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