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car-detection-bayes
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updates

This commit is contained in:
Glenn Jocher 2019-12-06 23:58:47 -08:00
parent a066a7b8ea
commit 2c0985f366
1 changed files with 13 additions and 13 deletions
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train.py
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@ -21,24 +21,24 @@ best = wdir + 'best.pt'
results_file = 'results.txt' results_file = 'results.txt'
# Hyperparameters (results68: 59.2 mAP@0.5 yolov3-spp-416) https://github.com/ultralytics/yolov3/issues/310 # Hyperparameters (results68: 59.2 mAP@0.5 yolov3-spp-416) https://github.com/ultralytics/yolov3/issues/310
hyp = {'giou': 3.31, # giou loss gain hyp = {'giou': 3.54, # giou loss gain
'cls': 42.4, # cls loss gain 'cls': 37.4, # cls loss gain
'cls_pw': 1.0, # cls BCELoss positive_weight 'cls_pw': 1.0, # cls BCELoss positive_weight
'obj': 52.0, # obj loss gain (*=img_size/416 if img_size != 416) 'obj': 64.3, # obj loss gain (*=img_size/416 if img_size != 416)
'obj_pw': 1.0, # obj BCELoss positive_weight 'obj_pw': 1.0, # obj BCELoss positive_weight
'iou_t': 0.213, # iou training threshold 'iou_t': 0.225, # iou training threshold
'lr0': 0.00261, # initial learning rate (SGD=1E-3, Adam=9E-5) 'lr0': 0.00579, # initial learning rate (SGD=1E-3, Adam=9E-5)
'lrf': -4., # final LambdaLR learning rate = lr0 * (10 ** lrf) 'lrf': -4., # final LambdaLR learning rate = lr0 * (10 ** lrf)
'momentum': 0.949, # SGD momentum 'momentum': 0.937, # SGD momentum
'weight_decay': 0.000489, # optimizer weight decay 'weight_decay': 0.000484, # optimizer weight decay
'fl_gamma': 0.5, # focal loss gamma 'fl_gamma': 0.5, # focal loss gamma
'hsv_h': 0.0103, # image HSV-Hue augmentation (fraction) 'hsv_h': 0.0138, # image HSV-Hue augmentation (fraction)
'hsv_s': 0.691, # image HSV-Saturation augmentation (fraction) 'hsv_s': 0.678, # image HSV-Saturation augmentation (fraction)
'hsv_v': 0.433, # image HSV-Value augmentation (fraction) 'hsv_v': 0.36, # image HSV-Value augmentation (fraction)
'degrees': 1.43, # image rotation (+/- deg) 'degrees': 1.98, # image rotation (+/- deg)
'translate': 0.0663, # image translation (+/- fraction) 'translate': 0.0779, # image translation (+/- fraction)
'scale': 0.11, # image scale (+/- gain) 'scale': 0.11, # image scale (+/- gain)
'shear': 0.384} # image shear (+/- deg) 'shear': 0.641} # image shear (+/- deg)
# Overwrite hyp with hyp*.txt (optional) # Overwrite hyp with hyp*.txt (optional)
f = glob.glob('hyp*.txt') f = glob.glob('hyp*.txt')