|
| 1 | +# YOLOv5 🚀 by Ultralytics, GPL-3.0 license |
| 2 | +# Hyperparameters when using Albumentations frameworks |
| 3 | +# python train.py --hyp hyp.no-augmentation.yaml |
| 4 | +# See https://github.com/ultralytics/yolov5/pull/3882 for YOLOv5 + Albumentations Usage examples |
| 5 | + |
| 6 | +lr0: 0.01 # initial learning rate (SGD=1E-2, Adam=1E-3) |
| 7 | +lrf: 0.1 # final OneCycleLR learning rate (lr0 * lrf) |
| 8 | +momentum: 0.937 # SGD momentum/Adam beta1 |
| 9 | +weight_decay: 0.0005 # optimizer weight decay 5e-4 |
| 10 | +warmup_epochs: 3.0 # warmup epochs (fractions ok) |
| 11 | +warmup_momentum: 0.8 # warmup initial momentum |
| 12 | +warmup_bias_lr: 0.1 # warmup initial bias lr |
| 13 | +box: 0.05 # box loss gain |
| 14 | +cls: 0.3 # cls loss gain |
| 15 | +cls_pw: 1.0 # cls BCELoss positive_weight |
| 16 | +obj: 0.7 # obj loss gain (scale with pixels) |
| 17 | +obj_pw: 1.0 # obj BCELoss positive_weight |
| 18 | +iou_t: 0.20 # IoU training threshold |
| 19 | +anchor_t: 4.0 # anchor-multiple threshold |
| 20 | +# anchors: 3 # anchors per output layer (0 to ignore) |
| 21 | +# this parameters are all zero since we want to use albumentation framework |
| 22 | +fl_gamma: 0.0 # focal loss gamma (efficientDet default gamma=1.5) |
| 23 | +hsv_h: 0 # image HSV-Hue augmentation (fraction) |
| 24 | +hsv_s: 00 # image HSV-Saturation augmentation (fraction) |
| 25 | +hsv_v: 0 # image HSV-Value augmentation (fraction) |
| 26 | +degrees: 0.0 # image rotation (+/- deg) |
| 27 | +translate: 0 # image translation (+/- fraction) |
| 28 | +scale: 0 # image scale (+/- gain) |
| 29 | +shear: 0 # image shear (+/- deg) |
| 30 | +perspective: 0.0 # image perspective (+/- fraction), range 0-0.001 |
| 31 | +flipud: 0.0 # image flip up-down (probability) |
| 32 | +fliplr: 0.0 # image flip left-right (probability) |
| 33 | +mosaic: 0.0 # image mosaic (probability) |
| 34 | +mixup: 0.0 # image mixup (probability) |
| 35 | +copy_paste: 0.0 # segment copy-paste (probability) |
0 commit comments