car-detection-bayes/our_scripts/config.yml

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train:
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epochs: 200
batch-size: 14 #
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cfg: ./cfg/yolov3-spp-19cls.cfg
data: ./data/widok_01_19.data
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multi-scale: false
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img-size: '768 1280'
rect: false
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resume: false
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nosave: false
notest: false
evolve: false
bucket:
cache-images: false
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weights: /home/tomekb/yolov3/weights/yolov3-spp-ultralytics.pt
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device: 1
adam: true
single-cls: false
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snapshot-every: 50
freeze-layers: true
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# inne hiperparametry
other-hyps:
giou: 3.53 # giou loss gain
cls: 37.4 # cls loss gain
cls_pw: 1.0 # cls BCELoss positive_weight
obj: 64.3 # obj loss gain (*=img_size/320 if img_size != 320)
obj_pw: 1.0 # obj BCELoss positive_weight
iou_t: 0.20 # iou training threshold
lr0: 0.01 # initial learning rate (SGD=5E-3 Adam=5E-4)
lrf: 0.0005 # final learning rate (with cos scheduler)
momentum: 0.937 # SGD momentum
weight_decay: 0.0005 # optimizer weight decay
fl_gamma: 0.0 # focal loss gamma (efficientDet default is gamma=1.5)
hsv_h: 0.0138 # image HSV-Hue augmentation (fraction)
hsv_s: 0.678 # image HSV-Saturation augmentation (fraction)
hsv_v: 0.36 # image HSV-Value augmentation (fraction)
degrees: 0 # 1.98 * 0 # image rotation (+/- deg)
translate: 0 # 0.05 * 0 # image translation (+/- fraction)
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scale: 0 #0 .05 * 0 # image scale (+/- gain)
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shear: 0 # 0.641 * 0 # image shear (+/- deg)
experiments:
dir: ./experiments
detect:
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source: ./data/widok_01_19/widok_01_19_test_labels.txt
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test-img-size: 1024
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conf-thres: 0.3
iou-thres: 0.6
classes:
agnostic-nms:
augment:
confussion-matrix:
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labels-dir: ./data/widok_01_19/widok_01_19_labels
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bayes:
todo: todo