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hyp.scratch.yaml
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optimizer:
optimizer: momentum
lr_init: 0.01 # initial learning rate (SGD=1E-2, Adam=1E-3)
gp_weight_decay: 0.001 # optimizer weight decay 5e-4
momentum: 0.937 # SGD momentum/Adam beta1
nesterov: True # update gradients with NAG(Nesterov Accelerated Gradient) algorithm
loss_scale: 1.0 # loss scale for optimizer
warmup_epochs: 3 # warmup epochs (fractions ok)
warmup_momentum: 0.8 # warmup initial momentum
warmup_bias_lr: 0.1 # warmup initial bias lr
min_warmup_step: 1000 # minimum warmup step
group_param: yolov3 # group param strategy
start_factor: 1.0
end_factor: 0.1
loss:
name: YOLOv3Loss
box: 0.05 # box loss gain
cls: 0.3 # cls loss gain
cls_pw: 1.0 # cls BCELoss positive_weight
obj: 0.7 # obj loss gain (scale with pixels)
obj_pw: 1.0 # obj BCELoss positive_weight
fl_gamma: 0.0 # focal loss gamma (efficientDet default gamma=1.5)
iou_t: 0.20 # IoU training threshold
anchor_t: 4.0 # anchor-multiple threshold
label_smoothing: 0.0 # label smoothing epsilon
data:
num_parallel_workers: 4
train_transforms:
- { func_name: mosaic, prob: 1.0 }
- { func_name: resample_segments }
- { func_name: random_perspective, prob: 1.0, degrees: 0.0, translate: 0.1, scale: 0.9, shear: 0.0 }
- { func_name: mixup, alpha: 8.0, beta: 8.0, prob: 0.1, pre_transform: [
{ func_name: mosaic, prob: 1.0 },
{ func_name: resample_segments },
{ func_name: random_perspective, prob: 1.0, degrees: 0.0, translate: 0.1, scale: 0.9, shear: 0.0 }, ]
}
- { func_name: hsv_augment, prob: 1.0, hgain: 0.015, sgain: 0.7, vgain: 0.4 }
- { func_name: albumentations }
- { func_name: fliplr, prob: 0.5 }
- { func_name: label_norm, xyxy2xywh_: True }
- { func_name: label_pad, padding_size: 160, padding_value: -1 }
- { func_name: image_norm, scale: 255. }
- { func_name: image_transpose, bgr2rgb: True, hwc2chw: True }
test_transforms:
- { func_name: letterbox, scaleup: False, only_image: True }
- { func_name: image_norm, scale: 255. }
- { func_name: image_transpose, bgr2rgb: True, hwc2chw: True }