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@@ -16,377 +16,15 @@ from dotenv import load_dotenv
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load_dotenv(override=True)
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from utils import (
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- get_image_files_from_dir,
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- get_image_files_from_list,
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- get_image_files_from_csv,
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collect_pid_files,
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- load_images_from_pdf,
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- normalize_financial_numbers,
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- normalize_markdown_table
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)
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-def convert_pdf_to_images(pdf_file: str, output_dir: str | None = None, dpi: int = 200) -> List[str]:
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- """
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- 将PDF转换为图像文件
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-
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- Args:
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- pdf_file: PDF文件路径
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- output_dir: 输出目录
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- dpi: 图像分辨率
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-
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- Returns:
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- 生成的图像文件路径列表
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- """
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- pdf_path = Path(pdf_file)
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- if not pdf_path.exists() or pdf_path.suffix.lower() != '.pdf':
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- print(f"❌ Invalid PDF file: {pdf_path}")
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- return []
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-
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- # 如果没有指定输出目录,使用PDF同名目录
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- if output_dir is None:
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- output_path = pdf_path.parent / f"{pdf_path.stem}"
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- else:
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- output_path = Path(output_dir) / f"{pdf_path.stem}"
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- output_path = output_path.resolve()
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- output_path.mkdir(parents=True, exist_ok=True)
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-
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- try:
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- # 使用doc_utils中的函数加载PDF图像
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- images = load_images_from_pdf(str(pdf_path), dpi=dpi)
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-
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- image_paths = []
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- for i, image in enumerate(images):
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- # 生成图像文件名
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- image_filename = f"{pdf_path.stem}_page_{i+1:03d}.png"
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- image_path = output_path / image_filename
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-
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- # 保存图像
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- image.save(str(image_path))
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- image_paths.append(str(image_path))
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-
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- print(f"✅ Converted {len(images)} pages from {pdf_path.name} to images")
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- return image_paths
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-
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- except Exception as e:
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- print(f"❌ Error converting PDF {pdf_path}: {e}")
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- traceback.print_exc()
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- return []
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-
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-def get_input_files(args) -> List[str]:
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- """
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- 获取输入文件列表,统一处理PDF和图像文件
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-
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- Args:
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- args: 命令行参数
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-
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- Returns:
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- 处理后的图像文件路径列表
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- """
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- input_files = []
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-
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- # 获取原始输入文件
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- if args.input_csv:
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- raw_files = get_image_files_from_csv(args.input_csv, "fail")
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- elif args.input_file_list:
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- raw_files = get_image_files_from_list(args.input_file_list)
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- elif args.input_file:
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- raw_files = [Path(args.input_file).resolve()]
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- else:
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- input_dir = Path(args.input_dir).resolve()
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- if not input_dir.exists():
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- print(f"❌ Input directory does not exist: {input_dir}")
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- return []
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-
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- # 获取所有支持的文件(图像和PDF)
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- image_extensions = ['.jpg', '.jpeg', '.png', '.bmp', '.tiff', '.tif']
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- pdf_extensions = ['.pdf']
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-
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- raw_files = []
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- for ext in image_extensions + pdf_extensions:
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- raw_files.extend(list(input_dir.glob(f"*{ext}")))
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- raw_files.extend(list(input_dir.glob(f"*{ext.upper()}")))
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-
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- raw_files = [str(f) for f in raw_files]
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-
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- # 分别处理PDF和图像文件
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- pdf_count = 0
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- image_count = 0
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-
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- for file_path in raw_files:
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- file_path = Path(file_path)
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-
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- if file_path.suffix.lower() == '.pdf':
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- # 转换PDF为图像
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- print(f"📄 Processing PDF: {file_path.name}")
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- pdf_images = convert_pdf_to_images(
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- str(file_path),
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- args.output_dir,
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- dpi=args.pdf_dpi
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- )
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- input_files.extend(pdf_images)
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- pdf_count += 1
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- else:
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- # 直接添加图像文件
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- if file_path.exists():
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- input_files.append(str(file_path))
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- image_count += 1
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-
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- print(f"📊 Input summary:")
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- print(f" PDF files processed: {pdf_count}")
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- print(f" Image files found: {image_count}")
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- print(f" Total image files to process: {len(input_files)}")
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-
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- return input_files
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-
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-def convert_api_result_to_json(api_result: Dict[str, Any],
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- input_image_path: str,
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- output_dir: str,
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- filename: str,
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- normalize_numbers: bool = True) -> tuple[str, Dict[str, Any]]:
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- """
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- 将API返回结果转换为标准JSON格式,并支持数字标准化
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- """
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- # 获取主要数据
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- layout_parsing_results = api_result.get('layoutParsingResults', [])
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-
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- if not layout_parsing_results:
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- print("⚠️ Warning: No layoutParsingResults found in API response")
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- return {}
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-
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- # 取第一个结果(通常只有一个)
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- main_result = layout_parsing_results[0]
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- pruned_result = main_result.get('prunedResult', {})
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-
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- # 构造标准格式的JSON
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- converted_json = {
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- "input_path": input_image_path,
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- "page_index": None,
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- "model_settings": pruned_result.get('model_settings', {}),
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- "parsing_res_list": pruned_result.get('parsing_res_list', []),
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- "doc_preprocessor_res": {
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- "input_path": None,
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- "page_index": None,
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- "model_settings": pruned_result.get('doc_preprocessor_res', {}).get('model_settings', {}),
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- "angle": pruned_result.get('doc_preprocessor_res', {}).get('angle', 0)
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- },
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- "layout_det_res": {
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- "input_path": None,
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- "page_index": None,
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- "boxes": pruned_result.get('layout_det_res', {}).get('boxes', [])
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- },
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- "overall_ocr_res": {
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- "input_path": None,
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- "page_index": None,
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- "model_settings": pruned_result.get('overall_ocr_res', {}).get('model_settings', {}),
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- "dt_polys": pruned_result.get('overall_ocr_res', {}).get('dt_polys', []),
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- "text_det_params": pruned_result.get('overall_ocr_res', {}).get('text_det_params', {}),
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- "text_type": pruned_result.get('overall_ocr_res', {}).get('text_type', 'general'),
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- "textline_orientation_angles": pruned_result.get('overall_ocr_res', {}).get('textline_orientation_angles', []),
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- "text_rec_score_thresh": pruned_result.get('overall_ocr_res', {}).get('text_rec_score_thresh', 0.0),
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- "return_word_box": pruned_result.get('overall_ocr_res', {}).get('return_word_box', False),
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- "rec_texts": pruned_result.get('overall_ocr_res', {}).get('rec_texts', []),
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- "rec_scores": pruned_result.get('overall_ocr_res', {}).get('rec_scores', []),
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- "rec_polys": pruned_result.get('overall_ocr_res', {}).get('rec_polys', []),
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- "rec_boxes": pruned_result.get('overall_ocr_res', {}).get('rec_boxes', [])
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- },
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- "table_res_list": pruned_result.get('table_res_list', [])
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- }
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-
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- # 数字标准化处理
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- original_json = converted_json.copy()
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- changes_count = 0
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-
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- if normalize_numbers:
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- # 1. 标准化 parsing_res_list 中的文本内容
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- for item in converted_json.get('parsing_res_list', []):
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- if 'block_content' in item:
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- original_content = item['block_content']
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- normalized_content = original_content
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- # 根据block_label类型选择标准化方法
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- if item.get('block_label') == 'table':
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- normalized_content = normalize_markdown_table(original_content)
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- # else:
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- # normalized_content = normalize_financial_numbers(original_content)
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-
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- if original_content != normalized_content:
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- item['block_content'] = normalized_content
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- changes_count += len([1 for o, n in zip(original_content, normalized_content) if o != n])
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-
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- # 2. 标准化 table_res_list 中的HTML表格
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- for table_item in converted_json.get('table_res_list', []):
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- if 'pred_html' in table_item:
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- original_html = table_item['pred_html']
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- normalized_html = normalize_markdown_table(original_html)
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-
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- if original_html != normalized_html:
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- table_item['pred_html'] = normalized_html
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- changes_count += len([1 for o, n in zip(original_html, normalized_html) if o != n])
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-
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- # 检查是否需要修复表格一致性(这里只做统计,实际修复可能需要更复杂的逻辑)
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- # 统计表格数量
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- parsing_res_tables_count = 0
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- table_res_list_count = 0
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- if 'parsing_res_list' in converted_json:
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- parsing_res_tables_count = len([item for item in converted_json['parsing_res_list']
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- if 'block_label' in item and item['block_label'] == 'table'])
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- if 'table_res_list' in converted_json:
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- table_res_list_count = len(converted_json["table_res_list"])
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- table_consistency_fixed = False
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- if parsing_res_tables_count != table_res_list_count:
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- warnings.warn(f"⚠️ Warning: {filename} Table count mismatch - parsing_res_list has {parsing_res_tables_count} tables, "
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- f"but table_res_list has {table_res_list_count} tables.")
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- table_consistency_fixed = True
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- # 这里可以添加实际的修复逻辑,例如根据需要添加或删除表格项
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- # 但由于缺乏具体规则,暂时只做统计和警告
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-
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- # 3. 标准化 overall_ocr_res 中的识别文本
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- # ocr_res = converted_json.get('overall_ocr_res', {})
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- # if 'rec_texts' in ocr_res:
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- # original_texts = ocr_res['rec_texts'][:]
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- # normalized_texts = []
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-
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- # for text in original_texts:
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- # normalized_text = normalize_financial_numbers(text)
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- # normalized_texts.append(normalized_text)
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- # if text != normalized_text:
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- # changes_count += len([1 for o, n in zip(text, normalized_text) if o != n])
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-
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- # ocr_res['rec_texts'] = normalized_texts
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-
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- # 添加标准化处理信息
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- converted_json['processing_info'] = {
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- "normalize_numbers": normalize_numbers,
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- "changes_applied": changes_count > 0,
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- "character_changes_count": changes_count,
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- "parsing_res_tables_count": parsing_res_tables_count,
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- "table_res_list_count": table_res_list_count,
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- "table_consistency_fixed": table_consistency_fixed
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- }
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-
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- # if changes_count > 0:
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- # print(f"🔧 已标准化 {changes_count} 个字符(全角→半角)")
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- else:
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- converted_json['processing_info'] = {
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- "normalize_numbers": False,
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- "changes_applied": False,
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- "character_changes_count": 0
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- }
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-
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- # 保存JSON文件
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- output_path = Path(output_dir).resolve()
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- output_path.mkdir(parents=True, exist_ok=True)
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-
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- json_file_path = output_path / f"{filename}.json"
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- with open(json_file_path, 'w', encoding='utf-8') as f:
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- json.dump(converted_json, f, ensure_ascii=False, indent=2)
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-
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- # 如果启用了标准化且有变化,保存原始版本用于对比
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- if normalize_numbers and changes_count > 0:
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- original_output_path = output_path / f"{filename}_original.json"
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- with open(original_output_path, 'w', encoding='utf-8') as f:
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- json.dump(original_json, f, ensure_ascii=False, indent=2)
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-
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- return str(output_path), converted_json
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-
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-def save_output_images(api_result: Dict[str, Any], output_dir: str, output_filename: str) -> Dict[str, str]:
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- """
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- 保存API返回的输出图像
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-
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- Args:
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- api_result: API返回的结果
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- output_dir: 输出目录
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-
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- Returns:
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- 保存的图像文件路径字典
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- """
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- layout_parsing_results = api_result.get('layoutParsingResults', [])
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- if not layout_parsing_results:
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- return {}
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-
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- main_result = layout_parsing_results[0]
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- output_images = main_result.get('outputImages', {})
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-
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- output_path = Path(output_dir).resolve()
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- output_path.mkdir(parents=True, exist_ok=True)
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-
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- saved_images = {}
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-
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- for img_name, img_base64 in output_images.items():
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- try:
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- # 解码base64图像
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- img_data = base64.b64decode(img_base64)
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-
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- # 生成文件名
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- img_filename = f"{output_filename}_{img_name}.jpg"
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- img_path = output_path / img_filename
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-
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- # 保存图像
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- with open(img_path, 'wb') as f:
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- f.write(img_data)
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-
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- saved_images[img_name] = str(img_path)
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- # print(f"📷 Saved image: {img_path}")
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-
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- except Exception as e:
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- print(f"❌ Error saving image {img_name}: {e}")
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-
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- return saved_images
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-
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-def save_markdown_content(api_result: Dict[str, Any], output_dir: str,
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- filename: str, normalize_numbers: bool = True) -> str:
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- """
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- 保存Markdown内容,支持数字标准化
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- """
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- layout_parsing_results = api_result.get('layoutParsingResults', [])
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- if not layout_parsing_results:
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- return ""
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-
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- main_result = layout_parsing_results[0]
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- markdown_data = main_result.get('markdown', {})
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-
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- output_path = Path(output_dir).resolve()
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- output_path.mkdir(parents=True, exist_ok=True)
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-
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- # 保存Markdown文本
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- markdown_text = markdown_data.get('text', '')
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-
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- # 数字标准化处理
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- changes_count = 0
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- if normalize_numbers and markdown_text:
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- original_markdown_text = markdown_text
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- markdown_text = normalize_markdown_table(markdown_text)
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-
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- changes_count = len([1 for o, n in zip(original_markdown_text, markdown_text) if o != n])
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- # if changes_count > 0:
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- # print(f"🔧 Markdown中已标准化 {changes_count} 个字符(全角→半角)")
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-
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- md_file_path = output_path / f"{filename}.md"
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- with open(md_file_path, 'w', encoding='utf-8') as f:
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- f.write(markdown_text)
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-
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- # 如果启用了标准化且有变化,保存原始版本用于对比
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- if normalize_numbers and changes_count > 0:
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- original_output_path = output_path / f"{filename}_original.md"
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- with open(original_output_path, 'w', encoding='utf-8') as f:
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- f.write(original_markdown_text)
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-
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- # 保存Markdown中的图像
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- markdown_images = markdown_data.get('images', {})
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- for img_path, img_base64 in markdown_images.items():
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- try:
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- img_data = base64.b64decode(img_base64)
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- full_img_path = output_path / img_path
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- full_img_path.parent.mkdir(parents=True, exist_ok=True)
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-
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- with open(full_img_path, 'wb') as f:
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- f.write(img_data)
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-
|
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- # print(f"🖼️ Saved Markdown image: {full_img_path}")
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-
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- except Exception as e:
|
|
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- print(f"❌ Error saving Markdown image {img_path}: {e}")
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-
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- return str(md_file_path)
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+from ppstructurev3_utils import (
|
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+ get_input_files,
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+ convert_pruned_result_to_json,
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+ save_output_images,
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+ save_markdown_content
|
|
|
+)
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def call_api_for_image(image_path: str, api_url: str, timeout: int = 300) -> Dict[str, Any]:
|
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|
"""
|
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|
@@ -474,53 +112,67 @@ def process_images_via_api(image_paths: List[str],
|
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api_result = call_api_for_image(img_path, api_url, timeout)
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|
processing_time = time.time() - start_time
|
|
|
|
|
|
+ # 获取主要数据
|
|
|
+ layout_parsing_results = api_result.get('layoutParsingResults', [])
|
|
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+
|
|
|
+ if not layout_parsing_results:
|
|
|
+ print("⚠️ Warning: No layoutParsingResults found in API response")
|
|
|
+ return []
|
|
|
+
|
|
|
# 处理API返回结果
|
|
|
input_path = Path(img_path)
|
|
|
|
|
|
# 生成输出文件名
|
|
|
output_filename = input_path.stem
|
|
|
-
|
|
|
- # 转换并保存标准JSON格式
|
|
|
- json_output_path, converted_json = convert_api_result_to_json(
|
|
|
- api_result,
|
|
|
- str(input_path),
|
|
|
- output_dir,
|
|
|
- output_filename,
|
|
|
- normalize_numbers=normalize_numbers
|
|
|
- )
|
|
|
|
|
|
- # 保存输出图像
|
|
|
- saved_images = save_output_images(api_result, str(output_dir), output_filename)
|
|
|
+ # 处理结果
|
|
|
+ for idx, result in enumerate(layout_parsing_results):
|
|
|
+ if idx > 0:
|
|
|
+ raise ValueError("Multiple results found for a single image")
|
|
|
+
|
|
|
+ json_content = result.get('prunedResult', {})
|
|
|
+ json_output_path, converted_json = convert_pruned_result_to_json(
|
|
|
+ json_content,
|
|
|
+ str(input_path),
|
|
|
+ output_dir,
|
|
|
+ output_filename,
|
|
|
+ normalize_numbers=normalize_numbers
|
|
|
+ )
|
|
|
|
|
|
- # 保存Markdown内容
|
|
|
- md_output_path = save_markdown_content(
|
|
|
- api_result,
|
|
|
- output_dir,
|
|
|
- output_filename,
|
|
|
- normalize_numbers=normalize_numbers
|
|
|
- )
|
|
|
-
|
|
|
- # 记录处理结果
|
|
|
- all_results.append({
|
|
|
- "image_path": str(input_path),
|
|
|
- "processing_time": processing_time,
|
|
|
- "success": True,
|
|
|
- "api_url": api_url,
|
|
|
- "output_json": json_output_path,
|
|
|
- "output_md": md_output_path,
|
|
|
- "is_pdf_page": "_page_" in input_path.name, # 标记是否为PDF页面
|
|
|
- "processing_info": converted_json.get('processing_info', {})
|
|
|
- })
|
|
|
-
|
|
|
- # 更新进度条
|
|
|
- success_count = sum(1 for r in all_results if r.get('success', False))
|
|
|
-
|
|
|
- pbar.update(1)
|
|
|
- pbar.set_postfix({
|
|
|
- 'time': f"{processing_time:.2f}s",
|
|
|
- 'success': f"{success_count}/{len(all_results)}",
|
|
|
- 'rate': f"{success_count/len(all_results)*100:.1f}%"
|
|
|
- })
|
|
|
+ # 保存输出图像
|
|
|
+ img_content = result.get('outputImages', {})
|
|
|
+ saved_images = save_output_images(img_content, str(output_dir), output_filename)
|
|
|
+
|
|
|
+ # 保存Markdown内容
|
|
|
+ markdown_content = result.get('markdown', {})
|
|
|
+ md_output_path = save_markdown_content(
|
|
|
+ markdown_content,
|
|
|
+ output_dir,
|
|
|
+ output_filename,
|
|
|
+ normalize_numbers=normalize_numbers
|
|
|
+ )
|
|
|
+
|
|
|
+ # 记录处理结果
|
|
|
+ all_results.append({
|
|
|
+ "image_path": str(input_path),
|
|
|
+ "processing_time": processing_time,
|
|
|
+ "success": True,
|
|
|
+ "api_url": api_url,
|
|
|
+ "output_json": json_output_path,
|
|
|
+ "output_md": md_output_path,
|
|
|
+ "is_pdf_page": "_page_" in input_path.name, # 标记是否为PDF页面
|
|
|
+ "processing_info": converted_json.get('processing_info', {})
|
|
|
+ })
|
|
|
+
|
|
|
+ # 更新进度条
|
|
|
+ success_count = sum(1 for r in all_results if r.get('success', False))
|
|
|
+
|
|
|
+ pbar.update(1)
|
|
|
+ pbar.set_postfix({
|
|
|
+ 'time': f"{processing_time:.2f}s",
|
|
|
+ 'success': f"{success_count}/{len(all_results)}",
|
|
|
+ 'rate': f"{success_count/len(all_results)*100:.1f}%"
|
|
|
+ })
|
|
|
|
|
|
except Exception as e:
|
|
|
print(f"Error processing {Path(img_path).name}: {e}", file=sys.stderr)
|
|
|
@@ -676,12 +328,16 @@ if __name__ == "__main__":
|
|
|
|
|
|
# 默认配置
|
|
|
default_config = {
|
|
|
- "input_file": "/Users/zhch158/workspace/data/至远彩色印刷工业有限公司/data_PPStructureV3_Results/2023年度报告母公司/2023年度报告母公司_page_027.png",
|
|
|
+ # "input_file": "/Users/zhch158/workspace/data/至远彩色印刷工业有限公司/data_PPStructureV3_Results/2023年度报告母公司/2023年度报告母公司_page_027.png",
|
|
|
+ # "input_file": "/home/ubuntu/zhch/data/至远彩色印刷工业有限公司/PPStructureV3_Results/2023年度报告母公司/2023年度报告母公司_page_027.png",
|
|
|
+ "input_file": "/home/ubuntu/zhch/data/至远彩色印刷工业有限公司/2023年度报告母公司.pdf",
|
|
|
+ "output_dir": "/home/ubuntu/zhch/data/至远彩色印刷工业有限公司/PPStructureV3_Results",
|
|
|
+ "collect_results": f"/home/ubuntu/zhch/data/至远彩色印刷工业有限公司/PPStructureV3_Results/processed_files_{time.strftime('%Y%m%d_%H%M%S')}.csv",
|
|
|
# "input_dir": "../../OmniDocBench/OpenDataLab___OmniDocBench/images",
|
|
|
- "output_dir": "./OmniDocBench_API_Results",
|
|
|
+ # "output_dir": "./OmniDocBench_API_Results",
|
|
|
+ # "collect_results": f"./OmniDocBench_API_Results/processed_files_{time.strftime('%Y%m%d_%H%M%S')}.csv",
|
|
|
"api_url": "http://10.192.72.11:8111/layout-parsing",
|
|
|
"timeout": "300",
|
|
|
- "collect_results": f"./OmniDocBench_API_Results/processed_files_{time.strftime('%Y%m%d_%H%M%S')}.csv",
|
|
|
}
|
|
|
|
|
|
# 构造参数
|