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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-10-25 11:03:04 -05:00
parent 39d247d7e8
commit d957b20a53
1 changed files with 17 additions and 17 deletions
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train.py
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@ -20,25 +20,25 @@ last = wdir + 'last.pt'
best = wdir + 'best.pt'
results_file = 'results.txt'
# Hyperparameters (j-series, 50.5 mAP yolov3-320) evolved by @ktian08 https://github.com/ultralytics/yolov3/issues/310
hyp = {'giou': 1.582, # giou loss gain
'cls': 27.76, # cls loss gain (CE=~1.0, uCE=~20)
'cls_pw': 1.446, # cls BCELoss positive_weight
'obj': 21.35, # obj loss gain (*=80 for uBCE with 80 classes)
'obj_pw': 3.941, # obj BCELoss positive_weight
'iou_t': 0.2635, # iou training threshold
'lr0': 0.002324, # initial learning rate (SGD=1E-3, Adam=9E-5)
# Hyperparameters (k-series, 53.3 mAP yolov3-spp-320) https://github.com/ultralytics/yolov3/issues/310
hyp = {'giou': 3.31, # giou loss gain
'cls': 42.4, # cls loss gain (CE=~1.0, uCE=~20)
'cls_pw': 1.0, # cls BCELoss positive_weight
'obj': 50.0, # obj loss gain (*=80 for uBCE with 80 classes)
'obj_pw': 1.0, # obj BCELoss positive_weight
'iou_t': 0.213, # iou training threshold
'lr0': 0.00261, # initial learning rate (SGD=1E-3, Adam=9E-5)
'lrf': -4., # final LambdaLR learning rate = lr0 * (10 ** lrf)
'momentum': 0.97, # SGD momentum
'weight_decay': 0.0004569, # optimizer weight decay
'momentum': 0.949, # SGD momentum
'weight_decay': 0.000489, # optimizer weight decay
'fl_gamma': 0.5, # focal loss gamma
'hsv_h': 0.01, # image HSV-Hue augmentation (fraction)
'hsv_s': 0.5703, # image HSV-Saturation augmentation (fraction)
'hsv_v': 0.3174, # image HSV-Value augmentation (fraction)
'degrees': 1.113, # image rotation (+/- deg)
'translate': 0.06797, # image translation (+/- fraction)
'scale': 0.1059, # image scale (+/- gain)
'shear': 0.5768} # image shear (+/- deg)
'hsv_h': 0.0103, # image HSV-Hue augmentation (fraction)
'hsv_s': 0.691, # image HSV-Saturation augmentation (fraction)
'hsv_v': 0.433, # image HSV-Value augmentation (fraction)
'degrees': 1.43, # image rotation (+/- deg)
'translate': 0.0663, # image translation (+/- fraction)
'scale': 0.11, # image scale (+/- gain)
'shear': 0.384} # image shear (+/- deg)
# Overwrite hyp with hyp*.txt (optional)
f = glob.glob('hyp*.txt')