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# run script in /script/get_coco_dataset_2017.sh to download COCO 2017 Dataset# preprocess coco datasetcd data
mkdir dataset
cd ..
cd scripts
python coco_convert.py --input ./coco/annotations/instances_val2017.json --output val2017.pkl
python coco_annotation.py --coco_path ./coco
cd ..
# evaluate yolov4 model
python evaluate.py --weights ./data/yolov4.weights
cd mAP/extra
python remove_space.py
cd ..
python main.py --output results_yolov4_tf
# Prepare your dataset# If you want to train from scratch:
In config.py set FISRT_STAGE_EPOCHS=0
# Run script:
python train.py
# Transfer learning:
python train.py --weights ./data/yolov4.weights
TODO
YOLOv4 tflite on android
YOLOv4 tflite on ios
Training code
Update scale xy
ciou
Mosaic data augmentation
Mish activation
yolov4 tflite version
yolov4 in8 tflite version for mobile
References
YOLOv4: Optimal Speed and Accuracy of Object Detection YOLOv4.