216 lines
4.6 KiB
Python
216 lines
4.6 KiB
Python
#!/usr/bin/env python3
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import argparse
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import glob
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import json
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import os
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import time
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from collections import defaultdict
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# ------------------------------------------------------------
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def load_detection_json(path):
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with open(path, 'r', encoding='utf-8') as f:
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data = json.load(f)
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return data
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# ------------------------------------------------------------
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def find_detection_files(directory, timestamp):
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pattern = os.path.join(
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directory,
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f'*_{timestamp}_aruco_detection.json'
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)
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files = sorted(glob.glob(pattern))
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return files
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# ------------------------------------------------------------
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def build_scene(detection_files, timestamp):
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scene = {
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"schema_version": "1.0",
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"scene_timestamp": str(timestamp),
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"created_utc": time.strftime(
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"%Y-%m-%dT%H:%M:%SZ",
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time.gmtime()
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),
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"cameras": {},
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"markers": {}
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}
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marker_map = defaultdict(list)
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# --------------------------------------------------------
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# Read all camera detection jsons
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# --------------------------------------------------------
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for json_file in detection_files:
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data = load_detection_json(json_file)
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cam = data["camera"]
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img = data["image"]
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basename = os.path.basename(json_file)
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# snapshot_video1_1778819665744_aruco_detection.json
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parts = basename.split('_')
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video_part = parts[1] # "video1"
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camera_id = video_part.replace('video', '')
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# ----------------------------------------------------
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# Camera information
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# ----------------------------------------------------
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scene["cameras"][camera_id] = {
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"camera_id": camera_id,
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"intrinsics_file": cam["intrinsics_file"],
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"camera_matrix": cam["camera_matrix"],
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"distortion_coefficients":
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cam["distortion_coefficients"],
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"image": {
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"image_file": img["image_file"],
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"image_sha256": img["image_sha256"],
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"width_px": img["width_px"],
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"height_px": img["height_px"]
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}
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}
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# ----------------------------------------------------
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# Marker observations
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# ----------------------------------------------------
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for obs in data["observations"]:
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marker_id = str(obs["marker_id"])
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observation = {
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"camera_id": camera_id,
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"center_px": obs["center_px"],
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"corners_px": obs["corners_px"],
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"bbox_px": obs["bbox_px"],
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"quality": obs["quality"]
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}
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marker_map[marker_id].append(observation)
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# --------------------------------------------------------
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# Convert marker map
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# --------------------------------------------------------
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for marker_id, observations in marker_map.items():
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scene["markers"][marker_id] = {
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"marker_id": int(marker_id),
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"num_observations": len(observations),
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"observations": observations
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}
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return scene
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# ------------------------------------------------------------
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument(
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'-timestamp',
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required=True,
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help='Scene timestamp'
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)
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parser.add_argument(
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'-dir',
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default='.',
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help='Directory containing detection json files'
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)
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parser.add_argument(
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'-o',
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'--output',
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default=None
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)
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args = parser.parse_args()
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detection_files = find_detection_files(
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args.dir,
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args.timestamp
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)
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if len(detection_files) == 0:
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raise RuntimeError(
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f'No detection json files found for timestamp '
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f'{args.timestamp}'
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)
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print('Found detection files:')
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for f in detection_files:
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print(' ', f)
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scene = build_scene(
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detection_files,
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args.timestamp
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)
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# --------------------------------------------------------
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# Output filename
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# --------------------------------------------------------
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if args.output is None:
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out_json = os.path.join(
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args.dir,
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f'scene_{args.timestamp}.json'
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)
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else:
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out_json = args.output
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with open(out_json, 'w', encoding='utf-8') as f:
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json.dump(scene, f, indent=2)
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print()
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print(f'Saved scene: {out_json}')
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# ------------------------------------------------------------
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if __name__ == '__main__':
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main() |