updates
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train.py
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train.py
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@ -35,6 +35,11 @@ hyp = {'giou': 1.582, # giou loss gain
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'scale': 0.1059, # image scale (+/- gain)
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'scale': 0.1059, # image scale (+/- gain)
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'shear': 0.5768} # image shear (+/- deg)
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'shear': 0.5768} # image shear (+/- deg)
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if os.path.exists('hyp.txt'): # overwrite hyp if hyp.txt is found
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x = np.loadtxt('hyp.txt')
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for i, k in enumerate(hyp.keys()):
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hyp[k] = x[i]
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def train():
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def train():
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cfg = opt.cfg
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cfg = opt.cfg
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