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train.cmd
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train.cmd
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rem starting script for Windows.
rem train from scratch
rem python train.py gpus='0' backbone="CSPDarknet-s" num_epochs=300 exp_id="coco_CSPDarknet-s_640x640" use_amp=False val_intervals=1 data_num_workers=8
rem load pre-train weight
rem python train.py gpus='0' backbone="CSPDarknet-s" num_epochs=300 exp_id="coco_CSPDarknet-s_640x640" use_amp=False val_intervals=1 data_num_workers=4 load_model="f:/weights/yolox-s.pth" resume=False dataset_path=D:/coco_dataset
python train.py gpus='0' backbone="CSPDarknet-nano" num_epochs=300 exp_id="coco_CSPDarknet-nano_640x640" use_amp=False val_intervals=1 data_num_workers=4 load_model="f:/weights/yolox-nano.pth" resume=False dataset_path=D:/coco_dataset label_name="redheader,stamp"
rem resume 'model_best.pth / model_num.pth', includes weight and epoch
rem python train.py gpus='0' backbone="CSPDarknet-s" num_epochs=300 exp_id="coco_CSPDarknet-s_640x640" use_amp=False val_intervals=1 data_num_workers=8 load_model="exp/coco_CSPDarknet-s_640x640/model_best.pth" resume=True
rem resume 'model_last.pth', includes weight, optimizer, scaler and epoch
rem python train.py gpus='0' backbone="CSPDarknet-s" num_epochs=300 exp_id="coco_CSPDarknet-s_640x640" use_amp=False val_intervals=1 data_num_workers=8 load_model="exp/coco_CSPDarknet-s_640x640/model_last.pth" resume=True