Merge branch 'dev' into multi_gpu_v2

mineru/utils/cli_parser.py

+import click
+
+
+def arg_parse(ctx: 'click.Context') -> dict:
+    # 解析额外参数
+    extra_kwargs = {}
+    i = 0
+    while i < len(ctx.args):
+        arg = ctx.args[i]
+        if arg.startswith('--'):
+            param_name = arg[2:].replace('-', '_')  # 转换参数名格式
+            i += 1
+            if i < len(ctx.args) and not ctx.args[i].startswith('--'):
+                # 参数有值
+                try:
+                    # 尝试转换为适当的类型
+                    if ctx.args[i].lower() == 'true':
+                        extra_kwargs[param_name] = True
+                    elif ctx.args[i].lower() == 'false':
+                        extra_kwargs[param_name] = False
+                    elif '.' in ctx.args[i]:
+                        try:
+                            extra_kwargs[param_name] = float(ctx.args[i])
+                        except ValueError:
+                            extra_kwargs[param_name] = ctx.args[i]
+                    else:
+                        try:
+                            extra_kwargs[param_name] = int(ctx.args[i])
+                        except ValueError:
+                            extra_kwargs[param_name] = ctx.args[i]
+                except:
+                    extra_kwargs[param_name] = ctx.args[i]
+            else:
+                # 布尔型标志参数
+                extra_kwargs[param_name] = True
+                i -= 1
+        i += 1
+    return extra_kwargs
\ No newline at end of file

mineru/utils/enum_class.py

@@ -21,6 +21,7 @@ class ContentType:
     TEXT = 'text'
     INTERLINE_EQUATION = 'interline_equation'
     INLINE_EQUATION = 'inline_equation'
+    EQUATION = 'equation'
 
 
 class CategoryId:

mineru/utils/format_utils.py

@@ -132,6 +132,35 @@ def otsl_parse_texts(texts, tokens):
     r_idx = 0
     c_idx = 0
 
+    # Check and complete the matrix
+    if split_row_tokens:
+        max_cols = max(len(row) for row in split_row_tokens)
+
+        # Insert additional <ecel> to tags
+        for row_idx, row in enumerate(split_row_tokens):
+            while len(row) < max_cols:
+                row.append(OTSL_ECEL)
+
+        # Insert additional <ecel> to texts
+        new_texts = []
+        text_idx = 0
+
+        for row_idx, row in enumerate(split_row_tokens):
+            for col_idx, token in enumerate(row):
+                new_texts.append(token)
+                if text_idx < len(texts) and texts[text_idx] == token:
+                    text_idx += 1
+                    if (text_idx < len(texts) and 
+                        texts[text_idx] not in [OTSL_NL, OTSL_FCEL, OTSL_ECEL, OTSL_LCEL, OTSL_UCEL, OTSL_XCEL]):
+                        new_texts.append(texts[text_idx])
+                        text_idx += 1
+
+            new_texts.append(OTSL_NL)
+            if text_idx < len(texts) and texts[text_idx] == OTSL_NL:
+                text_idx += 1
+
+        texts = new_texts
+
     def count_right(tokens, c_idx, r_idx, which_tokens):
         span = 0
         c_idx_iter = c_idx
@@ -235,10 +264,11 @@ def export_to_html(table_data: TableData):
 
     body = ""
 
+    grid = table_data.grid
     for i in range(nrows):
         body += "<tr>"
         for j in range(ncols):
-            cell: TableCell = table_data.grid[i][j]
+            cell: TableCell = grid[i][j]
 
             rowspan, rowstart = (
                 cell.row_span,

mineru/utils/llm_aided.py

 # Copyright (c) Opendatalab. All rights reserved.
 from loguru import logger
 from openai import OpenAI
-import ast
+import json_repair
 
 from mineru.backend.pipeline.pipeline_middle_json_mkcontent import merge_para_with_text
 
@@ -20,14 +20,19 @@ def llm_aided_title(page_info_list, title_aided_config):
             if block["type"] == "title":
                 origin_title_list.append(block)
                 title_text = merge_para_with_text(block)
-                page_line_height_list = []
+
+                if 'line_avg_height' in block:
+                    line_avg_height = block['line_avg_height']
+                else:
+                    title_block_line_height_list = []
                     for line in block['lines']:
                         bbox = line['bbox']
-                    page_line_height_list.append(int(bbox[3] - bbox[1]))
-                if len(page_line_height_list) > 0:
-                    line_avg_height = sum(page_line_height_list) / len(page_line_height_list)
+                        title_block_line_height_list.append(int(bbox[3] - bbox[1]))
+                    if len(title_block_line_height_list) > 0:
+                        line_avg_height = sum(title_block_line_height_list) / len(title_block_line_height_list)
                     else:
                         line_avg_height = int(block['bbox'][3] - block['bbox'][1])
+
                 title_dict[f"{i}"] = [title_text, line_avg_height, int(page_info['page_idx']) + 1]
                 i += 1
     # logger.info(f"Title list: {title_dict}")
@@ -91,7 +96,6 @@ Corrected title list:
             if "</think>" in content:
                 idx = content.index("</think>") + len("</think>")
                 content = content[idx:].strip()
-            import json_repair
             dict_completion = json_repair.loads(content)
             dict_completion = {int(k): int(v) for k, v in dict_completion.items()}
 

mineru/utils/models_download_utils.py

@@ -57,8 +57,12 @@ def auto_download_and_get_model_root_path(relative_path: str, repo_mode='pipelin
         relative_path = relative_path.strip('/')
         cache_dir = snapshot_download(repo, allow_patterns=[relative_path, relative_path+"/*"])
     elif repo_mode == 'vlm':
-        # VLM 模式下，直接下载整个模型目录
+        # VLM 模式下，根据 relative_path 的不同处理方式
+        if relative_path == "/":
             cache_dir = snapshot_download(repo)
+        else:
+            relative_path = relative_path.strip('/')
+            cache_dir = snapshot_download(repo, allow_patterns=[relative_path, relative_path+"/*"])
 
     if not cache_dir:
         raise FileNotFoundError(f"Failed to download model: {relative_path} from {repo}")

mineru/utils/ocr_utils.py

@@ -5,9 +5,11 @@ import numpy as np
 
 
 class OcrConfidence:
-    min_confidence = 0.68
+    min_confidence = 0.5
     min_width = 3
 
+LINE_WIDTH_TO_HEIGHT_RATIO_THRESHOLD = 4  # 一般情况下，行宽度超过高度4倍时才是一个正常的横向文本块
+
 
 def merge_spans_to_line(spans, threshold=0.6):
     if len(spans) == 0:
@@ -20,7 +22,7 @@ def merge_spans_to_line(spans, threshold=0.6):
         current_line = [spans[0]]
         for span in spans[1:]:
             # 如果当前的span与当前行的最后一个span在y轴上重叠，则添加到当前行
-            if __is_overlaps_y_exceeds_threshold(span['bbox'], current_line[-1]['bbox'], threshold):
+            if _is_overlaps_y_exceeds_threshold(span['bbox'], current_line[-1]['bbox'], threshold):
                 current_line.append(span)
             else:
                 # 否则，开始新行
@@ -33,7 +35,7 @@ def merge_spans_to_line(spans, threshold=0.6):
 
         return lines
 
-def __is_overlaps_y_exceeds_threshold(bbox1,
+def _is_overlaps_y_exceeds_threshold(bbox1,
                                      bbox2,
                                      overlap_ratio_threshold=0.8):
     """检查两个bbox在y轴上是否有重叠，并且该重叠区域的高度占两个bbox高度更低的那个超过80%"""
@@ -45,7 +47,21 @@ def __is_overlaps_y_exceeds_threshold(bbox1,
     # max_height = max(height1, height2)
     min_height = min(height1, height2)
 
-    return (overlap / min_height) > overlap_ratio_threshold
+    return (overlap / min_height) > overlap_ratio_threshold if min_height > 0 else False
+
+
+def _is_overlaps_x_exceeds_threshold(bbox1,
+                                     bbox2,
+                                     overlap_ratio_threshold=0.8):
+    """检查两个bbox在x轴上是否有重叠，并且该重叠区域的宽度占两个bbox宽度更低的那个超过指定阈值"""
+    x0_1, _, x1_1, _ = bbox1
+    x0_2, _, x1_2, _ = bbox2
+
+    overlap = max(0, min(x1_1, x1_2) - max(x0_1, x0_2))
+    width1, width2 = x1_1 - x0_1, x1_2 - x0_2
+    min_width = min(width1, width2)
+
+    return (overlap / min_width) > overlap_ratio_threshold if min_width > 0 else False
 
 
 def img_decode(content: bytes):
@@ -178,7 +194,7 @@ def update_det_boxes(dt_boxes, mfd_res):
         masks_list = []
         for mf_box in mfd_res:
             mf_bbox = mf_box['bbox']
-            if __is_overlaps_y_exceeds_threshold(text_bbox, mf_bbox):
+            if _is_overlaps_y_exceeds_threshold(text_bbox, mf_bbox):
                 masks_list.append([mf_bbox[0], mf_bbox[2]])
         text_x_range = [text_bbox[0], text_bbox[2]]
         text_remove_mask_range = remove_intervals(text_x_range, masks_list)
@@ -266,12 +282,27 @@ def merge_det_boxes(dt_boxes):
         for span in line:
             line_bbox_list.append(span['bbox'])
 
+        # 计算整行的宽度和高度
+        min_x = min(bbox[0] for bbox in line_bbox_list)
+        max_x = max(bbox[2] for bbox in line_bbox_list)
+        min_y = min(bbox[1] for bbox in line_bbox_list)
+        max_y = max(bbox[3] for bbox in line_bbox_list)
+        line_width = max_x - min_x
+        line_height = max_y - min_y
+
+        # 只有当行宽度超过高度4倍时才进行合并
+        if line_width > line_height * LINE_WIDTH_TO_HEIGHT_RATIO_THRESHOLD:
+
             # Merge overlapping text regions within the same line
             merged_spans = merge_overlapping_spans(line_bbox_list)
 
             # Convert the merged text regions back to point format and add them to the new detection box list
             for span in merged_spans:
                 new_dt_boxes.append(bbox_to_points(span))
+        else:
+            # 不进行合并，直接添加原始区域
+            for bbox in line_bbox_list:
+                new_dt_boxes.append(bbox_to_points(bbox))
 
     new_dt_boxes.extend(angle_boxes_list)
 

mineru/utils/pdf_reader.py

@@ -15,7 +15,7 @@ def page_to_image(
     scale = dpi / 72
 
     long_side_length = max(*page.get_size())
-    if long_side_length > max_width_or_height:
+    if (long_side_length*scale) > max_width_or_height:
         scale = max_width_or_height / long_side_length
 
     bitmap: PdfBitmap = page.render(scale=scale)  # type: ignore

mineru/utils/span_block_fix.py

 # Copyright (c) Opendatalab. All rights reserved.
 from mineru.utils.boxbase import calculate_overlap_area_in_bbox1_area_ratio
 from mineru.utils.enum_class import BlockType, ContentType
-from mineru.utils.ocr_utils import __is_overlaps_y_exceeds_threshold
+from mineru.utils.ocr_utils import _is_overlaps_y_exceeds_threshold, _is_overlaps_x_exceeds_threshold
 
+VERTICAL_SPAN_HEIGHT_TO_WIDTH_RATIO_THRESHOLD = 2
+VERTICAL_SPAN_IN_BLOCK_THRESHOLD = 0.8
 
 def fill_spans_in_blocks(blocks, spans, radio):
     """将allspans中的span按位置关系，放入blocks中."""
@@ -71,8 +73,26 @@ def fix_text_block(block):
     for span in block['spans']:
         if span['type'] == ContentType.INTERLINE_EQUATION:
             span['type'] = ContentType.INLINE_EQUATION
+
+    # 假设block中的span超过80%的数量高度是宽度的两倍以上，则认为是纵向文本块
+    vertical_span_count = sum(
+        1 for span in block['spans']
+        if (span['bbox'][3] - span['bbox'][1]) / (span['bbox'][2] - span['bbox'][0]) > VERTICAL_SPAN_HEIGHT_TO_WIDTH_RATIO_THRESHOLD
+    )
+    total_span_count = len(block['spans'])
+    if total_span_count == 0:
+        vertical_ratio = 0
+    else:
+        vertical_ratio = vertical_span_count / total_span_count
+
+    if vertical_ratio > VERTICAL_SPAN_IN_BLOCK_THRESHOLD:
+        # 如果是纵向文本块，则按纵向lines处理
+        block_lines = merge_spans_to_vertical_line(block['spans'])
+        sort_block_lines = vertical_line_sort_spans_from_top_to_bottom(block_lines)
+    else:
         block_lines = merge_spans_to_line(block['spans'])
         sort_block_lines = line_sort_spans_by_left_to_right(block_lines)
+
     block['lines'] = sort_block_lines
     del block['spans']
     return block
@@ -103,7 +123,7 @@ def merge_spans_to_line(spans, threshold=0.6):
                 continue
 
             # 如果当前的span与当前行的最后一个span在y轴上重叠，则添加到当前行
-            if __is_overlaps_y_exceeds_threshold(span['bbox'], current_line[-1]['bbox'], threshold):
+            if _is_overlaps_y_exceeds_threshold(span['bbox'], current_line[-1]['bbox'], threshold):
                 current_line.append(span)
             else:
                 # 否则，开始新行
@@ -117,6 +137,44 @@ def merge_spans_to_line(spans, threshold=0.6):
         return lines
 
 
+def merge_spans_to_vertical_line(spans, threshold=0.6):
+    """将纵向文本的spans合并成纵向lines（从右向左阅读）"""
+    if len(spans) == 0:
+        return []
+    else:
+        # 按照x2坐标从大到小排序（从右向左）
+        spans.sort(key=lambda span: span['bbox'][2], reverse=True)
+
+        vertical_lines = []
+        current_line = [spans[0]]
+
+        for span in spans[1:]:
+            # 特殊类型元素单独成列
+            if span['type'] in [
+                ContentType.INTERLINE_EQUATION, ContentType.IMAGE,
+                ContentType.TABLE
+            ] or any(s['type'] in [
+                ContentType.INTERLINE_EQUATION, ContentType.IMAGE,
+                ContentType.TABLE
+            ] for s in current_line):
+                vertical_lines.append(current_line)
+                current_line = [span]
+                continue
+
+            # 如果当前的span与当前行的最后一个span在y轴上重叠，则添加到当前行
+            if _is_overlaps_x_exceeds_threshold(span['bbox'], current_line[-1]['bbox'], threshold):
+                current_line.append(span)
+            else:
+                vertical_lines.append(current_line)
+                current_line = [span]
+
+        # 添加最后一列
+        if current_line:
+            vertical_lines.append(current_line)
+
+        return vertical_lines
+
+
 # 将每一个line中的span从左到右排序
 def line_sort_spans_by_left_to_right(lines):
     line_objects = []
@@ -136,6 +194,28 @@ def line_sort_spans_by_left_to_right(lines):
     return line_objects
 
 
+def vertical_line_sort_spans_from_top_to_bottom(vertical_lines):
+    line_objects = []
+    for line in vertical_lines:
+        # 按照y0坐标排序（从上到下）
+        line.sort(key=lambda span: span['bbox'][1])
+
+        # 计算整个列的边界框
+        line_bbox = [
+            min(span['bbox'][0] for span in line),  # x0
+            min(span['bbox'][1] for span in line),  # y0
+            max(span['bbox'][2] for span in line),  # x1
+            max(span['bbox'][3] for span in line),  # y1
+        ]
+
+        # 组装结果
+        line_objects.append({
+            'bbox': line_bbox,
+            'spans': line,
+        })
+    return line_objects
+
+
 def fix_block_spans(block_with_spans):
     fix_blocks = []
     for block in block_with_spans:

mineru/utils/span_pre_proc.py

 # Copyright (c) Opendatalab. All rights reserved.
+import collections
 import re
 import statistics
 
@@ -187,7 +188,7 @@ def txt_spans_extract(pdf_page, spans, pil_img, scale, all_bboxes, all_discarded
             span['chars'] = []
             new_spans.append(span)
 
-    need_ocr_spans = fill_char_in_spans(new_spans, page_all_chars)
+    need_ocr_spans = fill_char_in_spans(new_spans, page_all_chars, median_span_height)
 
     """对未填充的span进行ocr"""
     if len(need_ocr_spans) > 0:
@@ -208,14 +209,26 @@ def txt_spans_extract(pdf_page, spans, pil_img, scale, all_bboxes, all_discarded
     return spans
 
 
-def fill_char_in_spans(spans, all_chars):
-
+def fill_char_in_spans(spans, all_chars, median_span_height):
     # 简单从上到下排一下序
     spans = sorted(spans, key=lambda x: x['bbox'][1])
 
+    grid_size = median_span_height
+    grid = collections.defaultdict(list)
+    for i, span in enumerate(spans):
+        start_cell = int(span['bbox'][1] / grid_size)
+        end_cell = int(span['bbox'][3] / grid_size)
+        for cell_idx in range(start_cell, end_cell + 1):
+            grid[cell_idx].append(i)
+
     for char in all_chars:
+        char_center_y = (char['bbox'][1] + char['bbox'][3]) / 2
+        cell_idx = int(char_center_y / grid_size)
 
-        for span in spans:
+        candidate_span_indices = grid.get(cell_idx, [])
+
+        for span_idx in candidate_span_indices:
+            span = spans[span_idx]
             if calculate_char_in_span(char['bbox'], span['bbox'], char['char']):
                 span['chars'].append(char)
                 break

mineru/version.py

-__version__ = "2.0.5"
+__version__ = "2.0.6"

projects/README.md

@@ -3,10 +3,7 @@
 ## Project List
 
 - Projects compatible with version 2.0:
-  - [gradio_app](./gradio_app/README.md): Web application based on Gradio
   - [multi_gpu_v2](./multi_gpu_v2/README.md): Multi-GPU parallel processing based on LitServe
 
 - Projects not yet compatible with version 2.0:
-  - [web_api](./web_api/README.md): Web API based on FastAPI
-  - [multi_gpu](./multi_gpu/README.md): Multi-GPU parallel processing based on LitServe
   - [mcp](./mcp/README.md): MCP server based on the official API

projects/README_zh-CN.md

@@ -3,10 +3,7 @@
 ## 项目列表
 
 - 已兼容2.0版本的项目列表
-  - [gradio_app](./gradio_app/README_zh-CN.md): 基于 Gradio 的 Web 应用
   - [multi_gpu_v2](./multi_gpu_v2/README_zh.md): 基于 LitServe 的多 GPU 并行处理
 
 - 未兼容2.0版本的项目列表
-  - [web_api](./web_api/README.md): 基于 FastAPI 的 Web API 
-  - [multi_gpu](./multi_gpu/README.md): 基于 LitServe 的多 GPU 并行处理
   - [mcp](./mcp/README.md): 基于官方api的mcp server

projects/gradio_app/README.md

-## Installation
-
-MinerU(>=0.8.0)
- > If you already have a functioning MinerU environment, you can skip this step.
- > 
-[Deploy in CPU environment](https://github.com/opendatalab/MinerU?tab=readme-ov-file#quick-cpu-demo)
-
-[Deploy in GPU environment](https://github.com/opendatalab/MinerU?tab=readme-ov-file#using-gpu)
-
-Third-party Software
-
-```bash
-pip install gradio gradio-pdf
-```
-
-## Start Gradio App
-
-```bash
-python app.py
-```
-
-## Use Gradio App
-
-Access http://127.0.0.1:7860 in your web browser
\ No newline at end of file

projects/gradio_app/README_zh-CN.md

-## 安装
-
-MinerU(>=0.8.0)
- >如已有正常运行的MinerU环境则可以跳过此步骤
-> 
-[在CPU环境部署](https://github.com/opendatalab/MinerU/blob/master/README_zh-CN.md#%E4%BD%BF%E7%94%A8cpu%E5%BF%AB%E9%80%9F%E4%BD%93%E9%AA%8C)
-
-[在GPU环境部署](https://github.com/opendatalab/MinerU/blob/master/README_zh-CN.md#%E4%BD%BF%E7%94%A8gpu)
-
-第三方软件
-
-```bash
-pip install gradio gradio-pdf
-```
-
-## 启动gradio应用
-
-```bash
-python app.py
-```
-
-## 使用gradio应用
-
-在浏览器中访问 http://127.0.0.1:7860
\ No newline at end of file