Chengfang Lu
e72bc061c5
Major changes: - New frontend (platform/web/): Vite + React 18 + TypeScript + Tailwind - 4-module navigation: 数据送标 / 模型管理 / 车队管理 / 系统管理 - Data catalog with charts (DMS/ADAS/Lane 3-tab view) - Quality review workflow (标注质检): Good/Fine/Bad scoring with auto-advance - Audit enhancements: batch operations, rejection categories, Feishu notifications - Operation audit log (操作日志) - World model simulation studio (仿真工坊) - Dataset version management with snapshots and diff - ADAS 7-class dataset integration (138K images organized + compressed) - User management with Feishu integration and pagination - CRUD/search/filter on all pages, card layout redesign - PIL-optimized image overlay rendering - Auto-snapshot on build, in_review workflow stage - Removed embedded algorithm code (now in workspace)
67 lines
2.0 KiB
Python
67 lines
2.0 KiB
Python
"""Visualize TuSimple-format predictions from test.py (tusimple_eval_tmp.0.txt)."""
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import argparse
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import json
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import os
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import cv2
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LANE_COLORS = [(0, 255, 0), (0, 0, 255), (255, 0, 0), (0, 255, 255)]
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def draw_lanes(img, lanes, h_samples):
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for lane_idx, xs in enumerate(lanes):
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color = LANE_COLORS[lane_idx % len(LANE_COLORS)]
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pts = [(int(x), int(y)) for x, y in zip(xs, h_samples) if x >= 0]
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for i in range(len(pts) - 1):
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cv2.line(img, pts[i], pts[i + 1], color, 3)
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for p in pts:
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cv2.circle(img, p, 4, color, -1)
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def main():
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parser = argparse.ArgumentParser()
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parser.add_argument(
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'--pred',
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default='tmp/tusimple_eval_tmp.0.txt',
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help='prediction jsonl from test.py',
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)
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parser.add_argument(
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'--data_root',
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default='/home/chengfanglu/DATA/lane0_copy/DATASET',
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help='dataset root (images under data_root/raw_file)',
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)
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parser.add_argument(
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'--out_dir',
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default='tmp/vis_pred',
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help='directory to save overlay images',
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)
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args = parser.parse_args()
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os.makedirs(args.out_dir, exist_ok=True)
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n_ok = 0
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with open(args.pred, 'r') as f:
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for line in f:
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item = json.loads(line)
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rel = item['raw_file']
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img_path = os.path.join(args.data_root, rel)
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if not os.path.isfile(img_path):
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print('skip (missing):', img_path)
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continue
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img = cv2.imread(img_path)
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if img is None:
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print('skip (read failed):', img_path)
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continue
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draw_lanes(img, item['lanes'], item['h_samples'])
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out_path = os.path.join(args.out_dir, rel)
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os.makedirs(os.path.dirname(out_path), exist_ok=True)
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cv2.imwrite(out_path, img)
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n_ok += 1
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print('saved', out_path)
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print(f'done: {n_ok} images -> {args.out_dir}')
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if __name__ == '__main__':
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main()
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