update fast mode
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db2c3acd3a
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2
train.py
2
train.py
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@ -303,7 +303,7 @@ def train(hyp):
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model=ema.ema,
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single_cls=opt.single_cls,
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dataloader=testloader,
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fast=ni < n_burn)
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fast=epoch > epochs / 2)
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# Write
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with open(results_file, 'a') as f:
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@ -526,12 +526,11 @@ def non_max_suppression(prediction, conf_thres=0.1, iou_thres=0.6, fast=False, c
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time_limit = 10.0 # seconds to quit after
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redundant = True # require redundant detections
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fast |= conf_thres > 0.001 # fast mode
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multi_label = nc > 1 # multiple labels per box (adds 0.5ms/img)
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if fast:
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merge = False
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multi_label = nc > 1 # multiple labels per box (adds 0.5ms/img)
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else:
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merge = True # merge for best mAP (adds 0.5ms/img)
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multi_label = nc > 1 # multiple labels per box (adds 0.5ms/img)
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t = time.time()
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output = [None] * prediction.shape[0]
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