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update times to end-to-end latency (inference + NMS)
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@ -62,7 +62,6 @@ def detect(save_img=False):
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# Inference
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t1 = torch_utils.time_synchronized()
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pred = model(img, augment=opt.augment)[0]
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t2 = torch_utils.time_synchronized()
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# to float
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if half:
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@ -71,6 +70,7 @@ def detect(save_img=False):
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# Apply NMS
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pred = non_max_suppression(pred, opt.conf_thres, opt.iou_thres,
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fast=True, classes=opt.classes, agnostic=opt.agnostic_nms)
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t2 = torch_utils.time_synchronized()
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# Apply Classifier
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if classify:
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