updates
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train.py
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train.py
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@ -178,6 +178,9 @@ def train(
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print('multi_scale img_size = %g' % dataset.img_size)
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# Calculate mAP
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if opt.nosave and epochs < 10:
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results = (0, 0, 0, 0, 0)
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else:
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with torch.no_grad():
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results = test.test(cfg, data_cfg, batch_size=batch_size, img_size=img_size, model=model, conf_thres=0.1)
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