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Create config.yaml

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+ # YOLOv9 Configuration File
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+
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+ # Model architecture details
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+ model:
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+ type: YOLOv9 # Model type
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+ backbone:
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+ type: CSPDarknet # Backbone architecture type
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+ depth_multiple: 1.0 # Depth multiplier
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+ width_multiple: 1.0 # Width multiplier
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+
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+ # Input image settings
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+ input_size: 640 # Input image size (square)
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+
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+ # Anchor parameters
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+ anchors:
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+ - [10, 13, 16, 30, 33, 23] # Anchor box 1
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+ - [30, 61, 62, 45, 59, 119] # Anchor box 2
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+ - [116, 90, 156, 198, 373, 326] # Anchor box 3
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+
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+ # Training hyperparameters
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+ hyp:
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+ lr0: 0.01 # Initial learning rate
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+ lrf: 0.01 # Learning rate reduction factor
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+ momentum: 0.937 # Momentum
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+ weight_decay: 0.0005 # Weight decay
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+ warmup_epochs: 3.0 # Warmup epochs
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+ warmup_momentum: 0.8 # Warmup momentum
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+ warmup_bias_lr: 0.1 # Warmup bias learning rate
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+ box: 7.5 # Box loss gain
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+ cls: 0.5 # Class loss gain
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+ cls_pw: 1.0 # Class label smoothing
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+ dfl: 1.5 # DFL loss gain
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+ obj_pw: 1.0 # Objectness loss gain
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+ iou_t: 0.2 # IoU training threshold
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+ anchor_t: 5.0 # Anchor matching threshold
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+ fl_gamma: 0.0 # Focal loss gamma
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+ hsv_h: 0.015 # HSV hue gain
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+ hsv_s: 0.7 # HSV saturation gain
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+ hsv_v: 0.4 # HSV value gain
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+ degrees: 0.0 # Image rotation (degrees)
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+ translate: 0.1 # Image translation
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+ scale: 0.9 # Image scale
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+ shear: 0.0 # Image shear
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+ perspective: 0.0 # Image perspective transform
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+ flipud: 0.0 # Flip image vertically
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+ fliplr: 0.5 # Flip image horizontally
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+ mosaic: 1.0 # Mosaic augmentation
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+ mixup: 0.15 # Mixup augmentation
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+ copy_paste: 0.3 # Copy-Paste augmentation
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+
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+ # Other settings
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+ other:
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+ multi_scale: false # Use multi-scale training
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+ flip: true # Use random horizontal flipping
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+ blur: false # Use random image blurring
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+ letterbox: false # Use letterbox resizing
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+ rect: false # Use rectangular resizing