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car-detection-bayes
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Glenn Jocher 2019-07-14 22:28:48 +02:00
parent 9c776b8052
commit 6509d8e588
1 changed files with 13 additions and 9 deletions
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train.py
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@ -15,19 +15,23 @@ from utils.utils import *
# 0.223 0.218 0.138 0.189 9.28 1.153 4.376 0.08263 24.28 3.05 20.93 2.842 0.2759 0.001357 -5.036 0.9158 0.0005722 mAP/F1 - 50/50 weighting # 0.223 0.218 0.138 0.189 9.28 1.153 4.376 0.08263 24.28 3.05 20.93 2.842 0.2759 0.001357 -5.036 0.9158 0.0005722 mAP/F1 - 50/50 weighting
# 0.231 0.215 0.135 0.191 9.51 1.432 3.007 0.06082 24.87 3.477 24.13 2.802 0.3436 0.001127 -5.036 0.9232 0.0005874 # 0.231 0.215 0.135 0.191 9.51 1.432 3.007 0.06082 24.87 3.477 24.13 2.802 0.3436 0.001127 -5.036 0.9232 0.0005874
# 0.246 0.194 0.128 0.192 8.12 1.101 3.954 0.0817 22.83 3.967 19.83 1.779 0.3352 0.000895 -5.036 0.9238 0.0007973 # 0.246 0.194 0.128 0.192 8.12 1.101 3.954 0.0817 22.83 3.967 19.83 1.779 0.3352 0.000895 -5.036 0.9238 0.0007973
# 0.242 0.296 0.196 0.231 5.67 0.8541 4.286 0.1539 21.61 1.957 22.9 2.894 0.3689 0.001844 -4 0.913 0.000467
# 0.298 0.244 0.167 0.247 4.99 0.8896 4.067 0.1694 21.41 2.033 25.61 1.783 0.4115 0.00128 -4 0.950 0.000377
# 0.268 0.268 0.178 0.240 4.36 1.104 5.596 0.2087 14.47 2.599 16.27 2.406 0.4114 0.001585 -4 0.950 0.000524
# 0.161 0.327 0.190 0.193 7.82 1.153 4.062 0.1845 24.28 3.05 20.93 2.842 0.2759 0.001357 -4 0.916 0.000572 # 320 --epochs 2
hyp = {'giou': 1.153, # giou loss gain hyp = {'giou': 0.8541, # giou loss gain
'xy': 4.062, # xy loss gain 'xy': 4.062, # xy loss gain
'wh': 0.1845, # wh loss gain 'wh': 0.1845, # wh loss gain
'cls': 24.28, # cls loss gain 'cls': 21.61, # cls loss gain
'cls_pw': 3.05, # cls BCELoss positive_weight 'cls_pw': 1.957, # cls BCELoss positive_weight
'obj': 20.93, # obj loss gain 'obj': 22.9, # obj loss gain
'obj_pw': 2.842, # obj BCELoss positive_weight 'obj_pw': 2.894, # obj BCELoss positive_weight
'iou_t': 0.2759, # iou target-anchor training threshold 'iou_t': 0.3689, # iou target-anchor training threshold
'lr0': 0.001357, # initial learning rate 'lr0': 0.001844, # initial learning rate
'lrf': -4., # final learning rate = lr0 * (10 ** lrf) 'lrf': -4., # final learning rate = lr0 * (10 ** lrf)
'momentum': 0.9158, # SGD momentum 'momentum': 0.913, # SGD momentum
'weight_decay': 0.0005722} # optimizer weight decay 'weight_decay': 0.000467} # optimizer weight decay
def train( def train(