AstroGuard/config.yaml at main · Keshav1605/AstroGuard · GitHub

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# YOLOv8 Configuration for Space Station Object Detection
# Classes: Toolbox, Oxygen Tank, Fire Extinguisher

# Dataset Configuration
path: ./dataset  # Dataset root directory
train: train/images  # Train images (relative to 'path')
val: val/images      # Val images (relative to 'path')
test: test/images    # Test images (relative to 'path')
nc: 3
names: ["Toolbox", "Oxygen Tank", "Fire Extinguisher"]

# Classes
class_names:
  0: Toolbox
  1: Oxygen Tank
  2: Fire Extinguisher

# Model Configuration
model: yolov8n.pt  # Model size: n(nano), s(small), m(medium), l(large), x(xlarge)
epochs: 100
batch_size: 16
imgsz: 640
device: auto  # cuda device, i.e. 0 or 0,1,2,3 or cpu

# Training Hyperparameters
lr0: 0.01  # Initial learning rate
lrf: 0.01  # Final learning rate (lr0 * lrf)
momentum: 0.937
weight_decay: 0.0005
warmup_epochs: 3.0
warmup_momentum: 0.8
warmup_bias_lr: 0.1
box: 7.5  # Box loss gain
cls: 0.5  # Class loss gain
dfl: 1.5  # DFL loss gain
pose: 12.0  # Pose loss gain
kobj: 2.0  # Keypoint obj loss gain
label_smoothing: 0.0  # Label smoothing epsilon
nbs: 64  # Nominal batch size
overlap_mask: True  # Masks should overlap during training (segment train only)
mask_ratio: 4  # Mask downsample ratio (segment train only)
dropout: 0.0  # Use dropout regularization (classify train only)

# Data Augmentation
hsv_h: 0.015  # Image HSV-Hue augmentation (fraction)
hsv_s: 0.7    # Image HSV-Saturation augmentation (fraction)
hsv_v: 0.4    # Image HSV-Value augmentation (fraction)
degrees: 0.0   # Image rotation (+/- deg)
translate: 0.1  # Image translation (+/- fraction)
scale: 0.5     # Image scale (+/- gain)
shear: 0.0     # Image shear (+/- deg)
perspective: 0.0  # Image perspective (+/- fraction), range 0-0.001
flipud: 0.0    # Image flip up-down (probability)
fliplr: 0.5    # Image flip left-right (probability)
mosaic: 1.0    # Image mosaic (probability)
mixup: 0.0     # Image mixup (probability)
copy_paste: 0.0  # Segment copy-paste (probability)

# Validation
val: True  # Validate during training
save_period: -1  # Save checkpoint every x epochs (disabled if < 1)
save_dir: runs/train  # Save results to project/name

# Logging
project: space_station_detection
name: yolov8_training
exist_ok: False
pretrained: True
optimizer: auto
verbose: True
seed: 0
deterministic: True
single_cls: False
rect: False
cos_lr: False
close_mosaic: 10
resume: False
amp: True
fraction: 1.0
cache: False
image_weights: False
multi_scale: False
single_cls: False
optimizer: SGD
sync_bn: False
workers: 8
patience: 50
save: True
save_period: -1
local_rank: -1
entity: null
upload_dataset: False
bbox_interval: -1
artifact_alias: latest
quad: False
cos_lr: False
flat: 1
linear_lr: False
label_smoothing: 0.0
patience: 100
freeze: [0]
save_period: -1
local_rank: -1
entity: null
upload_dataset: False
bbox_interval: -1
artifact_alias: latest