# Evaluation Configuration — ROI1
# Same as eval_config_yolov26s-roi0.yaml but evaluates only roi_id="1" detections
# ROI1: narrow crop 768×352, centered on vanishing point (crop_center_mode=vxvy)

dataset:
  det_path: "/data1/dongying/Mono3d/G1Q3/model_inference/KPI/DL_KPI_SCENE/model_20260403"  # Root directory containing case folders with txt_results
  gt_path: "/data1/dongying/Mono3d/G1Q3/dataset_for_evaluation/DL_KPI_SCENE"        # Root directory containing case folders with labels
  path_depth: 1
  det_format: "json"
  gt_format: "json"
  det_subdir: "predictions/roi1"  # Relative to each case directory; used before generic json_results/predictions probing
  det_roi_filter: "1"  # Only evaluate detections with roi_id="1"; set to null to evaluate all ROIs together

# Image properties
image:
  width: 1920
  height: 1080

# Model configuration for GT filtering
model:
  input_size: 768  # Model input width (used for GT min box size calculation)
  min_box_size_at_input_scale: 8
  # GT filtering threshold: min_box_size = 8 * 768 / 768 = 8.0 pixels at original scale (ROI1 is 768×352)

# Performance settings
performance:
  num_workers: 32

# ROI Ground Truth Processing
roi_gt:
  enabled: true
  calib_root: "/data1/dongying/Mono3d/G1Q3/dataset_for_evaluation/DL_KPI_SCENE"  # Root path to calibration files (camera4.json)
  roi_config: [768, 352]   # ROI1 crop size (narrow, centered on VP, crop_center_mode=vxvy)
  roi_bottom_offset: 0

# Class definitions
classes:
  3d_classes: [0, 1, 2, 3, 4, 5, 6, 7, 8]
  2d_classes: [9, 10, 11, 12]
  class_names:
    0: "vehicle"
    1: "bus"
    2: "truck"
    3: "tanker"
    4: "unknown"
    5: "pedestrian"
    6: "bicycle"
    7: "motorcyclist"
    8: "tricycle"
    9: "traffic_sign"
    10: "wheel"
    11: "plate"
    12: "face"

# Matching parameters
matching:
  iou_threshold: 0.5

# 2D metrics configuration
metrics_2d:
  enabled: true
  conf_threshold: 0.27
  ap_method: "voc2010"
  distance_ranges:
    - [0, 30]
    - [30, 60]
    - [60, 100]
    - [100, 999]
  lateral_roi: [-15, 15]

# 3D metrics configuration
metrics_3d:
  enabled: true
  coordinate_system: "camera"
  heading_tolerance: "both"
  distance_ranges:
    - [0, 10]
    - [10, 20]
    - [20, 30]
    - [30, 40]
    - [40, 50]
    - [50, 60]
    - [60, 70]
    - [70, 80]
    - [80, 90]
    - [90, 100]
    - [100, 999]
  lateral_distance_ranges:
    - [-50, -40]
    - [-40, -30]
    - [-30, -20]
    - [-20, -10]
    - [-10, 0]
    - [0, 10]
    - [10, 20]
    - [20, 30]
    - [30, 40]
    - [40, 50]

# Output configuration
output:
  save_path: "eval_results_multiprocess/yolov5s/{timestamp}"
  formats: ["json", "txt"]
  print_details: true
  per_case_reports: true