import os import argparse import subprocess import cv2 import numpy as np import glob import sys # python '.\1_Batch_Gen_All_Depth(跑之前删除结果文件夹).py' # --img-path "./Data" # === 配置区域 === # 两个项目的文件夹名称 img_path = "./Data" V1_FOLDER = "Depth-Anything-V1-main" V2_FOLDER = "Depth-Anything-V2-main" # 定义各自包含的模型列表 V1_ENCODERS = ['vits', 'vitb', 'vitl'] V2_ENCODERS = ['vits', 'vitb', 'vitl', 'vitg'] # ================ def read_image_safe(path): """ [解决中文路径问题] 读取图片 使用 numpy 读取字节流再解码，绕过 cv2.imread 的路径编码 bug """ try: # np.fromfile 读取文件内容到内存 img_array = np.fromfile(path, dtype=np.uint8) # cv2.imdecode 解码内存数据 img = cv2.imdecode(img_array, cv2.IMREAD_COLOR) return img except Exception as e: print(f"Error reading image {path}: {e}") return None def write_image_safe(path, img): """ [解决中文路径问题] 保存图片 使用 cv2.imencode 编码再用 numpy 保存，绕过 cv2.imwrite 的路径编码 bug """ try: # 获取文件扩展名 (例如 .png) ext = os.path.splitext(path)[1] if not ext: ext = ".png" # cv2.imencode 编码图片 success, img_array = cv2.imencode(ext, img) if success: # tofile 保存到文件 img_array.tofile(path) return True else: print(f"Error encoding image for {path}") return False except Exception as e: print(f"Error writing image {path}: {e}") return False def run_inference(repo_path, encoder, img_path_abs, out_dir_abs, grayscale, version_tag): """ 调用各自文件夹下的 run.py 进行推理 注意：如果 run.py 内部也使用了 cv2.imread 且未做中文处理，这里即使传入绝对路径也可能报错。 建议尽量确保 input 路径不含特殊字符，或者修改 run.py 内部源码。 """ if not os.path.exists(repo_path): print(f"Error: Repository folder not found: {repo_path}") return False script_path = "run.py" cmd = [ sys.executable, script_path, '--encoder', encoder, '--img-path', img_path_abs, '--outdir', out_dir_abs, '--pred-only' ] if grayscale: cmd.append('--grayscale') print(f"[{version_tag}] Executing {encoder} (Gray={grayscale})...") try: # cwd=repo_path 是关键 subprocess.check_call(cmd, cwd=repo_path) except subprocess.CalledProcessError as e: print(f"Error executing {version_tag} {encoder}: {e}") return False return True def add_text(img, text, is_header=False): """ 在图片左上角添加文字标注 """ if img is None: return None font = cv2.FONT_HERSHEY_SIMPLEX font_scale = 1.0 if not is_header else 1.2 font_color = (255, 255, 255) thickness = 2 position = (30, 50) cv2.putText(img, text, position, font, font_scale, (0, 0, 0), thickness + 3, cv2.LINE_AA) cv2.putText(img, text, position, font, font_scale, font_color, thickness, cv2.LINE_AA) return img def create_grand_comparison(image_files, root_out_dir, v1_out_base, v2_out_base, mode_suffix, out_subfolder_name): """ 生成超大对比图： 原图 + V1结果 + V2结果 """ compare_dir = os.path.join(root_out_dir, out_subfolder_name) if not os.path.exists(compare_dir): os.makedirs(compare_dir) # makedirs 支持中文路径 print(f"\n--- Generating Grand Comparisons ({out_subfolder_name}) ---") for img_file in image_files: file_basename = os.path.basename(img_file) file_name_no_ext = os.path.splitext(file_basename)[0] # 1. 读取原图 (使用 safe 读取) raw_img = read_image_safe(img_file) if raw_img is None: print(f"Skipping {img_file} due to read error.") continue h, w = raw_img.shape[:2] # 标注原图 raw_img_labeled = raw_img.copy() raw_img_labeled = add_text(raw_img_labeled, "Original", is_header=True) images_to_concat = [raw_img_labeled] # 内部函数：读取并处理深度图 def process_result_img(base_dir, ver_tag, enc_name): target_dir = os.path.join(base_dir, f'{ver_tag}_{enc_name}{mode_suffix}') target_path = os.path.join(target_dir, file_name_no_ext + '.png') # 尝试读取深度图 (使用 safe 读取) d_img = None if os.path.exists(target_path): d_img = read_image_safe(target_path) if d_img is None: # 缺失或读取失败，生成黑色占位图 # print(f"Warning: Missing or failed to read {target_path}") blank = np.zeros((h, w, 3), dtype=np.uint8) return add_text(blank, f"{ver_tag}_{enc_name} (N/A)") # 确保通道数 if len(d_img.shape) == 2: d_img = cv2.cvtColor(d_img, cv2.COLOR_GRAY2BGR) # 强制 Resize 到原图尺寸 if d_img.shape[:2] != (h, w): d_img = cv2.resize(d_img, (w, h), interpolation=cv2.INTER_LINEAR) return add_text(d_img, f"{ver_tag}_{enc_name}") # 2. 收集 V1 结果 for enc in V1_ENCODERS: images_to_concat.append(process_result_img(root_out_dir, "V1", enc)) # 3. 收集 V2 结果 for enc in V2_ENCODERS: images_to_concat.append(process_result_img(root_out_dir, "V2", enc)) # 4. 拼接并保存 try: combined_result = cv2.hconcat(images_to_concat) save_path = os.path.join(compare_dir, f"{file_name_no_ext}_compare.png") # 使用 safe 保存 if write_image_safe(save_path, combined_result): print(f"Saved: {save_path}") else: print(f"Failed to save: {save_path}") except Exception as e: print(f"Error combining images for {file_name_no_ext}: {e}") def main(): parser = argparse.ArgumentParser(description='Universal Depth Anything Batch Process (V1 & V2) - Chinese Path Supported') parser.add_argument('--img-path', type=str, default=img_path, help='Path to input images folder') parser.add_argument('--skip-inference', action='store_true', help='Skip inference, only generate comparison') args = parser.parse_args() # 路径绝对化处理 input_path_abs = os.path.abspath(args.img_path) # 定义总输出目录： 输入文件夹名 + "_Universal_Results" root_folder_name = os.path.basename(os.path.normpath(input_path_abs)) + "_Universal_Results" root_out_abs = os.path.abspath(root_folder_name) if not os.path.exists(root_out_abs): os.makedirs(root_out_abs) print(f"Input: {input_path_abs}") print(f"Output: {root_out_abs}") # ========================== # 1. 运行推理 (Inference) # ========================== # 注意：如果 Depth-Anything 原版 run.py 内部不支持中文路径， # 这里即使调度成功，内部 subprocess 也可能报错。 # 解决方法：确保 run.py 内部也使用了类似 imdecode 的方法，或者仅处理中文路径的对比图生成。 if not args.skip_inference: # --- Run V1 --- for enc in V1_ENCODERS: out_dir = os.path.join(root_out_abs, f'V1_{enc}_gray_result') if not os.path.exists(out_dir): run_inference(V1_FOLDER, enc, input_path_abs, out_dir, True, "V1") out_dir = os.path.join(root_out_abs, f'V1_{enc}_colorful_result') if not os.path.exists(out_dir): run_inference(V1_FOLDER, enc, input_path_abs, out_dir, False, "V1") # --- Run V2 --- for enc in V2_ENCODERS: out_dir = os.path.join(root_out_abs, f'V2_{enc}_gray_result') if not os.path.exists(out_dir): run_inference(V2_FOLDER, enc, input_path_abs, out_dir, True, "V2") out_dir = os.path.join(root_out_abs, f'V2_{enc}_colorful_result') if not os.path.exists(out_dir): run_inference(V2_FOLDER, enc, input_path_abs, out_dir, False, "V2") else: print("Skipping inference step as requested...") # ========================== # 2. 生成对比图 (Comparison) # ========================== # 收集图片列表 (支持 glob 中文路径查找，但在 Windows 下有时需要注意编码) exts = ['*.jpg', '*.jpeg', '*.png', '*.bmp', '*.tif', '*.tiff'] image_files = [] # glob.glob 在较新版本的 Python (3.10+) 中通常能较好处理中文路径 # 如果 glob 找不到文件，请尝试将路径转为 glob.escape(input_path_abs) for ext in exts: image_files.extend(glob.glob(os.path.join(input_path_abs, ext))) # image_files.extend(glob.glob(os.path.join(input_path_abs, '**', ext), recursive=True)) image_files = sorted(list(set(image_files))) if not image_files: print("No images found in input path. (Check if path encoding is correct)") # 调试信息 print(f"Glob pattern used: {os.path.join(input_path_abs, '*.jpg')} etc.") return # 生成灰度大对比 create_grand_comparison( image_files, root_out_abs, "V1", "V2", mode_suffix='_gray_result', out_subfolder_name='Comparison_All_Gray' ) # 生成彩色大对比 create_grand_comparison( image_files, root_out_abs, "V1", "V2", mode_suffix='_colorful_result', out_subfolder_name='Comparison_All_Colorful' ) print(f"\nAll tasks completed. Results stored in: {root_out_abs}") if __name__ == "__main__": main()