Merge remote-tracking branch 'origin/dev' into dev

magic_pdf/pdf_parse_union_core_v2.py

@@ -17,6 +17,7 @@ from magic_pdf.libs.hash_utils import compute_md5
 from magic_pdf.libs.local_math import float_equal
 from magic_pdf.libs.ocr_content_type import ContentType
 from magic_pdf.model.magic_model import MagicModel
+from magic_pdf.para.para_split_v3 import para_split
 from magic_pdf.pre_proc.citationmarker_remove import remove_citation_marker
 from magic_pdf.pre_proc.construct_page_dict import ocr_construct_page_component_v2
 from magic_pdf.pre_proc.cut_image import ocr_cut_image_and_table
@@ -359,7 +360,7 @@ def parse_page_core(pdf_docs, magic_model, page_id, pdf_bytes_md5, imageWriter,
                                                need_drop, drop_reason)
 
     '''将span填入blocks中'''
-    block_with_spans, spans = fill_spans_in_blocks(all_bboxes, spans, 0.3)
+    block_with_spans, spans = fill_spans_in_blocks(all_bboxes, spans, 0.5)
 
     '''对block进行fix操作'''
     fix_blocks = fix_block_spans(block_with_spans, img_blocks, table_blocks)
@@ -435,9 +436,7 @@ def pdf_parse_union(pdf_bytes,
         pdf_info_dict[f"page_{page_id}"] = page_info
 
     """分段"""
-    # para_split(pdf_info_dict, debug_mode=debug_mode)
-    for page_num, page in pdf_info_dict.items():
-        page['para_blocks'] = page['preproc_blocks']
+    para_split(pdf_info_dict, debug_mode=debug_mode)
 
     """dict转list"""
     pdf_info_list = dict_to_list(pdf_info_dict)

magic_pdf/pre_proc/ocr_detect_all_bboxes.py

@@ -108,7 +108,7 @@ def ocr_prepare_bboxes_for_layout_split_v2(img_blocks, table_blocks, discarded_b
     all_bboxes = remove_overlaps_min_blocks(all_bboxes)
     all_discarded_blocks = remove_overlaps_min_blocks(all_discarded_blocks)
     '''将剩余的bbox做分离处理，防止后面分layout时出错'''
-    # all_bboxes, drop_reasons = remove_overlap_between_bbox_for_block(all_bboxes)
+    all_bboxes, drop_reasons = remove_overlap_between_bbox_for_block(all_bboxes)
 
     return all_bboxes, all_discarded_blocks
 

magic_pdf/pre_proc/ocr_dict_merge.py

@@ -49,8 +49,7 @@ def merge_spans_to_line(spans):
                 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']):
+            if __is_overlaps_y_exceeds_threshold(span['bbox'], current_line[-1]['bbox'], 0.6):
                 current_line.append(span)
             else:
                 # 否则，开始新行

docs/FAQ_en_us.md → old_docs/FAQ_en_us.md

@@ -11,7 +11,7 @@ pip install magic-pdf[full]
 
 ### 2. Encountering the error `pickle.UnpicklingError: invalid load key, 'v'.` during use
 
-This might be due to an incomplete download of the model file. You can try re-downloading the model file and then try again.  
+This might be due to an incomplete download of the model file. You can try re-downloading the model file and then try again.
 Reference: https://github.com/opendatalab/MinerU/issues/143
 
 ### 3. Where should the model files be downloaded and how should the `/models-dir` configuration be set?
@@ -24,7 +24,7 @@ The path for the model files is configured in "magic-pdf.json". just like:
 }
 ```
 
-This path is an absolute path, not a relative path. You can obtain the absolute path in the models directory using the "pwd" command.  
+This path is an absolute path, not a relative path. You can obtain the absolute path in the models directory using the "pwd" command.
 Reference: https://github.com/opendatalab/MinerU/issues/155#issuecomment-2230216874
 
 ### 4. Encountered the error `ImportError: libGL.so.1: cannot open shared object file: No such file or directory` in Ubuntu 22.04 on WSL2
@@ -38,17 +38,22 @@ sudo apt-get install libgl1-mesa-glx
 Reference: https://github.com/opendatalab/MinerU/issues/388
 
 ### 5. Encountered error `ModuleNotFoundError: No module named 'fairscale'`
+
 You need to uninstall the module and reinstall it:
+
 ```bash
 pip uninstall fairscale
 pip install fairscale
 ```
+
 Reference: https://github.com/opendatalab/MinerU/issues/411
 
 ### 6. On some newer devices like the H100, the text parsed during OCR using CUDA acceleration is garbled.
 
 The compatibility of cuda11 with new graphics cards is poor, and the CUDA version used by Paddle needs to be upgraded.
+
 ```bash
 pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu123/
 ```
+
 Reference: https://github.com/opendatalab/MinerU/issues/558

docs/FAQ_zh_cn.md → old_docs/FAQ_zh_cn.md

 # 常见问题解答
 
-### 1.在较新版本的mac上使用命令安装pip install magic-pdf[full] zsh: no matches found: magic-pdf[full]
+### 1.在较新版本的mac上使用命令安装pip install magic-pdf\[full\] zsh: no matches found: magic-pdf\[full\]
 
 在 macOS 上，默认的 shell 从 Bash 切换到了 Z shell，而 Z shell 对于某些类型的字符串匹配有特殊的处理逻辑，这可能导致no matches found错误。
 可以通过在命令行禁用globbing特性，再尝试运行安装命令
+
 ```bash
 setopt no_nomatch
 pip install magic-pdf[full]
@@ -11,41 +12,50 @@ pip install magic-pdf[full]
 
 ### 2.使用过程中遇到_pickle.UnpicklingError: invalid load key, 'v'.错误
 
-可能是由于模型文件未下载完整导致，可尝试重新下载模型文件后再试  
+可能是由于模型文件未下载完整导致，可尝试重新下载模型文件后再试
 参考：https://github.com/opendatalab/MinerU/issues/143
 
 ### 3.模型文件应该下载到哪里/models-dir的配置应该怎么填
 
 模型文件的路径输入是在"magic-pdf.json"中通过
+
 ```json
 {
   "models-dir": "/tmp/models"
 }
 ```
+
 进行配置的。
-这个路径是绝对路径而不是相对路径，绝对路径的获取可在models目录中通过命令 "pwd" 获取。  
+这个路径是绝对路径而不是相对路径，绝对路径的获取可在models目录中通过命令 "pwd" 获取。
 参考：https://github.com/opendatalab/MinerU/issues/155#issuecomment-2230216874
 
 ### 4.在WSL2的Ubuntu22.04中遇到报错`ImportError: libGL.so.1: cannot open shared object file: No such file or directory`
 
 WSL2的Ubuntu22.04中缺少`libgl`库，可通过以下命令安装`libgl`库解决：
+
 ```bash
 sudo apt-get install libgl1-mesa-glx
 ```
+
 参考：https://github.com/opendatalab/MinerU/issues/388
 
 ### 5.遇到报错 `ModuleNotFoundError : Nomodulenamed 'fairscale'`
+
 需要卸载该模块并重新安装
+
 ```bash
 pip uninstall fairscale
 pip install fairscale
 ```
+
 参考：https://github.com/opendatalab/MinerU/issues/411
 
 ### 6.在部分较新的设备如H100上，使用CUDA加速OCR时解析出的文字乱码。
 
 cuda11对新显卡的兼容性不好，需要升级paddle使用的cuda版本
+
 ```bash
 pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu123/
 ```
+
 参考：https://github.com/opendatalab/MinerU/issues/558

docs/README_Ubuntu_CUDA_Acceleration_en_US.md → old_docs/README_Ubuntu_CUDA_Acceleration_en_US.md

-
 # Ubuntu 22.04 LTS
 
 ### 1. Check if NVIDIA Drivers Are Installed
-   ```sh
-   nvidia-smi
-   ```
-   If you see information similar to the following, it means that the NVIDIA drivers are already installed, and you can skip Step 2.
-   ```plaintext
-   +---------------------------------------------------------------------------------------+
-   | NVIDIA-SMI 537.34                 Driver Version: 537.34       CUDA Version: 12.2     |
-   |-----------------------------------------+----------------------+----------------------+
-   | GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |
-   | Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
-   |                                         |                      |               MIG M. |
-   |=========================================+======================+======================|
-   |   0  NVIDIA GeForce RTX 3060 Ti   WDDM  | 00000000:01:00.0  On |                  N/A |
-   |  0%   51C    P8              12W / 200W |   1489MiB /  8192MiB |      5%      Default |
-   |                                         |                      |                  N/A |
-   +-----------------------------------------+----------------------+----------------------+
-   ```
+
+```sh
+nvidia-smi
+```
+
+If you see information similar to the following, it means that the NVIDIA drivers are already installed, and you can skip Step 2.
+
+```plaintext
++---------------------------------------------------------------------------------------+
+| NVIDIA-SMI 537.34                 Driver Version: 537.34       CUDA Version: 12.2     |
+|-----------------------------------------+----------------------+----------------------+
+| GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |
+| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
+|                                         |                      |               MIG M. |
+|=========================================+======================+======================|
+|   0  NVIDIA GeForce RTX 3060 Ti   WDDM  | 00000000:01:00.0  On |                  N/A |
+|  0%   51C    P8              12W / 200W |   1489MiB /  8192MiB |      5%      Default |
+|                                         |                      |                  N/A |
++-----------------------------------------+----------------------+----------------------+
+```
 
 ### 2. Install the Driver
-   If no driver is installed, use the following command:
-   ```sh
-   sudo apt-get update
-   sudo apt-get install nvidia-driver-545
-   ```
-   Install the proprietary driver and restart your computer after installation.
-   ```sh
-   reboot
-   ```
+
+If no driver is installed, use the following command:
+
+```sh
+sudo apt-get update
+sudo apt-get install nvidia-driver-545
+```
+
+Install the proprietary driver and restart your computer after installation.
+
+```sh
+reboot
+```
 
 ### 3. Install Anaconda
-   If Anaconda is already installed, skip this step.
-   ```sh
-   wget https://repo.anaconda.com/archive/Anaconda3-2024.06-1-Linux-x86_64.sh
-   bash Anaconda3-2024.06-1-Linux-x86_64.sh
-   ```
-   In the final step, enter `yes`, close the terminal, and reopen it.
+
+If Anaconda is already installed, skip this step.
+
+```sh
+wget https://repo.anaconda.com/archive/Anaconda3-2024.06-1-Linux-x86_64.sh
+bash Anaconda3-2024.06-1-Linux-x86_64.sh
+```
+
+In the final step, enter `yes`, close the terminal, and reopen it.
 
 ### 4. Create an Environment Using Conda
-   Specify Python version 3.10.
-   ```sh
-   conda create -n MinerU python=3.10
-   conda activate MinerU
-   ```
+
+Specify Python version 3.10.
+
+```sh
+conda create -n MinerU python=3.10
+conda activate MinerU
+```
 
 ### 5. Install Applications
-   ```sh
-   pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
-   ```
+
+```sh
+pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
+```
+
 ❗ After installation, make sure to check the version of `magic-pdf` using the following command:
-   ```sh
-   magic-pdf --version
-   ```
-   If the version number is less than 0.7.0, please report the issue.
+
+```sh
+magic-pdf --version
+```
+
+If the version number is less than 0.7.0, please report the issue.
 
 ### 6. Download Models
-   Refer to detailed instructions on [how to download model files](how_to_download_models_en.md).
+
+Refer to detailed instructions on [how to download model files](how_to_download_models_en.md).
 
 ## 7. Understand the Location of the Configuration File
 
 After completing the [6. Download Models](#6-download-models) step, the script will automatically generate a `magic-pdf.json` file in the user directory and configure the default model path.
 You can find the `magic-pdf.json` file in your user directory.
+
 > The user directory for Linux is "/home/username".
 
 ### 8. First Run
-   Download a sample file from the repository and test it.
-   ```sh
-   wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf
-   magic-pdf -p small_ocr.pdf
-   ```
+
+Download a sample file from the repository and test it.
+
+```sh
+wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf
+magic-pdf -p small_ocr.pdf
+```
 
 ### 9. Test CUDA Acceleration
 
@@ -90,7 +109,7 @@ If your graphics card has at least **8GB** of VRAM, follow these steps to test C
    ```
 
 ### 10. Enable CUDA Acceleration for OCR
- 
+
 1. Download `paddlepaddle-gpu`. Installation will automatically enable OCR acceleration.
    ```sh
    python -m pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/

docs/README_Ubuntu_CUDA_Acceleration_zh_CN.md → old_docs/README_Ubuntu_CUDA_Acceleration_zh_CN.md

 # Ubuntu 22.04 LTS
 
 ## 1. 检测是否已安装nvidia驱动
+
 ```bash
-nvidia-smi 
+nvidia-smi
 ```
+
 如果看到类似如下的信息，说明已经安装了nvidia驱动，可以跳过步骤2
+
 ```
 +---------------------------------------------------------------------------------------+
 | NVIDIA-SMI 537.34                 Driver Version: 537.34       CUDA Version: 12.2     |
@@ -18,78 +21,110 @@ nvidia-smi
 |                                         |                      |                  N/A |
 +-----------------------------------------+----------------------+----------------------+
 ```
+
 ## 2. 安装驱动
+
 如没有驱动，则通过如下命令
+
 ```bash
 sudo apt-get update
 sudo apt-get install nvidia-driver-545
 ```
+
 安装专有驱动，安装完成后，重启电脑
+
 ```bash
 reboot
 ```
+
 ## 3. 安装anacoda
+
 如果已安装conda，可以跳过本步骤
+
 ```bash
 wget -U NoSuchBrowser/1.0 https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2024.06-1-Linux-x86_64.sh
 bash Anaconda3-2024.06-1-Linux-x86_64.sh
 ```
+
 最后一步输入yes，关闭终端重新打开
+
 ## 4. 使用conda 创建环境
+
 需指定python版本为3.10
+
 ```bash
 conda create -n MinerU python=3.10
 conda activate MinerU
 ```
+
 ## 5. 安装应用
+
 ```bash
 pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i https://pypi.tuna.tsinghua.edu.cn/simple
 ```
+
 > ❗️下载完成后，务必通过以下命令确认magic-pdf的版本是否正确
-> 
+>
 > ```bash
 > magic-pdf --version
->```
+> ```
+>
 > 如果版本号小于0.7.0，请到issue中向我们反馈
 
 ## 6. 下载模型
+
 详细参考 [如何下载模型文件](how_to_download_models_zh_cn.md)
 
 ## 7. 了解配置文件存放的位置
+
 完成[6.下载模型](#6-下载模型)步骤后，脚本会自动生成用户目录下的magic-pdf.json文件，并自动配置默认模型路径。
-您可在【用户目录】下找到magic-pdf.json文件。 
+您可在【用户目录】下找到magic-pdf.json文件。
+
 > linux用户目录为 "/home/用户名"
 
 ## 8. 第一次运行
+
 从仓库中下载样本文件，并测试
+
 ```bash
 wget https://gitee.com/myhloli/MinerU/raw/master/demo/small_ocr.pdf
 magic-pdf -p small_ocr.pdf
 ```
+
 ## 9. 测试CUDA加速
+
 如果您的显卡显存大于等于 **8GB** ，可以进行以下流程，测试CUDA解析加速效果
->❗️因8GB显存运行本应用非常极限，需要关闭所有其他正在使用显存的程序以确保本应用运行时有足额8GB显存可用。
+
+> ❗️因8GB显存运行本应用非常极限，需要关闭所有其他正在使用显存的程序以确保本应用运行时有足额8GB显存可用。
 
 **1.修改【用户目录】中配置文件magic-pdf.json中"device-mode"的值**
+
 ```json
 {
   "device-mode":"cuda"
 }
 ```
+
 **2.运行以下命令测试cuda加速效果**
+
 ```bash
 magic-pdf -p small_ocr.pdf
 ```
+
 > 提示：CUDA加速是否生效可以根据log中输出的各个阶段cost耗时来简单判断，通常情况下，`layout detection cost` 和 `mfr time` 应提速10倍以上。
 
 ## 10. 为ocr开启cuda加速
 
 **1.下载paddlepaddle-gpu, 安装完成后会自动开启ocr加速**
+
 ```bash
 python -m pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/
 ```
+
 **2.运行以下命令测试ocr加速效果**
+
 ```bash
 magic-pdf -p small_ocr.pdf
 ```
+
 > 提示：CUDA加速是否生效可以根据log中输出的各个阶段cost耗时来简单判断，通常情况下，`ocr cost`应提速10倍以上。

docs/README_Windows_CUDA_Acceleration_en_US.md → old_docs/README_Windows_CUDA_Acceleration_en_US.md

 # Windows 10/11
 
 ### 1. Install CUDA and cuDNN
+
 Required versions: CUDA 11.8 + cuDNN 8.7.0
-   - CUDA 11.8: https://developer.nvidia.com/cuda-11-8-0-download-archive
-   - cuDNN v8.7.0 (November 28th, 2022), for CUDA 11.x: https://developer.nvidia.com/rdp/cudnn-archive
-   
+
+- CUDA 11.8: https://developer.nvidia.com/cuda-11-8-0-download-archive
+- cuDNN v8.7.0 (November 28th, 2022), for CUDA 11.x: https://developer.nvidia.com/rdp/cudnn-archive
+
 ### 2. Install Anaconda
-   If Anaconda is already installed, you can skip this step.
-   
+
+If Anaconda is already installed, you can skip this step.
+
 Download link: https://repo.anaconda.com/archive/Anaconda3-2024.06-1-Windows-x86_64.exe
 
 ### 3. Create an Environment Using Conda
-   Python version must be 3.10.
-   ```
-   conda create -n MinerU python=3.10
-   conda activate MinerU
-   ```
+
+Python version must be 3.10.
+
+```
+conda create -n MinerU python=3.10
+conda activate MinerU
+```
 
 ### 4. Install Applications
-   ```
-   pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
-   ```
-   >❗️After installation, verify the version of `magic-pdf`:
-   >  ```bash
-   >  magic-pdf --version
-   >  ```
-   > If the version number is less than 0.7.0, please report it in the issues section.
-   
+
+```
+pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
+```
+
+> ❗️After installation, verify the version of `magic-pdf`:
+>
+> ```bash
+> magic-pdf --version
+> ```
+>
+> If the version number is less than 0.7.0, please report it in the issues section.
+
 ### 5. Download Models
-   Refer to detailed instructions on [how to download model files](how_to_download_models_en.md).
+
+Refer to detailed instructions on [how to download model files](how_to_download_models_en.md).
 
 ### 6. Understand the Location of the Configuration File
 
 After completing the [5. Download Models](#5-download-models) step, the script will automatically generate a `magic-pdf.json` file in the user directory and configure the default model path.
 You can find the `magic-pdf.json` file in your 【user directory】 .
+
 > The user directory for Windows is "C:/Users/username".
 
 ### 7. First Run
-   Download a sample file from the repository and test it.
-   ```powershell
-     wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf -O small_ocr.pdf
-     magic-pdf -p small_ocr.pdf
-   ```
+
+Download a sample file from the repository and test it.
+
+```powershell
+  wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf -O small_ocr.pdf
+  magic-pdf -p small_ocr.pdf
+```
 
 ### 8. Test CUDA Acceleration
-   If your graphics card has at least 8GB of VRAM, follow these steps to test CUDA-accelerated parsing performance.
-    
+
+If your graphics card has at least 8GB of VRAM, follow these steps to test CUDA-accelerated parsing performance.
+
 > ❗ Due to the extremely limited nature of 8GB VRAM for running this application, you need to close all other programs using VRAM to ensure that 8GB of VRAM is available when running this application.
 
-   1. **Overwrite the installation of torch and torchvision** supporting CUDA.
-      ```
-      pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 --index-url https://download.pytorch.org/whl/cu118
-      ```
-      >❗️Ensure the following versions are specified in the command:
-      >```
-      > torch==2.3.1 torchvision==0.18.1
-      >```
-      >These are the highest versions we support. Installing higher versions without specifying them will cause the program to fail.
-   2. **Modify the value of `"device-mode"`** in the `magic-pdf.json` configuration file located in your user directory.
-     
-      ```json
-      {
-        "device-mode": "cuda"
-      }
-      ```
-   3. **Run the following command to test CUDA acceleration**:
-
-      ```
-      magic-pdf -p small_ocr.pdf
-      ```
+1. **Overwrite the installation of torch and torchvision** supporting CUDA.
+
+   ```
+   pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 --index-url https://download.pytorch.org/whl/cu118
+   ```
+
+   > ❗️Ensure the following versions are specified in the command:
+   >
+   > ```
+   > torch==2.3.1 torchvision==0.18.1
+   > ```
+   >
+   > These are the highest versions we support. Installing higher versions without specifying them will cause the program to fail.
+
+2. **Modify the value of `"device-mode"`** in the `magic-pdf.json` configuration file located in your user directory.
+
+   ```json
+   {
+     "device-mode": "cuda"
+   }
+   ```
+
+3. **Run the following command to test CUDA acceleration**:
+
+   ```
+   magic-pdf -p small_ocr.pdf
+   ```
 
 ### 9. Enable CUDA Acceleration for OCR
 
 1. **Download paddlepaddle-gpu**, which will automatically enable OCR acceleration upon installation.
-      ```
-      pip install paddlepaddle-gpu==2.6.1
-      ```
+   ```
+   pip install paddlepaddle-gpu==2.6.1
+   ```
 2. **Run the following command to test OCR acceleration**:
    ```
    magic-pdf -p small_ocr.pdf

docs/README_Windows_CUDA_Acceleration_zh_CN.md → old_docs/README_Windows_CUDA_Acceleration_zh_CN.md

@@ -3,82 +3,108 @@
 ## 1. 安装cuda和cuDNN
 
 需要安装的版本 CUDA 11.8 + cuDNN 8.7.0
+
 - CUDA 11.8 https://developer.nvidia.com/cuda-11-8-0-download-archive
 - cuDNN v8.7.0 (November 28th, 2022), for CUDA 11.x https://developer.nvidia.com/rdp/cudnn-archive
 
 ## 2. 安装anaconda
+
 如果已安装conda，可以跳过本步骤
 
 下载链接：
 https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2024.06-1-Windows-x86_64.exe
 
 ## 3. 使用conda 创建环境
+
 需指定python版本为3.10
+
 ```bash
 conda create -n MinerU python=3.10
 conda activate MinerU
 ```
+
 ## 4. 安装应用
+
 ```bash
 pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i https://pypi.tuna.tsinghua.edu.cn/simple
 ```
+
 > ❗️下载完成后，务必通过以下命令确认magic-pdf的版本是否正确
-> 
+>
 > ```bash
 > magic-pdf --version
->```
+> ```
+>
 > 如果版本号小于0.7.0，请到issue中向我们反馈
 
 ## 5. 下载模型
+
 详细参考 [如何下载模型文件](how_to_download_models_zh_cn.md)
 
 ## 6. 了解配置文件存放的位置
+
 完成[5.下载模型](#5-下载模型)步骤后，脚本会自动生成用户目录下的magic-pdf.json文件，并自动配置默认模型路径。
 您可在【用户目录】下找到magic-pdf.json文件。
+
 > windows用户目录为 "C:/Users/用户名"
 
 ## 7. 第一次运行
+
 从仓库中下载样本文件，并测试
+
 ```powershell
  wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf -O small_ocr.pdf
  magic-pdf -p small_ocr.pdf
 ```
 
 ## 8. 测试CUDA加速
+
 如果您的显卡显存大于等于 **8GB** ，可以进行以下流程，测试CUDA解析加速效果
->❗️因8GB显存运行本应用非常极限，需要关闭所有其他正在使用显存的程序以确保本应用运行时有足额8GB显存可用。
+
+> ❗️因8GB显存运行本应用非常极限，需要关闭所有其他正在使用显存的程序以确保本应用运行时有足额8GB显存可用。
 
 **1.覆盖安装支持cuda的torch和torchvision**
+
 ```bash
 pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 --index-url https://download.pytorch.org/whl/cu118
 ```
+
 > ❗️务必在命令中指定以下版本
+>
 > ```bash
-> torch==2.3.1 torchvision==0.18.1 
+> torch==2.3.1 torchvision==0.18.1
 > ```
+>
 > 这是我们支持的最高版本，如果不指定版本会自动安装更高版本导致程序无法运行
 
 **2.修改【用户目录】中配置文件magic-pdf.json中"device-mode"的值**
+
 ```json
 {
   "device-mode":"cuda"
 }
 ```
+
 **3.运行以下命令测试cuda加速效果**
+
 ```bash
 magic-pdf -p small_ocr.pdf
 ```
+
 > 提示：CUDA加速是否生效可以根据log中输出的各个阶段的耗时来简单判断，通常情况下，`layout detection time` 和 `mfr time` 应提速10倍以上。
 
 ## 9. 为ocr开启cuda加速
 
 **1.下载paddlepaddle-gpu, 安装完成后会自动开启ocr加速**
+
 ```bash
 pip install paddlepaddle-gpu==2.6.1
 ```
+
 **2.运行以下命令测试ocr加速效果**
+
 ```bash
 magic-pdf -p small_ocr.pdf
 ```
-> 提示：CUDA加速是否生效可以根据log中输出的各个阶段cost耗时来简单判断，通常情况下，`ocr time`应提速10倍以上。
 
+> 提示：CUDA加速是否生效可以根据log中输出的各个阶段cost耗时来简单判断，通常情况下，`ocr time`应提速10倍以上。

docs/download_models.py → old_docs/download_models.py

+import json
 import os
+
 import requests
-import json
 from modelscope import snapshot_download
 
 
@@ -27,13 +28,13 @@ def download_and_modify_json(url, local_filename, modifications):
 if __name__ == '__main__':
     model_dir = snapshot_download('opendatalab/PDF-Extract-Kit')
     layoutreader_model_dir = snapshot_download('ppaanngggg/layoutreader')
-    model_dir = model_dir + "/models"
-    print(f"model_dir is: {model_dir}")
-    print(f"layoutreader_model_dir is: {layoutreader_model_dir}")
+    model_dir = model_dir + '/models'
+    print(f'model_dir is: {model_dir}')
+    print(f'layoutreader_model_dir is: {layoutreader_model_dir}')
 
     json_url = 'https://gitee.com/myhloli/MinerU/raw/master/magic-pdf.template.json'
-    config_file_name = "magic-pdf.json"
-    home_dir = os.path.expanduser("~")
+    config_file_name = 'magic-pdf.json'
+    home_dir = os.path.expanduser('~')
     config_file = os.path.join(home_dir, config_file_name)
 
     json_mods = {
@@ -42,5 +43,4 @@ if __name__ == '__main__':
     }
 
     download_and_modify_json(json_url, config_file, json_mods)
-    print(f"The configuration file has been configured successfully, the path is: {config_file}")
-
+    print(f'The configuration file has been configured successfully, the path is: {config_file}')

docs/download_models_hf.py → old_docs/download_models_hf.py

+import json
 import os
+
 import requests
-import json
 from huggingface_hub import snapshot_download
 
 
@@ -27,13 +28,13 @@ def download_and_modify_json(url, local_filename, modifications):
 if __name__ == '__main__':
     model_dir = snapshot_download('opendatalab/PDF-Extract-Kit')
     layoutreader_model_dir = snapshot_download('hantian/layoutreader')
-    model_dir = model_dir + "/models"
-    print(f"model_dir is: {model_dir}")
-    print(f"layoutreader_model_dir is: {layoutreader_model_dir}")
+    model_dir = model_dir + '/models'
+    print(f'model_dir is: {model_dir}')
+    print(f'layoutreader_model_dir is: {layoutreader_model_dir}')
 
     json_url = 'https://github.com/opendatalab/MinerU/raw/master/magic-pdf.template.json'
-    config_file_name = "magic-pdf.json"
-    home_dir = os.path.expanduser("~")
+    config_file_name = 'magic-pdf.json'
+    home_dir = os.path.expanduser('~')
     config_file = os.path.join(home_dir, config_file_name)
 
     json_mods = {
@@ -42,5 +43,4 @@ if __name__ == '__main__':
     }
 
     download_and_modify_json(json_url, config_file, json_mods)
-    print(f"The configuration file has been configured successfully, the path is: {config_file}")
-
+    print(f'The configuration file has been configured successfully, the path is: {config_file}')

docs/how_to_download_models_en.md → old_docs/how_to_download_models_en.md

 Model downloads are divided into initial downloads and updates to the model directory. Please refer to the corresponding documentation for instructions on how to proceed.
 
-
 # Initial download of model files
 
 ### 1. Download the Model from Hugging Face
+
 Use a Python Script to Download Model Files from Hugging Face
+
 ```bash
 pip install huggingface_hub
 wget https://github.com/opendatalab/MinerU/raw/master/docs/download_models_hf.py -O download_models_hf.py
 python download_models_hf.py
 ```
+
 The Python script will automatically download the model files and configure the model directory in the configuration file.
 
 The configuration file can be found in the user directory, with the filename `magic-pdf.json`.
@@ -18,7 +20,7 @@ The configuration file can be found in the user directory, with the filename `ma
 
 ## 1. Models downloaded via Git LFS
 
->Due to feedback from some users that downloading model files using git lfs was incomplete or resulted in corrupted model files, this method is no longer recommended.
+> Due to feedback from some users that downloading model files using git lfs was incomplete or resulted in corrupted model files, this method is no longer recommended.
 
 If you previously downloaded model files via git lfs, you can navigate to the previous download directory and use the `git pull` command to update the model.
 

docs/how_to_download_models_zh_cn.md → old_docs/how_to_download_models_zh_cn.md

@@ -10,7 +10,6 @@
   <pre><code>pip install huggingface_hub
 wget https://gitee.com/myhloli/MinerU/raw/master/docs/download_models_hf.py -O download_models_hf.py
 python download_models_hf.py</code></pre>
-  <p>python脚本执行完毕后，会输出模型下载目录</p>
 </details>
 
 ## 方法二：从 ModelScope 下载模型
@@ -22,26 +21,27 @@ pip install modelscope
 wget https://gitee.com/myhloli/MinerU/raw/master/docs/download_models.py -O download_models.py
 python download_models.py
 ```
+
 python脚本会自动下载模型文件并配置好配置文件中的模型目录
 
 配置文件可以在用户目录中找到，文件名为`magic-pdf.json`
-> windows的用户目录为 "C:\\Users\\用户名", linux用户目录为 "/home/用户名", macOS用户目录为 "/Users/用户名"
 
+> windows的用户目录为 "C:\\Users\\用户名", linux用户目录为 "/home/用户名", macOS用户目录为 "/Users/用户名"
 
 # 此前下载过模型，如何更新
 
 ## 1. 通过git lfs下载过模型
 
->由于部分用户反馈通过git lfs下载模型文件遇到下载不全和模型文件损坏情况，现已不推荐使用该方式下载。
+> 由于部分用户反馈通过git lfs下载模型文件遇到下载不全和模型文件损坏情况，现已不推荐使用该方式下载。
 
 如此前通过 git lfs 下载过模型文件，可以进入到之前的下载目录中，通过`git pull`命令更新模型。
 
 > 0.9.x及以后版本由于新增layout排序模型，且该模型和此前的模型不在同一仓库，不能通过`git pull`命令更新，需要单独下载。
-> 
->``` 
->from modelscope import snapshot_download
->snapshot_download('ppaanngggg/layoutreader')
->```
+>
+> ```
+> from modelscope import snapshot_download
+> snapshot_download('ppaanngggg/layoutreader')
+> ```
 
 ## 2. 通过 Hugging Face 或 Model Scope 下载过模型