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68 lines
2.8 KiB
Python
68 lines
2.8 KiB
Python
import os
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import subprocess
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import json
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def process_images_in_folder(image_folder, output_json_file):
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results = [] # 用于存储所有图片的识别结果
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# 使用 os.walk 遍历文件夹及其子文件夹
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for root, dirs, files in os.walk(image_folder):
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for image_file in files:
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# 获取每个图片的完整路径
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temp_image_file = os.path.join(root, image_file)
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# 检查是否为图片文件
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if os.path.splitext(image_file)[-1].lower() in ['.jpg', '.jpeg', '.png', '.gif', '.bmp']:
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# 构造命令，调用 `predict_system_1.py` 进行处理
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command = [
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'python', 'tools/infer/predict_system_1.py',
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'--use_gpu=False',
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'--cls_model_dir=./models/cls',
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'--rec_model_dir=./models/rec',
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'--det_model_dir=./models/det',
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f'--image_dir={temp_image_file}'
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]
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try:
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# 执行命令，指定 UTF-8 编码并捕获输出
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result = subprocess.run(command, capture_output=True, text=True, encoding='utf-8')
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# 检查命令是否成功执行
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if result.returncode == 0:
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ocr_result = result.stdout.strip() # 获取识别结果
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else:
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ocr_result = f"识别失败，返回代码: {result.returncode}"
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# 将结果保存为字典格式，添加到结果列表中
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results.append({
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"图片名称": image_file,
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"文件路径": temp_image_file,
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"识别结果": ocr_result
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})
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except Exception as e:
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# 捕获处理图片时的错误并存储
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results.append({
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"图片名称": image_file,
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"文件路径": temp_image_file,
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"识别结果": f"处理图片时发生错误: {str(e)}"
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})
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# 将结果保存到指定的 JSON 文件
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with open(output_json_file, 'w', encoding='utf-8') as f:
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json.dump(results, f, ensure_ascii=False, indent=4) # 使用 UTF-8 保存 JSON 文件
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print(f"识别结果已保存到 {output_json_file}")
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if __name__ == "__main__":
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# 设置待处理图片所在的文件夹路径
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# image_folder = r"E:\Project\PaddleOcr_v4\contract"
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image_folder = r"E:\Project\PaddleOcr_v4\OCR_LLM_attribute\output_2\MaiMaiHeTong"
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# 设置输出 JSON 文件的路径
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output_json_file = r"E:\Project\PaddleOcr_v4\OCR_LLM_attribute\output_2\MaiMaiHeTong_results.json"
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# 调用函数处理图片并保存结果
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process_images_in_folder(image_folder, output_json_file)
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