# YOLO-Assisted Annotator Configuration
# Use pretrained YOLOv9t to auto-annotate video frames

model:
  path: "models/yolov9t.pt"          # Path to YOLO model (.pt, .onnx, or .rknn)
  device: "cuda"                      # cuda, cpu, or rknn
  conf_threshold: 0.25                # Confidence threshold
  iou_threshold: 0.45                 # NMS IoU threshold

video:
  source: "input/video.mp4"           # Video file path
  sample_fps: 2                       # Frames per second to extract
  max_frames: null                    # Max frames (null = all)
  start_time: 0                       # Start time in seconds
  end_time: null                      # End time (null = end of video)
  resize: null                        # [width, height] or null

detection:
  classes: null                       # Class IDs to keep (null = all), e.g. [0, 2, 5]
  min_confidence: 0.3                 # Minimum confidence to save
  min_area: 100                       # Minimum bbox area in pixels
  max_area: null                      # Maximum bbox area (null = no limit)
  min_size: 0.01                      # Minimum bbox dimension (normalized 0-1)

output:
  directory: "output/annotations"     # Output directory
  save_snapshots: true                # Save clean images (no boxes)
  save_labels: true                   # Save YOLO format labels
  save_debug: true                    # Save debug visualizations (with boxes)
  save_manifest: true                 # Save JSON manifest
  image_format: "jpg"                 # jpg or png
  image_quality: 95                   # JPEG quality (1-100)

# Class name mapping (COCO classes for pretrained model)
class_names:
  0: person
  1: bicycle
  2: car
  3: motorcycle
  4: airplane
  5: bus
  6: train
  7: truck
  8: boat
  9: traffic light
  10: fire hydrant
  11: stop sign
  12: parking meter
  13: bench
  14: bird
  15: cat
  16: dog
  17: horse
  18: sheep
  19: cow
  20: elephant
  21: bear
  22: zebra
  23: giraffe
  24: backpack
  25: umbrella
  26: handbag
  27: tie
  28: suitcase
  29: frisbee
  30: skis
  31: snowboard
  32: sports ball
  33: kite
  34: baseball bat
  35: baseball glove
  36: skateboard
  37: surfboard
  38: tennis racket
  39: bottle
  40: wine glass
  41: cup
  42: fork
  43: knife
  44: spoon
  45: bowl
  46: banana
  47: apple
  48: sandwich
  49: orange
  50: broccoli
  51: carrot
  52: hot dog
  53: pizza
  54: donut
  55: cake
  56: chair
  57: couch
  58: potted plant
  59: bed
  60: dining table
  61: toilet
  62: tv
  63: laptop
  64: mouse
  65: remote
  66: keyboard
  67: cell phone
  68: microwave
  69: oven
  70: toaster
  71: sink
  72: refrigerator
  73: book
  74: clock
  75: vase
  76: scissors
  77: teddy bear
  78: hair drier
  79: toothbrush