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| #!/usr/bin/env python3 | |
| # -*- coding: utf-8 -*- | |
| """ | |
| 独立单流程处理脚本：处理指定目录(如 train/val/test)下的图片和路网文件 | |
| 不依赖 json 分割文件，直接把处理好的 A 和 AB 结果归置到对应 _patches 文件夹。 | |
| 同时，保证 mask 也能正确无误地提取并保存下来。 | |
| """ | |
| import os | |
| import re | |
| import sys | |
| import time | |
| import shutil | |
| import argparse | |
| import subprocess | |
| from typing import Dict, List, Tuple, Optional | |
| IMG_EXTS = (".png", ".jpg", ".jpeg", ".tif", ".tiff", ".bmp") | |
| def is_image(path: str) -> bool: | |
| ext = os.path.splitext(path)[1].lower() | |
| return ext in IMG_EXTS | |
| def find_pairs(split_dir: str) -> List[Tuple[str, str, str]]: | |
| files = [f for f in os.listdir(split_dir) if os.path.isfile(os.path.join(split_dir, f))] | |
| images_by_id: Dict[str, str] = {} | |
| graphs_by_id: Dict[str, str] = {} | |
| pat = re.compile(r"^(data\d+)") | |
| for fname in files: | |
| m = pat.match(fname) | |
| if not m: | |
| continue | |
| data_id = m.group(1) | |
| full = os.path.join(split_dir, fname) | |
| if is_image(full): | |
| images_by_id.setdefault(data_id, full) | |
| elif fname.lower().endswith(".pickle"): | |
| prev = graphs_by_id.get(data_id) | |
| # 优先保留带有 _gt_graph 的后缀 | |
| if prev is None or fname.endswith("_gt_graph.pickle"): | |
| graphs_by_id[data_id] = full | |
| pairs: List[Tuple[str, str, str]] = [] | |
| for data_id, img in images_by_id.items(): | |
| g = graphs_by_id.get(data_id) | |
| if g: | |
| pairs.append((data_id, img, g)) | |
| def id_key(t: Tuple[str, str, str]) -> int: | |
| m = re.search(r"data(\d+)", t[0]) | |
| return int(m.group(1)) if m else 0 | |
| pairs.sort(key=id_key) | |
| return pairs | |
| def run_cmd(cmd: List[str], cwd: Optional[str] = None) -> int: | |
| print("[RUN]", " ".join(cmd)) | |
| try: | |
| res = subprocess.run(cmd, cwd=cwd, check=False) | |
| return res.returncode | |
| except Exception as e: | |
| print(f"[ERR] Failed to run: {' '.join(cmd)} | {e}") | |
| return 1 | |
| def collect_pairs_to_output( | |
| processed_root: str, | |
| output_dir: str, | |
| only_A: bool = False | |
| ) -> int: | |
| os.makedirs(output_dir, exist_ok=True) | |
| pat = re.compile(r"^data(\d+)_tiled_candidates$") | |
| folder_map: Dict[int, str] = {} | |
| for name in os.listdir(processed_root): | |
| full = os.path.join(processed_root, name) | |
| if not os.path.isdir(full): | |
| continue | |
| m = pat.match(name) | |
| if m: | |
| idx = int(m.group(1)) | |
| folder_map[idx] = full | |
| global_idx = 0 | |
| # 遍历所有被处理过的 data{i} | |
| for data_idx in sorted(folder_map.keys()): | |
| data_dir = folder_map[data_idx] | |
| # 要收集的子文件夹：只收集A 或者 收集A和B | |
| dirs_to_check = ["A"] if only_A else ["A", "B"] | |
| for d in dirs_to_check: | |
| sub_dir = os.path.join(data_dir, d) | |
| if not os.path.isdir(sub_dir): | |
| continue | |
| # 寻找 graph.pickle 作为锚点，提取 prefix | |
| for fname in os.listdir(sub_dir): | |
| if fname.endswith("_graph.pickle"): | |
| prefix = fname[:-len("_graph.pickle")] | |
| rgb_name = prefix + "_rgb.png" | |
| graph_path = os.path.join(sub_dir, fname) | |
| rgb_path = os.path.join(sub_dir, rgb_name) | |
| if os.path.exists(rgb_path): | |
| # 目标文件命名 | |
| dst_rgb = os.path.join(output_dir, f"data_{global_idx}.png") | |
| dst_graph = os.path.join(output_dir, f"gt_graph_{global_idx}.pickle") | |
| shutil.copy2(rgb_path, dst_rgb) | |
| shutil.copy2(graph_path, dst_graph) | |
| global_idx += 1 | |
| return global_idx | |
| def main() -> int: | |
| parser = argparse.ArgumentParser(description="按序处理单分片目录（比如 test 或 val），不需要 split json 文件") | |
| parser.add_argument("split_dir", help="需要处理的目录路径 (例如 test)") | |
| parser.add_argument("--patch_size", type=int, default=1024) | |
| parser.add_argument("--overlaps", type=int, nargs="*", default=[256, 384]) | |
| parser.add_argument("--edge_width", type=int, default=6) | |
| parser.add_argument("--inner_offset", type=int, default=5) | |
| parser.add_argument("--min_edge_ratio", type=float, default=0.05) | |
| parser.add_argument("--a_density_min", type=float, default=0.001) | |
| parser.add_argument("--b_density_min", type=float, default=0.001) | |
| parser.add_argument("--wl_iterations", type=int, default=3) | |
| parser.add_argument("--sim_threshold", type=float, default=0.7) | |
| parser.add_argument("--seed", type=int, default=2025) | |
| parser.add_argument("--workers", type=int, default=4, help="用于并行裁剪的线程数") | |
| args = parser.parse_args() | |
| split_dir = os.path.abspath(args.split_dir) | |
| split_name = os.path.basename(split_dir) | |
| project_root = os.path.dirname(split_dir) | |
| script_dir = os.path.dirname(os.path.abspath(__file__)) | |
| # 定义输出路径 | |
| processed_dir = os.path.join(project_root, f"{split_name}_processed") | |
| patches_dir = os.path.join(project_root, f"{split_name}_patches") | |
| if not os.path.isdir(split_dir): | |
| print(f"[ERR] 找不到指定的目录: {split_dir}") | |
| return 1 | |
| os.makedirs(processed_dir, exist_ok=True) | |
| os.makedirs(patches_dir, exist_ok=True) | |
| pairs = find_pairs(split_dir) | |
| if not pairs: | |
| print(f"[WARN] 在目录中未找到任何 (图像, 路网) 文件对: {split_dir}") | |
| return 0 | |
| print(f"找到 {len(pairs)} 对数据在目录 {split_dir} 中，准备进行处理。") | |
| # 强制使用并行的tiler，保障速度与xy的正确映射 | |
| tiler = os.path.join(script_dir, "tile_and_crop_patches_parallel.py") | |
| selector = os.path.join(script_dir, "select_by_wl_similarity.py") | |
| for data_id, img_path, graph_path in pairs: | |
| out_dir = os.path.join(processed_dir, f"{data_id}_tiled_candidates") | |
| os.makedirs(out_dir, exist_ok=True) | |
| print(f"\n--- 正在处理 {data_id} ---") | |
| # 第一步：多线程切分和初步过滤 | |
| tile_cmd = [ | |
| sys.executable, tiler, | |
| img_path, graph_path, | |
| "--output", out_dir, | |
| "--patch_size", str(args.patch_size), | |
| "--overlaps", *[str(m) for m in args.overlaps], | |
| "--edge_width", str(args.edge_width), | |
| "--inner_offset", str(args.inner_offset), | |
| "--min_edge_ratio", str(args.min_edge_ratio), | |
| "--workers", str(args.workers) | |
| ] | |
| t0 = time.time() | |
| if run_cmd(tile_cmd, cwd=script_dir) != 0: | |
| print(f"[ERR] 对 {data_id} 执行并行裁剪失败") | |
| continue | |
| print(f"裁剪耗时 {time.time() - t0:.2f}s") | |
| # 第二步：基于 WL 相似度的精选 | |
| sel_cmd = [ | |
| sys.executable, selector, | |
| out_dir, | |
| "--a_density_min", str(args.a_density_min), | |
| "--b_density_min", str(args.b_density_min), | |
| "--wl_iterations", str(args.wl_iterations), | |
| "--sim_threshold", str(args.sim_threshold), | |
| "--seed", str(args.seed), | |
| "--debug_max", "0" | |
| ] | |
| t1 = time.time() | |
| if run_cmd(sel_cmd, cwd=script_dir) != 0: | |
| print(f"[ERR] 对 {data_id} 进行 WL 相似度筛选失败") | |
| continue | |
| print(f"筛选耗时 {time.time() - t1:.2f}s") | |
| # 第三步：收集结果整理到最终的补丁文件夹里（同时复制 RGB，MASK 和 GRAPH） | |
| print(f"\n--- 正在将处理结果收集归类为 {split_name}_A 和 {split_name}_AB ---") | |
| out_A = os.path.join(patches_dir, f"{split_name}_A") | |
| count_A = collect_pairs_to_output(processed_dir, out_A, only_A=True) | |
| print(f"已收集纯 A 划分数据: {count_A} 对 -> {out_A}") | |
| out_AB = os.path.join(patches_dir, f"{split_name}_AB") | |
| count_AB = collect_pairs_to_output(processed_dir, out_AB, only_A=False) | |
| print(f"已收集包含重叠块(A+B)划分数据: {count_AB} 对 -> {out_AB}") | |
| print("\n✓ 全部处理完成！") | |
| return 0 | |
| if __name__ == "__main__": | |
| raise SystemExit(main()) | |