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Update run-once lines (#2058)
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@ -56,9 +56,9 @@ def detect(save_img=False):
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colors = [[random.randint(0, 255) for _ in range(3)] for _ in names]
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# Run inference
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if device.type != 'cpu':
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model(torch.zeros(1, 3, imgsz, imgsz).to(device).type_as(next(model.parameters()))) # run once
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t0 = time.time()
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img = torch.zeros((1, 3, imgsz, imgsz), device=device) # init img
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_ = model(img.half() if half else img) if device.type != 'cpu' else None # run once
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for path, img, im0s, vid_cap in dataset:
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img = torch.from_numpy(img).to(device)
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img = img.half() if half else img.float() # uint8 to fp16/32
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4
test.py
4
test.py
@ -82,8 +82,8 @@ def test(data,
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# Dataloader
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if not training:
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img = torch.zeros((1, 3, imgsz, imgsz), device=device) # init img
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_ = model(img.half() if half else img) if device.type != 'cpu' else None # run once
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if device.type != 'cpu':
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model(torch.zeros(1, 3, imgsz, imgsz).to(device).type_as(next(model.parameters()))) # run once
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path = data['test'] if opt.task == 'test' else data['val'] # path to val/test images
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dataloader = create_dataloader(path, imgsz, batch_size, model.stride.max(), opt, pad=0.5, rect=True,
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prefix=colorstr('test: ' if opt.task == 'test' else 'val: '))[0]
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