merge_batch NMS method
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8
test.py
8
test.py
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@ -17,6 +17,7 @@ def test(cfg,
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iou_thres=0.6, # for nms
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iou_thres=0.6, # for nms
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save_json=False,
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save_json=False,
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single_cls=False,
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single_cls=False,
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augment=False,
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model=None,
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model=None,
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dataloader=None):
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dataloader=None):
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# Initialize/load model and set device
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# Initialize/load model and set device
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@ -87,7 +88,7 @@ def test(cfg,
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# Disable gradients
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# Disable gradients
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with torch.no_grad():
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with torch.no_grad():
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if opt.augment: # augmented testing https://github.com/ultralytics/yolov3/issues/931
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if augment: # augmented testing https://github.com/ultralytics/yolov3/issues/931
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imgs = torch.cat((imgs,
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imgs = torch.cat((imgs,
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imgs.flip(3), # flip-lr
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imgs.flip(3), # flip-lr
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torch_utils.scale_img(imgs, 0.7), # scale
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torch_utils.scale_img(imgs, 0.7), # scale
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@ -98,7 +99,7 @@ def test(cfg,
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inf_out, train_out = model(imgs) # inference and training outputs
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inf_out, train_out = model(imgs) # inference and training outputs
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t0 += torch_utils.time_synchronized() - t
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t0 += torch_utils.time_synchronized() - t
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if opt.augment:
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if augment:
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x = torch.split(inf_out, nb, dim=0)
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x = torch.split(inf_out, nb, dim=0)
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x[1][..., 0] = width - x[1][..., 0] # flip lr
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x[1][..., 0] = width - x[1][..., 0] # flip lr
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x[2][..., :4] /= 0.7 # scale
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x[2][..., :4] /= 0.7 # scale
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@ -261,7 +262,8 @@ if __name__ == '__main__':
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opt.conf_thres,
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opt.conf_thres,
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opt.iou_thres,
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opt.iou_thres,
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opt.save_json,
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opt.save_json,
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opt.single_cls)
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opt.single_cls,
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opt.augment)
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elif opt.task == 'benchmark': # mAPs at 320-608 at conf 0.5 and 0.7
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elif opt.task == 'benchmark': # mAPs at 320-608 at conf 0.5 and 0.7
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y = []
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y = []
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