Initial media depth project backup
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213
Depth-Anything-V2-main/batch_process_and_compare_V2.py
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213
Depth-Anything-V2-main/batch_process_and_compare_V2.py
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import os
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import argparse
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import subprocess
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import cv2
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import numpy as np
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import glob
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import sys
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def read_image_safe(path):
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"""
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[解决中文路径问题] 读取图片
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使用 numpy 读取字节流再解码，绕过 cv2.imread 的路径编码 bug
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"""
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try:
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# np.fromfile 读取文件内容到内存
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img_array = np.fromfile(path, dtype=np.uint8)
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# cv2.imdecode 解码内存数据
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img = cv2.imdecode(img_array, cv2.IMREAD_COLOR)
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return img
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except Exception as e:
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print(f"Error reading image {path}: {e}")
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return None
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def write_image_safe(path, img):
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"""
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[解决中文路径问题] 保存图片
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使用 cv2.imencode 编码再用 numpy 保存，绕过 cv2.imwrite 的路径编码 bug
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"""
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try:
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# 获取文件扩展名 (例如 .png)
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ext = os.path.splitext(path)[1]
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if not ext:
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ext = ".png"
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# cv2.imencode 编码图片
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success, img_array = cv2.imencode(ext, img)
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if success:
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# tofile 保存到文件
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img_array.tofile(path)
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return True
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else:
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print(f"Error encoding image for {path}")
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return False
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except Exception as e:
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print(f"Error writing image {path}: {e}")
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return False
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def run_encoder(encoder, img_path, out_dir, grayscale):
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"""
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调用 run.py 生成指定 encoder 的深度图
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"""
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cmd = [
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sys.executable, 'run.py',
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'--encoder', encoder,
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'--img-path', img_path,
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'--outdir', out_dir,
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'--pred-only'
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]
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if grayscale:
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cmd.append('--grayscale')
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print(f"Executing: {' '.join(cmd)}")
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try:
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subprocess.check_call(cmd)
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except subprocess.CalledProcessError as e:
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print(f"Error occurred while running {encoder} (Gray={grayscale}): {e}")
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return False
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return True
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def add_text(img, text):
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"""
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在图片左上角添加文字标注
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"""
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font = cv2.FONT_HERSHEY_SIMPLEX
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font_scale = 1.0
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font_color = (255, 255, 255)
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thickness = 2
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position = (30, 50)
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cv2.putText(img, text, position, font, font_scale, (0, 0, 0), thickness + 3, cv2.LINE_AA)
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cv2.putText(img, text, position, font, font_scale, font_color, thickness, cv2.LINE_AA)
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return img
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def create_comparison(image_files, folder_name, encoders, mode_suffix, out_folder_name):
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"""
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生成对比图的核心逻辑
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"""
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compare_dir = os.path.join(folder_name, out_folder_name)
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os.makedirs(compare_dir, exist_ok=True)
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print(f"\n--- Generating Comparisons ({out_folder_name}) -> {compare_dir} ---")
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for img_file in image_files:
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file_basename = os.path.basename(img_file)
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file_name_no_ext = os.path.splitext(file_basename)[0]
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# 1. 读取原图
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raw_img = read_image_safe(img_file)
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if raw_img is None:
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continue
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# 获取原图尺寸 (高度, 宽度)
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h, w = raw_img.shape[:2]
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# 标注原图
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raw_img_labeled = raw_img.copy()
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raw_img_labeled = add_text(raw_img_labeled, "Original")
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images_to_concat = [raw_img_labeled]
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valid_group = True
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# 2. 依次读取 4 个 encoder 的结果
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for encoder in encoders:
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result_dir = os.path.join(folder_name, f'V2_{encoder}{mode_suffix}')
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result_path = os.path.join(result_dir, file_name_no_ext + '.png')
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if not os.path.exists(result_path):
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print(f"Missing result for {file_basename} in {encoder}, skipping.")
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valid_group = False
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break
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depth_img = read_image_safe(result_path)
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if depth_img is None:
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print(f"Failed to read {result_path}, skipping.")
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valid_group = False
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break
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# 确保通道数正确 (转为3通道以便拼接)
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if len(depth_img.shape) == 2:
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depth_img = cv2.cvtColor(depth_img, cv2.COLOR_GRAY2BGR)
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# --- 关键修改：强制 Resize 到原图尺寸 ---
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# 无论原始输出尺寸如何，都强制缩放为 (w, h)
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if depth_img.shape[:2] != (h, w):
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depth_img = cv2.resize(depth_img, (w, h), interpolation=cv2.INTER_LINEAR)
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# 标注文字
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label = f"Depth_Anything_V2_{encoder}"
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depth_img = add_text(depth_img, label)
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images_to_concat.append(depth_img)
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if valid_group:
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# 水平拼接
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try:
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combined_result = cv2.hconcat(images_to_concat)
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# 保存
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save_path = os.path.join(compare_dir, f"{file_name_no_ext}_compare.png")
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if write_image_safe(save_path, combined_result):
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print(f"Saved: {save_path}")
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else:
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print(f"Failed to save: {save_path}")
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except Exception as e:
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print(f"Error combining images for {file_name_no_ext}: {e}")
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def main():
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parser = argparse.ArgumentParser(description='Batch process depth estimation (Gray & Color) and compare.')
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parser.add_argument('--img-path', type=str, required=True, help='Path to input images folder')
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args = parser.parse_args()
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# 1. 确定根目录名称: 输入文件夹名 + "_results"
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folder_name = os.path.basename(os.path.normpath(args.img_path)) + "_results"
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encoders = ['vits', 'vitb', 'vitl', 'vitg']
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# 2. 批量生成深度图 (Run Inference)
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for encoder in encoders:
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# A. 灰度图
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gray_out_dir = os.path.join(folder_name, f'V2_{encoder}_gray_result')
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if not os.path.exists(gray_out_dir):
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run_encoder(encoder, args.img_path, gray_out_dir, grayscale=True)
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# B. 彩色图
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color_out_dir = os.path.join(folder_name, f'V2_{encoder}_colorful_result')
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if not os.path.exists(color_out_dir):
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run_encoder(encoder, args.img_path, color_out_dir, grayscale=False)
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# 3. 准备原图列表
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exts = ['*.jpg', '*.jpeg', '*.png', '*.bmp', '*.tif', '*.tiff']
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image_files = []
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for ext in exts:
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image_files.extend(glob.glob(os.path.join(args.img_path, ext)))
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image_files.extend(glob.glob(os.path.join(args.img_path, '**', ext), recursive=True))
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image_files = sorted(list(set(image_files)))
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if not image_files:
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print("No images found in input path.")
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return
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# 4. 生成灰度对比图
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create_comparison(
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image_files=image_files,
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folder_name=folder_name,
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encoders=encoders,
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mode_suffix='_gray_result',
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out_folder_name='compare_all_gray'
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)
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# 5. 生成彩色对比图
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create_comparison(
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image_files=image_files,
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folder_name=folder_name,
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encoders=encoders,
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mode_suffix='_colorful_result',
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out_folder_name='compare_all_colorful'
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)
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print(f"\nAll done! Results are in: {folder_name}")
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if __name__ == "__main__":
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main()
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