Files
yolov26_3d/eval_tools/configs/eval_config_yolov26s-roi1.yaml
2026-06-24 09:35:46 +08:00

106 lines
2.6 KiB
YAML
Executable File
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
# 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