy: 0.9419 - val_loss: 0.7755 - val_categorical_accuracy: 0.8480\n", - "Epoch 46/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.2336 - categorical_accuracy: 0.9178 - val_loss: 0.7158 - val_categorical_accuracy: 0.8560\n", - "Epoch 47/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.1922 - categorical_accuracy: 0.9299 - val_loss: 0.7854 - val_categorical_accuracy: 0.8480\n", - "Epoch 48/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.2264 - categorical_accuracy: 0.9178 - val_loss: 0.9473 - val_categorical_accuracy: 0.8240\n", - "Epoch 49/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.1565 - categorical_accuracy: 0.9539 - val_loss: 0.6922 - val_categorical_accuracy: 0.8800\n", - "Epoch 50/100\n", - "16/16 [==============================] - 1s 37ms/step - loss: 0.1425 - categorical_accuracy: 0.9519 - val_loss: 0.7299 - val_categorical_accuracy: 0.8640\n", - "Epoch 51/100\n", - "16/16 [==============================] - 1s 32ms/step - loss: 0.1028 - categorical_accuracy: 0.9719 - val_loss: 0.7734 - val_categorical_accuracy: 0.8800\n", - "Epoch 52/100\n", - "16/16 [==============================] - 0s 24ms/step - loss: 0.0776 - categorical_accuracy: 0.9699 - val_loss: 0.7024 - val_categorical_accuracy: 0.8800\n", - "Epoch 53/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.0952 - categorical_accuracy: 0.9699 - val_loss: 0.7696 - val_categorical_accuracy: 0.8720\n", - "Epoch 54/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.0979 - categorical_accuracy: 0.9699 - val_loss: 0.6391 - val_categorical_accuracy: 0.8880\n", - "Epoch 55/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.1418 - categorical_accuracy: 0.9439 - val_loss: 0.8247 - val_categorical_accuracy: 0.8560\n", - "Epoch 56/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.1139 - categorical_accuracy: 0.9579 - val_loss: 0.8348 - val_categorical_accuracy: 0.8800\n", - "Epoch 57/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.1112 - categorical_accuracy: 0.9579 - val_loss: 0.8574 - val_categorical_accuracy: 0.8560\n", - "Epoch 58/100\n", - "16/16 [==============================] - 0s 25ms/step - loss: 0.0750 - categorical_accuracy: 0.9739 - val_loss: 0.6934 - val_categorical_accuracy: 0.8800\n", - "Epoch 59/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.0794 - categorical_accuracy: 0.9840 - val_loss: 0.6185 - val_categorical_accuracy: 0.8880\n", - "Epoch 60/100\n", - "16/16 [==============================] - 0s 24ms/step - loss: 0.0797 - categorical_accuracy: 0.9739 - val_loss: 0.7429 - val_categorical_accuracy: 0.8640\n", - "Epoch 61/100\n", - "16/16 [==============================] - 0s 29ms/step - loss: 0.1981 - categorical_accuracy: 0.9379 - val_loss: 0.6515 - val_categorical_accuracy: 0.8960\n", - "Epoch 62/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.1966 - categorical_accuracy: 0.9359 - val_loss: 0.7868 - val_categorical_accuracy: 0.8640\n", - "Epoch 63/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.1372 - categorical_accuracy: 0.9559 - val_loss: 0.9240 - val_categorical_accuracy: 0.8160\n", - "Epoch 64/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.1060 - categorical_accuracy: 0.9679 - val_loss: 0.6382 - val_categorical_accuracy: 0.9120\n", - "Epoch 65/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.0911 - categorical_accuracy: 0.9739 - val_loss: 0.7762 - val_categorical_accuracy: 0.8400\n", - "Epoch 66/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.1127 - categorical_accuracy: 0.9599 - val_loss: 0.9982 - val_categorical_accuracy: 0.8160\n", - "Epoch 67/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.0752 - categorical_accuracy: 0.9760 - val_loss: 0.6734 - val_categorical_accuracy: 0.8880\n", - "Epoch 68/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.0518 - categorical_accuracy: 0.9800 - val_loss: 0.7425 - val_categorical_accuracy: 0.8960\n", - "Epoch 69/100\n", - "16/16 [==============================] - 0s 29ms/step - loss: 0.0467 - categorical_accuracy: 0.9820 - val_loss: 0.7276 - val_categorical_accuracy: 0.8720\n", - "Epoch 70/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.0737 - categorical_accuracy: 0.9760 - val_loss: 0.7341 - val_categorical_accuracy: 0.8880\n", - "Epoch 71/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.0438 - categorical_accuracy: 0.9860 - val_loss: 0.9370 - val_categorical_accuracy: 0.8720\n", - "Epoch 72/100\n", - "16/16 [==============================] - 0s 23ms/step - loss: 0.0392 - categorical_accuracy: 0.9900 - val_loss: 0.8334 - val_categorical_accuracy: 0.9120\n", - "Epoch 73/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.0310 - categorical_accuracy: 0.9900 - val_loss: 0.8172 - val_categorical_accuracy: 0.9040\n", - "Epoch 74/100\n", - "16/16 [==============================] - 0s 29ms/step - loss: 0.0563 - categorical_accuracy: 0.9860 - val_loss: 0.7033 - val_categorical_accuracy: 0.9280\n", - "Epoch 75/100\n", - "16/16 [==============================] - 0s 22ms/step - loss: 0.0486 - categorical_accuracy: 0.9800 - val_loss: 0.7949 - val_categorical_accuracy: 0.8880\n", - "Epoch 76/100\n", - "16/16 [==============================] - 0s 24ms/step - loss: 0.0749 - categorical_accuracy: 0.9739 - val_loss: 0.6894 - val_categorical_accuracy: 0.9120\n", - "Epoch 77/100\n", - "16/16 [==============================] - 0s 26ms/step - loss: 0.0817 - categorical_accuracy: 0.9699 - val_loss: 1.0077 - val_categorical_accuracy: 0.8640\n", - "Epoch 78/100\n", - "16/16 [==============================] - 0s 24ms/step - loss: 0.1340 - categorical_accuracy: 0.9499 - val_loss: 0.8971 - val_categorical_accuracy: 0.8640\n", - "Epoch 79/100\n", - "16/16 [==============================] - 0s 26ms/step - loss: 0.0939 - categorical_accuracy: 0.9739 - val_loss: 0.5820 - val_categorical_accuracy: 0.9280\n", - "Epoch 80/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.0559 - categorical_accuracy: 0.9820 - val_loss: 0.6334 - val_categorical_accuracy: 0.8880\n", - "Epoch 81/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.0580 - categorical_accuracy: 0.9820 - val_loss: 0.5898 - val_categorical_accuracy: 0.9360\n", - "Epoch 82/100\n", - "16/16 [==============================] - 0s 21ms/step - loss: 0.0438 - categorical_accuracy: 0.9820 - val_loss: 0.7552 - val_categorical_accuracy: 0.9040\n", - "Epoch 83/100\n", - "16/16 [==============================] - 0s 20ms/step - loss: 0.0458 - categorical_accuracy: 0.9860 - val_loss: 0.6963 - val_categorical_accuracy: 0.9200\n", - "Epoch 84/100\n", - "16/16 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val_categorical_accuracy: 0.9440\n", + "Epoch 495/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 1.9070e-04 - categorical_accuracy: 1.0000 - val_loss: 0.4827 - val_categorical_accuracy: 0.9440\n", + "Epoch 496/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 0.0014 - categorical_accuracy: 1.0000 - val_loss: 0.5006 - val_categorical_accuracy: 0.9360\n", + "Epoch 497/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 8.5796e-04 - categorical_accuracy: 1.0000 - val_loss: 0.4914 - val_categorical_accuracy: 0.9360\n", + "Epoch 498/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 4.7972e-04 - categorical_accuracy: 1.0000 - val_loss: 0.4816 - val_categorical_accuracy: 0.9360\n", + "Epoch 499/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 5.7910e-05 - categorical_accuracy: 1.0000 - val_loss: 0.4771 - val_categorical_accuracy: 0.9360\n", + "Epoch 500/500\n", + "16/16 [==============================] - 0s 24ms/step - loss: 5.4242e-05 - categorical_accuracy: 1.0000 - val_loss: 0.4757 - val_categorical_accuracy: 0.9440\n" ] } ], "source": [ - "history = model.fit(X_train, y_train, validation_split=0.2, epochs=100)" + "history = model.fit(X_train, y_train, validation_split=0.2, epochs=500)" ] }, { "cell_type": "code", - "execution_count": 61, + "execution_count": 96, "id": "8df847cc", "metadata": {}, "outputs": [ @@ -781,7 +1616,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy Score: 0.9423076923076923\n" + "Accuracy Score: 0.9358974358974359\n" ] } ], @@ -796,7 +1631,7 @@ }, { "cell_type": "code", - "execution_count": 62, + "execution_count": 97, "id": "c600e018", "metadata": {}, "outputs": [ @@ -814,7 +1649,7 @@ }, { "cell_type": "code", - "execution_count": 63, + "execution_count": 98, "id": "1184301b", "metadata": {}, "outputs": [ @@ -822,38 +1657,38 @@ "name": "stdout", "output_type": "stream", "text": [ - "Model: \"sequential_3\"\n", + "Model: \"sequential_11\"\n", "_________________________________________________________________\n", " Layer (type) Output Shape Param # \n", "=================================================================\n", - " conv2d_12 (Conv2D) (None, 16, 42, 32) 896 \n", + " conv2d_44 (Conv2D) (None, 30, 42, 32) 896 \n", " \n", - " max_pooling2d_9 (MaxPooling (None, 16, 21, 32) 0 \n", - " 2D) \n", + " max_pooling2d_33 (MaxPoolin (None, 15, 21, 32) 0 \n", + " g2D) \n", " \n", - " conv2d_13 (Conv2D) (None, 14, 19, 64) 18496 \n", + " conv2d_45 (Conv2D) (None, 13, 19, 64) 18496 \n", " \n", - " max_pooling2d_10 (MaxPoolin (None, 7, 9, 64) 0 \n", + " max_pooling2d_34 (MaxPoolin (None, 6, 9, 64) 0 \n", " g2D) \n", " \n", - " conv2d_14 (Conv2D) (None, 5, 7, 128) 73856 \n", + " conv2d_46 (Conv2D) (None, 4, 7, 128) 73856 \n", " \n", - " conv2d_15 (Conv2D) (None, 3, 5, 256) 295168 \n", + " conv2d_47 (Conv2D) (None, 2, 5, 256) 295168 \n", " \n", - " max_pooling2d_11 (MaxPoolin (None, 1, 2, 256) 0 \n", + " max_pooling2d_35 (MaxPoolin (None, 1, 2, 256) 0 \n", " g2D) \n", " \n", - " flatten_3 (Flatten) (None, 512) 0 \n", + " flatten_11 (Flatten) (None, 512) 0 \n", " \n", - " dense_9 (Dense) (None, 128) 65664 \n", + " dense_33 (Dense) (None, 128) 65664 \n", " \n", - " dropout_6 (Dropout) (None, 128) 0 \n", + " dropout_22 (Dropout) (None, 128) 0 \n", " \n", - " dense_10 (Dense) (None, 64) 8256 \n", + " dense_34 (Dense) (None, 64) 8256 \n", " \n", - " dropout_7 (Dropout) (None, 64) 0 \n", + " dropout_23 (Dropout) (None, 64) 0 \n", " \n", - " dense_11 (Dense) (None, 26) 1690 \n", + " dense_35 (Dense) (None, 26) 1690 \n", " \n", "=================================================================\n", "Total params: 464,026\n", @@ -869,17 +1704,17 @@ }, { "cell_type": "code", - "execution_count": 64, + "execution_count": 99, "id": "4730fa35", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "100" + "500" ] }, - "execution_count": 64, + "execution_count": 99, "metadata": {}, "output_type": "execute_result" } @@ -890,13 +1725,13 @@ }, { "cell_type": "code", - "execution_count": 66, + "execution_count": 101, "id": "3b02b8f5", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", + "image/png": 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\n", 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" ] @@ -921,13 +1756,13 @@ }, { "cell_type": "code", - "execution_count": 67, + "execution_count": 102, "id": "dd6f4b76", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -962,7 +1797,7 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": 103, "id": "41873402", "metadata": {}, "outputs": [], @@ -975,7 +1810,7 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": 104, "id": "f73c99f3", "metadata": {}, "outputs": [], @@ -986,17 +1821,17 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 105, "id": "050530cd", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'I'" + "'T'" ] }, - "execution_count": 70, + "execution_count": 105, "metadata": {}, "output_type": "execute_result" } @@ -1007,17 +1842,17 @@ }, { "cell_type": "code", - "execution_count": 71, + "execution_count": 106, "id": "3844a38d", "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "'I'" + "'T'" ] }, - "execution_count": 71, + "execution_count": 106, "metadata": {}, "output_type": "execute_result" } @@ -1028,7 +1863,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 107, "id": "880c4b32", "metadata": {}, "outputs": [], @@ -1038,13 +1873,13 @@ }, { "cell_type": "code", - "execution_count": 73, + "execution_count": 108, "id": "490d85d0", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1070,7 +1905,7 @@ }, { "cell_type": "code", - "execution_count": 74, + "execution_count": 109, "id": "3ee1d088", "metadata": {}, "outputs": [ @@ -1078,10 +1913,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "Precision Score: 0.9527930402930403\n", - "Recall Score: 0.9489926739926738\n", - "F1 Score: 0.945421860693354\n", - "F Beta Score for Beta as 0.5 = 0.9483468855680387\n" + "Precision Score: 0.9329212454212455\n", + "Recall Score: 0.9286935286935287\n", + "F1 Score: 0.9241946127752272\n", + "F Beta Score for Beta as 0.5 = 0.9273585870477405\n" ] } ], @@ -1094,7 +1929,7 @@ }, { "cell_type": "code", - "execution_count": 75, + "execution_count": 110, "id": "66772715", "metadata": {}, "outputs": [ @@ -1104,36 +1939,36 @@ "text": [ " precision recall f1-score support\n", "\n", - " A 1.00 1.00 1.00 4\n", + " A 1.00 1.00 1.00 8\n", " B 1.00 1.00 1.00 5\n", - " C 0.60 0.86 0.71 7\n", - " D 1.00 1.00 1.00 9\n", - " E 1.00 1.00 1.00 8\n", - " F 1.00 1.00 1.00 8\n", - " G 1.00 1.00 1.00 12\n", - " H 1.00 1.00 1.00 2\n", - " I 0.86 1.00 0.92 6\n", - " J 0.83 0.83 0.83 6\n", - " K 1.00 1.00 1.00 6\n", - " L 1.00 1.00 1.00 7\n", - " M 1.00 1.00 1.00 8\n", + " C 1.00 1.00 1.00 7\n", + " D 1.00 1.00 1.00 5\n", + " E 1.00 1.00 1.00 3\n", + " F 1.00 0.90 0.95 10\n", + " G 0.75 0.90 0.82 10\n", + " H 1.00 1.00 1.00 10\n", + " I 0.50 0.50 0.50 2\n", + " J 0.86 1.00 0.92 6\n", + " K 1.00 1.00 1.00 2\n", + " L 0.86 1.00 0.92 6\n", + " M 1.00 0.80 0.89 5\n", " N 1.00 1.00 1.00 5\n", - " O 1.00 0.60 0.75 10\n", - " P 0.86 1.00 0.92 6\n", - " Q 0.75 1.00 0.86 3\n", - " R 1.00 1.00 1.00 5\n", - " S 1.00 1.00 1.00 3\n", + " O 0.88 1.00 0.93 7\n", + " P 1.00 1.00 1.00 6\n", + " Q 1.00 0.86 0.92 7\n", + " R 1.00 1.00 1.00 7\n", + " S 1.00 1.00 1.00 6\n", " T 1.00 0.80 0.89 5\n", - " U 1.00 0.75 0.86 4\n", - " V 0.88 1.00 0.93 7\n", - " W 1.00 1.00 1.00 2\n", - " X 1.00 1.00 1.00 7\n", - " Y 1.00 0.83 0.91 6\n", - " Z 1.00 1.00 1.00 5\n", + " U 1.00 0.50 0.67 6\n", + " V 1.00 0.89 0.94 9\n", + " W 0.83 1.00 0.91 5\n", + " X 0.83 1.00 0.91 5\n", + " Y 0.75 1.00 0.86 3\n", + " Z 1.00 1.00 1.00 6\n", "\n", " accuracy 0.94 156\n", - " macro avg 0.95 0.95 0.95 156\n", - "weighted avg 0.95 0.94 0.94 156\n", + " macro avg 0.93 0.93 0.92 156\n", + "weighted avg 0.95 0.94 0.93 156\n", "\n" ] } @@ -1145,7 +1980,7 @@ }, { "cell_type": "code", - "execution_count": 76, + "execution_count": 111, "id": "44f72c9f", "metadata": {}, "outputs": [ @@ -1153,7 +1988,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Hamming Loss: 0.057692307692307696\n" + "Hamming Loss: 0.0641025641025641\n" ] } ], @@ -1164,7 +1999,7 @@ }, { "cell_type": "code", - "execution_count": 77, + "execution_count": 112, "id": "c1b71974", "metadata": {}, "outputs": [ @@ -1172,8 +2007,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "Jaccard Score: 0.9070138195138195\n", - "Matthews correlation coefficient: 0.9403164913771194\n" + "Jaccard Score: 0.8760625058701983\n", + "Matthews correlation coefficient: 0.9334709474777175\n" ] } ], @@ -1185,7 +2020,7 @@ }, { "cell_type": "code", - "execution_count": 78, + "execution_count": 113, "id": "6245c168", "metadata": {}, "outputs": [], @@ -1213,7 +2048,7 @@ }, { "cell_type": "code", - "execution_count": 79, + "execution_count": 114, "id": "be42467e", "metadata": {}, "outputs": [ @@ -1224,7 +2059,7 @@ " 'Z'], dtype='" ] @@ -1264,13 +2099,13 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 116, "id": "7bdbc5a8", "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", 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" ] @@ -1292,7 +2127,7 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 117, "id": "fa10e646", "metadata": {}, "outputs": [], @@ -1303,125 +2138,125 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 118, "id": "f8250c41", "metadata": {}, "outputs": [], "source": [ - "import tensorflow as tf\n", - "import tensorflow_hub as hub\n", - "from tensorflow import lite\n", + "# import tensorflow as tf\n", + "# import tensorflow_hub as hub\n", + "# from tensorflow import lite\n", "\n", - "SAVED_MODEL = \"saved_models\"\n", - "tf.saved_model.save(model, SAVED_MODEL)" + "# SAVED_MODEL = \"saved_models\"\n", + "# tf.saved_model.save(model, SAVED_MODEL)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 119, "id": "47dd0e88", "metadata": {}, "outputs": [], "source": [ - "#sigmodel = hub.load(SAVED_MODEL)\n", - "TFLITE_MODEL = \"tflite_models/sign.tflite\"\n", - "TFLITE_QUANT_MODEL = \"tflite_models/sign_quant.tflite\"" + "# #sigmodel = hub.load(SAVED_MODEL)\n", + "# TFLITE_MODEL = \"tflite_models/sign.tflite\"\n", + "# TFLITE_QUANT_MODEL = \"tflite_models/sign_quant.tflite\"" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 120, "id": "c3c36a2d", "metadata": {}, "outputs": [], "source": [ - "def convert_to_tflite():\n", - " converter = lite.TFLiteConverter.from_keras_model(model)\n", + "# def convert_to_tflite():\n", + "# converter = lite.TFLiteConverter.from_keras_model(model)\n", "\n", - " converter.optimizations = [tf.lite.Optimize.DEFAULT]\n", - " converter.experimental_new_converter = True\n", - " converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS,\n", - " tf.lite.OpsSet.SELECT_TF_OPS]\n", + "# converter.optimizations = [tf.lite.Optimize.DEFAULT]\n", + "# converter.experimental_new_converter = True\n", + "# converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS,\n", + "# tf.lite.OpsSet.SELECT_TF_OPS]\n", "\n", - " converted_tflite_model = converter.convert()\n", - " open(TFLITE_MODEL, \"wb\").write(converted_tflite_model)\n", + "# converted_tflite_model = converter.convert()\n", + "# open(TFLITE_MODEL, \"wb\").write(converted_tflite_model)\n", "\n", - " converter = lite.TFLiteConverter.from_keras_model(model)\n", - " converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_SIZE]\n", - " converter.experimental_new_converter = True\n", - " converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS,\n", - " tf.lite.OpsSet.SELECT_TF_OPS]\n", + "# converter = lite.TFLiteConverter.from_keras_model(model)\n", + "# converter.optimizations = [tf.lite.Optimize.OPTIMIZE_FOR_SIZE]\n", + "# converter.experimental_new_converter = True\n", + "# converter.target_spec.supported_ops = [tf.lite.OpsSet.TFLITE_BUILTINS,\n", + "# tf.lite.OpsSet.SELECT_TF_OPS]\n", "\n", - " tflite_quant_model = converter.convert()\n", - " open(TFLITE_QUANT_MODEL, \"wb\").write(tflite_quant_model)" + "# tflite_quant_model = converter.convert()\n", + "# open(TFLITE_QUANT_MODEL, \"wb\").write(tflite_quant_model)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 121, "id": "42a64831", "metadata": {}, "outputs": [], "source": [ - "convert_to_tflite()" + "#convert_to_tflite()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 122, "id": "a440220b", "metadata": {}, "outputs": [], "source": [ - "def use_tflite(X_test, y_test):\n", - " X_test = np.float32(X_test)\n", - " y_test = np.float32(y_test)\n", + "# def use_tflite(X_test, y_test):\n", + "# X_test = np.float32(X_test)\n", + "# y_test = np.float32(y_test)\n", " \n", - " tflite_interpreter = tf.lite.Interpreter(model_path=TFLITE_MODEL)\n", + "# tflite_interpreter = tf.lite.Interpreter(model_path=TFLITE_MODEL)\n", "\n", - " input_details = tflite_interpreter.get_input_details()\n", - " output_details = tflite_interpreter.get_output_details()\n", + "# input_details = tflite_interpreter.get_input_details()\n", + "# output_details = tflite_interpreter.get_output_details()\n", "\n", - " tflite_interpreter.resize_tensor_input(\n", - " input_details[0]['index'], X_test.shape)\n", - " tflite_interpreter.resize_tensor_input(\n", - " output_details[0]['index'], y_test.shape)\n", - " tflite_interpreter.allocate_tensors()\n", + "# tflite_interpreter.resize_tensor_input(\n", + "# input_details[0]['index'], X_test.shape)\n", + "# tflite_interpreter.resize_tensor_input(\n", + "# output_details[0]['index'], y_test.shape)\n", + "# tflite_interpreter.allocate_tensors()\n", "\n", - " input_details = tflite_interpreter.get_input_details()\n", - " output_details = tflite_interpreter.get_output_details()\n", + "# input_details = tflite_interpreter.get_input_details()\n", + "# output_details = tflite_interpreter.get_output_details()\n", "\n", - " # Load quantized TFLite model\n", - " tflite_interpreter_quant = tf.lite.Interpreter(\n", - " model_path=TFLITE_QUANT_MODEL)\n", + "# # Load quantized TFLite model\n", + "# tflite_interpreter_quant = tf.lite.Interpreter(\n", + "# model_path=TFLITE_QUANT_MODEL)\n", "\n", - " # Learn about its input and output details\n", - " input_details = tflite_interpreter_quant.get_input_details()\n", - " output_details = tflite_interpreter_quant.get_output_details()\n", + "# # Learn about its input and output details\n", + "# input_details = tflite_interpreter_quant.get_input_details()\n", + "# output_details = tflite_interpreter_quant.get_output_details()\n", "\n", - " # Resize input and output tensors\n", - " tflite_interpreter_quant.resize_tensor_input(\n", - " input_details[0]['index'], X_test.shape)\n", - " tflite_interpreter_quant.resize_tensor_input(\n", - " output_details[0]['index'], y_test.shape)\n", - " tflite_interpreter_quant.allocate_tensors()\n", + "# # Resize input and output tensors\n", + "# tflite_interpreter_quant.resize_tensor_input(\n", + "# input_details[0]['index'], X_test.shape)\n", + "# tflite_interpreter_quant.resize_tensor_input(\n", + "# output_details[0]['index'], y_test.shape)\n", + "# tflite_interpreter_quant.allocate_tensors()\n", "\n", - " input_details = tflite_interpreter_quant.get_input_details()\n", - " output_details = tflite_interpreter_quant.get_output_details()\n", + "# input_details = tflite_interpreter_quant.get_input_details()\n", + "# output_details = tflite_interpreter_quant.get_output_details()\n", "\n", - " # Run inference\n", - " tflite_interpreter_quant.set_tensor(input_details[0]['index'], X_test)\n", + "# # Run inference\n", + "# tflite_interpreter_quant.set_tensor(input_details[0]['index'], X_test)\n", "\n", - " tflite_interpreter_quant.invoke()\n", + "# tflite_interpreter_quant.invoke()\n", "\n", - " tflite_q_model_predictions = tflite_interpreter_quant.get_tensor(\n", - " output_details[0]['index'])\n", - "#print(\"\\nPrediction results shape:\", tflite_q_model_predictions.shape)" + "# tflite_q_model_predictions = tflite_interpreter_quant.get_tensor(\n", + "# output_details[0]['index'])\n", + "# #print(\"\\nPrediction results shape:\", tflite_q_model_predictions.shape)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 123, "id": "9f3171c2", "metadata": {}, "outputs": [], @@ -1736,13 +2571,7 @@ "2/2 [==============================] - 0s 11ms/step - loss: 0.0014 - categorical_accuracy: 1.0000\n", "Epoch 73/100\n", "2/2 [==============================] - 0s 14ms/step - loss: 7.9918e-04 - categorical_accuracy: 1.0000\n", - "Epoch 74/100\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Epoch 74/100\n", "2/2 [==============================] - 0s 14ms/step - loss: 0.0013 - categorical_accuracy: 1.0000\n", "Epoch 75/100\n", "2/2 [==============================] - 0s 16ms/step - loss: 9.2544e-04 - categorical_accuracy: 1.0000\n", @@ -2194,13 +3023,7 @@ "2/2 [==============================] - 0s 15ms/step - loss: 0.2208 - categorical_accuracy: 0.9286\n", "Epoch 73/100\n", "2/2 [==============================] - 0s 15ms/step - loss: 0.2832 - categorical_accuracy: 0.8810\n", - "Epoch 74/100\n" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ + "Epoch 74/100\n", "2/2 [==============================] - 0s 16ms/step - loss: 0.0510 - categorical_accuracy: 0.9762\n", "Epoch 75/100\n", "2/2 [==============================] - 0s 15ms/step - loss: 0.1497 - categorical_accuracy: 0.9524\n", diff --git a/Results/Accuracy/accuracy_benchmark.pdf b/Results/Accuracy/accuracy_benchmark.pdf index a46b6d2..b1e6926 100644 Binary files a/Results/Accuracy/accuracy_benchmark.pdf and b/Results/Accuracy/accuracy_benchmark.pdf differ diff --git a/Results/Accuracy/accuracy_custom.pdf b/Results/Accuracy/accuracy_custom.pdf index be6304f..80522dc 100644 Binary files a/Results/Accuracy/accuracy_custom.pdf and b/Results/Accuracy/accuracy_custom.pdf differ diff --git a/Results/Architecture/model_benchmark.pdf b/Results/Architecture/model_benchmark.pdf index 1e99807..bc77974 100644 Binary files a/Results/Architecture/model_benchmark.pdf and b/Results/Architecture/model_benchmark.pdf differ diff --git a/Results/Architecture/model_custom.pdf b/Results/Architecture/model_custom.pdf index 1e99807..bc77974 100644 Binary files a/Results/Architecture/model_custom.pdf and b/Results/Architecture/model_custom.pdf differ diff --git a/Results/Loss/loss_benchmark.pdf b/Results/Loss/loss_benchmark.pdf index 817e1d7..c08b5b4 100644 Binary files a/Results/Loss/loss_benchmark.pdf and b/Results/Loss/loss_benchmark.pdf differ diff --git a/Results/Loss/loss_custom.pdf b/Results/Loss/loss_custom.pdf index 52731b4..a93c75a 100644 Binary files a/Results/Loss/loss_custom.pdf and b/Results/Loss/loss_custom.pdf differ diff --git a/app.ipynb b/app.ipynb index 5012c49..371325f 100644 --- a/app.ipynb +++ b/app.ipynb @@ -149,7 +149,7 @@ "no_sequences = 1200\n", "\n", "# no of frames in each video\n", - "#sequence_length = 30\n", + "sequence_length = 30\n", "\n", "label_map = {label:num for num, label in enumerate(actions)}\n", "#label_map\n", @@ -171,7 +171,7 @@ "outputs": [], "source": [ "# change the .h5 file with the one you saved\n", - "model = load_model('models/weights_custom.h5')" + "model = load_model('weights_custom.h5')" ] }, { @@ -280,7 +280,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "b1950407", "metadata": { "scrolled": true @@ -294,8 +294,6 @@ "predictions = []\n", "lst = []\n", "threshold = 0.5\n", - "num_of_frames = 30\n", - "batch_size = 16\n", "\n", "cap = cv2.VideoCapture(0)\n", "# Set mediapipe model \n", @@ -318,10 +316,10 @@ " kp = extract_keypoints(results)\n", " sequence.append(kp)\n", " seq.append(keypoints)\n", - " sequence = sequence[-1*num_of_frames:]\n", - " seq = seq[-1*batch_size:]\n", + " sequence = sequence[-1*sequence_length:]\n", + " seq = seq[-1*sequence_length:]\n", " \n", - " if len(sequence) == num_of_frames:\n", + " if len(sequence) == sequence_length:\n", " res = model.predict(np.expand_dims(seq, axis=0))[0]\n", " #print(actions[np.argmax(res)])\n", "\n", diff --git a/architecture_diagram.drawio b/architecture_diagram.drawio new file mode 100644 index 0000000..67510da --- /dev/null +++ b/architecture_diagram.drawio @@ -0,0 +1 @@ +5Zxbc+I2FIB/DTPtAx5drIsfAwnddrKznWY6fTZYBncNZozZZPvrK4FMsKR0SeoLNrzEHPmGvnOkc46OMsLT9csvebhdfc4ikY4QiF5G+H6EEKIUyj9K8v0oYZQfBcs8iY4i+Cp4Sv4RWgi0dJ9EYlc5sciytEi2VeEi22zEoqjIwjzPnqunxVlafeo2XApL8LQIU1v6VxIVKy2FNHht+CSS5Uo/miN2bJiHi6/LPNtv9PNGCMeHz7F5HZb30j90twqj7PlMhB9GeJpnWXE8Wr9MRar6tuy243WzN1pP752LTXHJBffkEdwtf8P478fgmd4VBfz8+5j4x9t8C9O9KH/H4W2L72UPyRffqsPFfi7/TJ5XSSGetuFCyZ6lUkjZqlin8huUh3PVIyJ6nJ8Ep376si/SZCO0PArzr1/kbZJCaQ7wAKkK0UGqztwdlQao9iSXSpBkG/l9l+1VF0/iNNl+0jeNkzSdZmmWH14dR6Hg8ULdosizr+KshS64mMeyRf9+kRfi5c2ehSde0g5EthZF/l2eoi/gUKuENgEEsFdawfOrTpWKsDrTJoi1MNRqvDzd/RWlPNA030OW9IcsM8iKcFf8N9g4FnThBBuxYA5APWAZYR6poPUDanHFDq6oMax00Fj5QrixzjnxSV1YKahAJT7oGCobMtR2BmELKgceRR1z5f3has6uF3Algke+iytHc0xpPVwh4FWwMGBeQIPXD7topg24B2lTnIP+cP6A/bbC2Z5rKe14WC6fX8FKU9Vdc3mwVAcyLPkGS6l8yqnBUgDZNUUVcrU/N5mCWul8LQrTZKlQLWRXCimfqI5OZAhzpxvWSRSlb2lVflQlbeI1kBojY6S1MfkOTI15umUE+iNM6LYwMWDY0ynW6AwUugwUvi1QiHOPGajUHGfPa+3SwpfR8m+Llk+QSQsB6jHb1WyXliuRY9CKF+S2WHFQTcxAh0fRLiVXUsaiRG+LUoCr/oQjxdIuJDvFop4lXxcBH+kDbHv4gwEyhszw8KCNJAjaRGInSCDWJGCgD8ohcIhIMPBQddLBFHnIdhHaxWLnN5RHkKV7FVyG6voRkj8f/CEe/2wATiri4v+hibNN8aRfCdbAicOq5fgB9aDtGkDMbUwIe5w3RcrOUKxDZTTbLEuTzfIm4RB8HXCYnWeI92mq3lyvesouuXlTOiR04Vne7wrA2ZmHXRYXB8u6QUKUXIk92ZEr1T7CLfgKkFSxYAA8v2NPgdnhqa9RsNKPQ3y4TJDBBCm/QIIpP7BjPHZcCjWWMuBB5crzEPFQYOLpGogdg5YgyC0A8eX8YAQ8konH0PWYTI/W7D9QOTW9v0OTB0uBzhft1RWlO7GTUURUU9LOWO+Vmn5KuHZWTcXsSHfILoRZ0YYdFTIIletL7dibHcEOmoBhBRgHXnD+8bsGwu2odUgDYDtVS4FfxQwxu3SwQ7Qxsq4F9eGQvWBqq4EsBMBEyy+tCm4QLbLQDjruMu3Lh+TahlE7WTFsIoFVU+1YXWobgp2eQAOOrqyaSoxkbHWeW3XUVLZMpEfbFyB8Z/FsJOJwf1jht6Yg6ecFs5kRXUVZIft3sszDKJGIz06fzeQV+Kzt/uwtlChM61GZMfrxKj2EjrnMb6w8k/doK0SHKhKwe8BYKyqCrk5FepSk6VBFTqc3ryLGklGAnStGLWuJndxxFPwM1x0YI7PeB9npnlaTq9y1ocKok/t1s90Xt1UpN4bGJNx16X3QoxzQ+ze+tJMoMDeuUYfxtbrtJbDTP1GebTNlbeCnPJT9Jw8ODQB46OcG7K0HtQ6Qe8Dh37Rd6xDYCR1rpNQ1Kfy2BksIjFmt8+pvf8jeaGub8sdmfYsrzCCtOpCBa6vMlYJlH+Dayq78Mf2xuToDg5MR17+vt0fuDcFXaq926TpkxAOu8k3Xkj5nHmysUNCePOGpvKYsgBr0To+yB8pUPOg48CM9WnpEtMaRdFLjSGpOkDLGcO0mhcBhb+yU5q/f/enRf0mQQ8572c5mD3Q6dbG9Z8GkrtEUGQuaMhZ17T2FmLiWa0hTbIkrDLlWth+w23ZmSiNgQT71iKsYxMlWEsd+U3h75OB+IHCZ8emD23TrHJYJI8bKNyLy97hKQlxeLvfQ+/0g+fX1Pwwe2s7+jSN++Bc= \ No newline at end of file diff --git a/architecture_diagram.pdf b/architecture_diagram.pdf new file mode 100644 index 0000000..1e8fce0 Binary files /dev/null and b/architecture_diagram.pdf differ diff --git a/architecture_diagram.svg b/architecture_diagram.svg new file mode 100644 index 0000000..0f1ee92 --- /dev/null +++ b/architecture_diagram.svg @@ -0,0 +1,4 @@ + + + +
conv1
conv1
conv2
conv2
conv3
conv3
conv4
conv4
fc5
fc5
fc6
fc6
30 x 42 x 32
30 x 42 x 32
13 x 19 x 64
13 x 19 x 64
convolutional + ReLU
convolutional + ReLU
max pooling
max pooling
fully connected + ReLU
fully connected + ReLU
softmax
softmax
6 x 9 x 64
6 x 9 x 64
4 x 7 x 128
4 x 7 x 128
1 x 2 x 256
1 x 2 x 256
2 x 5 x 256
2 x 5 x 256
64
64
64
64
128
128
128
128
26
26
30 x 42 x 3
30 x 42 x 3
Input
Input
dropout (ratio = 0.2)
dropout (ratio = 0.2)
softmax8
softma...
15 x 21 x 32
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