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hyp : scaling and mosaic w/ scliang before mosaic

pull/2109/head
hanoch 2024-11-04 10:13:35 +02:00
parent 15755c31b9
commit b2bc3773a1
1 changed files with 37 additions and 0 deletions
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data/hyp.tir_od.tiny_aug_gamma_scaling_before_mosaic_rnd_scaling.yaml 100644
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lr0: 0.001 #0.001 # initial learning rate (SGD=1E-2, Adam=1E-3)
lrf: 0.01 # final OneCycleLR learning rate (lr0 * lrf)
momentum: 0.937 # SGD momentum/Adam beta1
weight_decay: 0.005 # optimizer weight decay 5e-4 It resolve mAP of overfitting test
warmup_epochs: 3.0 # warmup epochs (fractions ok)
warmup_momentum: 0.8 # warmup initial momentum
warmup_bias_lr: 0.001 #0.001 # warmup initial bias lr
box: 0.05 # box loss gain
cls: 0.5 # cls loss gain
cls_pw: 1.0 # cls BCELoss positive_weight
obj: 1.0 # obj loss gain (scale with pixels)
obj_pw: 1.0 # obj BCELoss positive_weight
iou_t: 0.60 # like the default in the code was 0.2 IoU training threshold
anchor_t: 4.0 # anchor-multiple threshold
anchors: 2 # anchors per output layer (0 to ignore) @@HK was 3
fl_gamma: 1.5 #1.5 # focal loss gamma (efficientDet default gamma=1.5)
hsv_h: 0.0 # image HSV-Hue augmentation (fraction)
hsv_s: 0.0 # image HSV-Saturation augmentation (fraction)
hsv_v: 0.0 # image HSV-Value augmentation (fraction)
degrees: 0 # image rotation (+/- deg)
translate: 0 # image translation (+/- fraction)
scale: 0 # image scale (+/- gain)
shear: 0.0 # image shear (+/- deg)
perspective: 0.0 # image perspective (+/- fraction), range 0-0.001
flipud: 0.3 # image flip up-down (probability)
fliplr: 0.5 # image flip left-right (probability)
mosaic: 0.5 # image mosaic (probability)
mixup: 0.15 # image mixup (probability)
copy_paste: 0.0 # image copy paste (probability)
paste_in: 0.0 # image copy paste (probability), use 0 for faster training : cutout
loss_ota: 0 #1 # use ComputeLossOTA, use 0 for faster training
inversion: 0.5 #opposite temperature
img_percentile_removal: 0.3
beta : 0.3
random_perspective : 0
scaling_before_mosaic : 1
gamma : 80 # percent