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test.py native --single-cls (#2928)

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Glenn Jocher 2021-04-25 20:05:16 +02:00 committed by GitHub
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test.py
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@ -119,7 +119,7 @@ def test(data,
targets[:, 2:] *= torch.Tensor([width, height, width, height]).to(device) # to pixels targets[:, 2:] *= torch.Tensor([width, height, width, height]).to(device) # to pixels
lb = [targets[targets[:, 0] == i, 1:] for i in range(nb)] if save_hybrid else [] # for autolabelling lb = [targets[targets[:, 0] == i, 1:] for i in range(nb)] if save_hybrid else [] # for autolabelling
t = time_synchronized() t = time_synchronized()
out = non_max_suppression(out, conf_thres=conf_thres, iou_thres=iou_thres, labels=lb, multi_label=True) out = non_max_suppression(out, conf_thres, iou_thres, labels=lb, multi_label=True, agnostic=single_cls)
t1 += time_synchronized() - t t1 += time_synchronized() - t
# Statistics per image # Statistics per image
@ -136,6 +136,8 @@ def test(data,
continue continue
# Predictions # Predictions
if single_cls:
pred[:, 5] = 0
predn = pred.clone() predn = pred.clone()
scale_coords(img[si].shape[1:], predn[:, :4], shapes[si][0], shapes[si][1]) # native-space pred scale_coords(img[si].shape[1:], predn[:, :4], shapes[si][0], shapes[si][1]) # native-space pred