This is our team's solution for Kaggle NFL 1st and Future - Impact Detection
Work by team tara: @tereka @hidehisaarai1213 @rishigami @arutema47
Public: 7th 0.5503
Private: 13th 0.5017
fix.. Private: 8th 0.5337
pip install -r requirements.txt
train-prepare-labels.ipynb
でラベルと画像データを書き出し
Write out training images with train-prepare-labels.ipynb
2.prepare_classification_images.ipynb
でclassification用データを書き出し
Write out classification images with prepare_classification_images.ipynb
- pretrainフォルダにeffdetの事前学習モデルを入れておく
Place effdet pretrained models inside pretrain
folder.
for end model:
python train_1ststage.py --enum 15 --modeltype Endzone --cutmix --strech 3 --imsize 1024 --bs 3 --all --effdet effdet4 --lr 1e-4
for side model:
python train_1ststage.py --enum 15 --modeltype Sideline --cutmix --strech 3 --imsize 1024 --bs 3 --all --effdet effdet4 --lr 1e-4
classification
python train_2ndstage.py --all
- 1ststage-inferenceでdetection結果を取得
Get inference results with 1st-stage-Inference.ipynb
2.2nd stage-inferenceでclassification。
CLassify with 2nd-stage-Inference.ipynb
CV: 0.47~0.5