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@@ -193,7 +193,7 @@ def train(hyp): |
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check_anchors(dataset, model=model, thr=hyp['anchor_t'], imgsz=imgsz) |
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# Exponential moving average |
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ema = torch_utils.ModelEMA(model, updates=start_epoch * nb / accumulate) |
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ema = torch_utils.ModelEMA(model) |
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# Start training |
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t0 = time.time() |
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@@ -223,7 +223,7 @@ def train(hyp): |
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pbar = tqdm(enumerate(dataloader), total=nb) # progress bar |
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for i, (imgs, targets, paths, _) in pbar: # batch ------------------------------------------------------------- |
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ni = i + nb * epoch # number integrated batches (since train start) |
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imgs = imgs.to(device).float() / 255.0 # uint8 to float32, 0 - 255 to 0.0 - 1.0 |
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imgs = imgs.to(device, non_blocking=True).float() / 255.0 # uint8 to float32, 0 - 255 to 0.0 - 1.0 |
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# Warmup |
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if ni <= nw: |