#!/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())