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@@ -143,7 +143,7 @@ def run(data, |
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batch_size = model.batch_size |
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else: |
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device = model.device |
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if not pt or jit: |
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if not (pt or jit): |
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batch_size = 1 # export.py models default to batch-size 1 |
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LOGGER.info(f'Forcing --batch-size 1 square inference (1,3,{imgsz},{imgsz}) for non-PyTorch models') |
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@@ -152,6 +152,7 @@ def run(data, |
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# Configure |
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model.eval() |
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cuda = device.type != 'cpu' |
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is_coco = isinstance(data.get('val'), str) and data['val'].endswith('coco/val2017.txt') # COCO dataset |
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nc = 1 if single_cls else int(data['nc']) # number of classes |
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iouv = torch.linspace(0.5, 0.95, 10).to(device) # iou vector for mAP@0.5:0.95 |
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@@ -177,7 +178,7 @@ def run(data, |
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pbar = tqdm(dataloader, desc=s, bar_format='{l_bar}{bar:10}{r_bar}{bar:-10b}') # progress bar |
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for batch_i, (im, targets, paths, shapes) in enumerate(pbar): |
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t1 = time_sync() |
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if pt or jit or engine: |
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if cuda: |
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im = im.to(device, non_blocking=True) |
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targets = targets.to(device) |
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im = im.half() if half else im.float() # uint8 to fp16/32 |