59 lines
1.6 KiB
YAML
59 lines
1.6 KiB
YAML
train:
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epochs: 2
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batch-size: 400
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cfg: ./cfg/yolov3-spp-18cls.cfg
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data: ./data/widok01-11.data
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multi-scale: false
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img-size: '64 128'
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rect: false
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resume: false
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nosave: false
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notest: false
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evolve: false
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bucket:
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cache-images: false
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weights: /home/tomekb/yolov3/weights/yolov3-spp-ultralytics.pt
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device: 1
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adam: true
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single-cls: false
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# inne hiperparametry
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other-hyps:
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giou: 3.53 # giou loss gain
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cls: 37.4 # cls loss gain
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cls_pw: 1.0 # cls BCELoss positive_weight
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obj: 64.3 # obj loss gain (*=img_size/320 if img_size != 320)
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obj_pw: 1.0 # obj BCELoss positive_weight
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iou_t: 0.20 # iou training threshold
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lr0: 0.01 # initial learning rate (SGD=5E-3 Adam=5E-4)
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lrf: 0.0005 # final learning rate (with cos scheduler)
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momentum: 0.937 # SGD momentum
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weight_decay: 0.0005 # optimizer weight decay
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fl_gamma: 0.0 # focal loss gamma (efficientDet default is gamma=1.5)
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hsv_h: 0.0138 # image HSV-Hue augmentation (fraction)
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hsv_s: 0.678 # image HSV-Saturation augmentation (fraction)
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hsv_v: 0.36 # image HSV-Value augmentation (fraction)
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degrees: 0 # 1.98 * 0 # image rotation (+/- deg)
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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)
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experiments:
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dir: ./experiments
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detect:
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source: /home/michall/yolov3/data/widok01-11_test_labels.txt
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test-img-size: 1024
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conf-thres: 0.3
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iou-thres: 0.6
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save-txt: true
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classes:
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agnostic-nms:
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augment:
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confussion-matrix:
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labels-dir: ./data/widok01-11_labels
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bayes:
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todo: todo
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