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car-detection-bayes
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FocalLoss() gamma and alpha default values

This commit is contained in:
Glenn Jocher 2020-03-13 16:51:30 -07:00
parent 208b9a73fe
commit 418269d739
2 changed files with 2 additions and 2 deletions
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2
train.py
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@ -32,7 +32,7 @@ hyp = {'giou': 3.54, # giou loss gain
'lrf': -4., # final LambdaLR learning rate = lr0 * (10 ** lrf) 'lrf': -4., # final LambdaLR learning rate = lr0 * (10 ** lrf)
'momentum': 0.937, # SGD momentum 'momentum': 0.937, # SGD momentum
'weight_decay': 0.000484, # optimizer weight decay 'weight_decay': 0.000484, # optimizer weight decay
'fl_gamma': 0.5, # focal loss gamma 'fl_gamma': 1.5, # focal loss gamma
'hsv_h': 0.0138, # image HSV-Hue augmentation (fraction) 'hsv_h': 0.0138, # image HSV-Hue augmentation (fraction)
'hsv_s': 0.678, # image HSV-Saturation augmentation (fraction) 'hsv_s': 0.678, # image HSV-Saturation augmentation (fraction)
'hsv_v': 0.36, # image HSV-Value augmentation (fraction) 'hsv_v': 0.36, # image HSV-Value augmentation (fraction)

2
utils/utils.py
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@ -340,7 +340,7 @@ def wh_iou(wh1, wh2):
class FocalLoss(nn.Module): class FocalLoss(nn.Module):
# Wraps focal loss around existing loss_fcn() https://arxiv.org/pdf/1708.02002.pdf # Wraps focal loss around existing loss_fcn() https://arxiv.org/pdf/1708.02002.pdf
# i.e. criteria = FocalLoss(nn.BCEWithLogitsLoss(), gamma=2.5) # i.e. criteria = FocalLoss(nn.BCEWithLogitsLoss(), gamma=2.5)
def __init__(self, loss_fcn, gamma=0.5, alpha=1): def __init__(self, loss_fcn, gamma=1.5, alpha=0.25):
super(FocalLoss, self).__init__() super(FocalLoss, self).__init__()
self.loss_fcn = loss_fcn self.loss_fcn = loss_fcn
self.gamma = gamma self.gamma = gamma