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A PROJECT WITH OPENCV ON LIVE FACE CAPTURE AND LIVE FACE DETECTION.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "2e4261c0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "bc8b5e14",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "< cv2.VideoCapture 0000014A9D92E010>"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vid = cv2.VideoCapture(0)\n",
+    "vid"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "be4c1cf5",
+   "metadata": {},
+   "source": [
+    " Live Capturing"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "fbd53b2b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import cv2\n",
+    "\n",
+    "vid = cv2.VideoCapture(0)\n",
+    "\n",
+    "while True:\n",
+    "    success, frame = vid.read()\n",
+    "    if not success:\n",
+    "        # If unable to read frame, break the loop\n",
+    "        break\n",
+    "    \n",
+    "    cv2.imshow(\"Video\", frame)\n",
+    "    if cv2.waitKey(1) & 0xFF == 27:\n",
+    "        break\n",
+    "\n",
+    "vid.release()\n",
+    "cv2.destroyAllWindows()\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a3bf1372",
+   "metadata": {},
+   "source": [
+    "Live capturing with face detections"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "f58e6f0d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "< cv2.VideoCapture 0000014A9D92E290>"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "vid = cv2.VideoCapture(0)\n",
+    "vid"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "d660da44",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "face_cascade =cv2.CascadeClassifier('haarcascade_frontalface_default .xml')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "a8131c25",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "vid = cv2.VideoCapture(0)\n",
+    "\n",
+    "while True:\n",
+    "    success, frame = vid.read()\n",
+    "    \n",
+    "    if frame is not None and frame.shape[0] > 0 and frame.shape[1] > 0:\n",
+    "        faces = face_cascade.detectMultiScale(frame)\n",
+    "        for (x,y,w,h) in faces:\n",
+    "            cv2.rectangle(frame,(x,y),(x+w,y+h),color=(255,0,255),thickness=3)\n",
+    "        \n",
+    "            cv2.imshow(\"Video\", frame)\n",
+    "\n",
+    "    if cv2.waitKey(1) & 0xFF == 27:\n",
+    "        break\n",
+    "\n",
+    "vid.release()\n",
+    "cv2.destroyAllWindows()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4427271d",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.4"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}