Merge pull request #2063 from myhloli/dev

update docs

README.md

@@ -215,7 +215,7 @@ There are three different ways to experience MinerU:
     </tr>
     <tr>
         <td colspan="3">Python Version</td>
-        <td colspan="3">3.10(Please make sure to create a Python 3.10 virtual environment using conda)</td>
+        <td colspan="3">3.10~3.12</td>
     </tr>
     <tr>
         <td colspan="3">Nvidia Driver Version</td>
@@ -225,8 +225,8 @@ There are three different ways to experience MinerU:
     </tr>
     <tr>
         <td colspan="3">CUDA Environment</td>
-        <td>Automatic installation [12.1 (pytorch) + 11.8 (paddle)]</td>
-        <td>11.8 (manual installation) + cuDNN v8.7.0 (manual installation)</td>
+        <td>11.8/12.4/12.6</td>
+        <td>11.8/12.4/12.6</td>
         <td>None</td>
     </tr>
     <tr>
@@ -236,11 +236,11 @@ There are three different ways to experience MinerU:
         <td>None</td>
     </tr>
     <tr>
-        <td rowspan="2">GPU Hardware Support List</td>
-        <td colspan="2">GPU VRAM 8GB or more</td>
-        <td colspan="2">2080~2080Ti / 3060Ti~3090Ti / 4060~4090<br>
-        8G VRAM can enable all acceleration features</td>
-        <td rowspan="2">None</td>
+        <td rowspan="2">GPU/MPS Hardware Support List</td>
+        <td colspan="2">GPU VRAM 6GB or more</td>
+        <td colspan="2">All GPUs with Tensor Cores produced from Volta(2017) onwards.<br>
+        More than 6GB VRAM </td>
+        <td rowspan="2">apple slicon</td>
     </tr>
 </table>
 
@@ -257,9 +257,9 @@ Synced with dev branch updates:
 #### 1. Install magic-pdf
 
 ```bash
-conda create -n mineru python=3.10
+conda create -n mineru 'python<3.13' -y
 conda activate mineru
-pip install -U "magic-pdf[full]" --extra-index-url https://wheels.myhloli.com
+pip install -U "magic-pdf[full]"
 ```
 
 #### 2. Download model weight files
@@ -284,7 +284,7 @@ You can modify certain configurations in this file to enable or disable features
 {
     // other config
     "layout-config": {
-        "model": "doclayout_yolo" // Please change to "layoutlmv3" when using layoutlmv3.
+        "model": "doclayout_yolo" 
     },
     "formula-config": {
         "mfd_model": "yolo_v8_mfd",
@@ -292,7 +292,7 @@ You can modify certain configurations in this file to enable or disable features
         "enable": true  // The formula recognition feature is enabled by default. If you need to disable it, please change the value here to "false".
     },
     "table-config": {
-        "model": "rapid_table",  // Default to using "rapid_table", can be switched to "tablemaster" or "struct_eqtable".
+        "model": "rapid_table", 
         "sub_model": "slanet_plus",  // When the model is "rapid_table", you can choose a sub_model. The options are "slanet_plus" and "unitable"
         "enable": true, // The table recognition feature is enabled by default. If you need to disable it, please change the value here to "false".
         "max_time": 400
@@ -308,7 +308,7 @@ If your device supports CUDA and meets the GPU requirements of the mainline envi
 - [Windows 10/11 + GPU](docs/README_Windows_CUDA_Acceleration_en_US.md)
 - Quick Deployment with Docker
 > [!IMPORTANT]
-> Docker requires a GPU with at least 8GB of VRAM, and all acceleration features are enabled by default.
+> Docker requires a GPU with at least 6GB of VRAM, and all acceleration features are enabled by default.
 >
 > Before running this Docker, you can use the following command to check if your device supports CUDA acceleration on Docker.
 > 
@@ -330,7 +330,7 @@ If your device has NPU acceleration hardware, you can follow the tutorial below
 
 ### Using MPS
 
-If your device uses Apple silicon chips, you can enable MPS acceleration for certain supported tasks (such as layout detection and formula detection).
+If your device uses Apple silicon chips, you can enable MPS acceleration for your tasks.
 
 You can enable MPS acceleration by setting the `device-mode` parameter to `mps` in the `magic-pdf.json` configuration file.
 
@@ -341,10 +341,6 @@ You can enable MPS acceleration by setting the `device-mode` parameter to `mps`
 }
 ```
 
-> [!TIP]
-> Since the formula recognition task cannot utilize MPS acceleration, you can disable the formula recognition feature in tasks where it is not needed to achieve optimal performance.
->
-> You can disable the formula recognition feature by setting the `enable` parameter in the `formula-config` section to `false`.
 
 ## Usage
 

README_zh-CN.md

@@ -288,7 +288,7 @@ pip install -U "magic-pdf[full]" -i https://mirrors.aliyun.com/pypi/simple
 {
     // other config
     "layout-config": {
-        "model": "doclayout_yolo" // 使用layoutlmv3请修改为“layoutlmv3"
+        "model": "doclayout_yolo" 
     },
     "formula-config": {
         "mfd_model": "yolo_v8_mfd",
@@ -296,7 +296,7 @@ pip install -U "magic-pdf[full]" -i https://mirrors.aliyun.com/pypi/simple
         "enable": true  // 公式识别功能默认是开启的，如果需要关闭请修改此处的值为"false"
     },
     "table-config": {
-        "model": "rapid_table",  // 默认使用"rapid_table",可以切换为"tablemaster"和"struct_eqtable"
+        "model": "rapid_table",  
         "sub_model": "slanet_plus",  // 当model为"rapid_table"时，可以自选sub_model，可选项为"slanet_plus"和"unitable"
         "enable": true, // 表格识别功能默认是开启的，如果需要关闭请修改此处的值为"false"
         "max_time": 400
@@ -312,7 +312,7 @@ pip install -U "magic-pdf[full]" -i https://mirrors.aliyun.com/pypi/simple
 - [Windows10/11 + GPU](docs/README_Windows_CUDA_Acceleration_zh_CN.md)
 - 使用Docker快速部署
 > [!IMPORTANT]
-> Docker 需设备gpu显存大于等于8GB，默认开启所有加速功能
+> Docker 需设备gpu显存大于等于6GB，默认开启所有加速功能
 > 
 > 运行本docker前可以通过以下命令检测自己的设备是否支持在docker上使用CUDA加速
 > 
@@ -332,7 +332,7 @@ pip install -U "magic-pdf[full]" -i https://mirrors.aliyun.com/pypi/simple
 [NPU加速教程](docs/README_Ascend_NPU_Acceleration_zh_CN.md)
 
 ### 使用MPS
-如果您的设备使用Apple silicon 芯片，您可以在部分支持的任务（layout检测/公式检测）中开启mps加速：
+如果您的设备使用Apple silicon 芯片，您可以开启mps加速：
 
 您可以通过在 `magic-pdf.json` 配置文件中将 `device-mode` 参数设置为 `mps` 来启用 MPS 加速。
 
@@ -343,10 +343,6 @@ pip install -U "magic-pdf[full]" -i https://mirrors.aliyun.com/pypi/simple
 }
 ```
 
-> [!TIP]
-> 由于公式识别任务无法开启mps加速，您可在不需要识别公式的任务关闭公式识别功能以获得最佳性能。
->
-> 您可以通过将 `formula-config` 部分中的 `enable` 参数设置为 `false` 来禁用公式识别功能。
 
 
 ## 使用

docs/README_Ubuntu_CUDA_Acceleration_en_US.md

@@ -9,11 +9,11 @@ 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.
 
 > [!NOTE]
-> Notice:`CUDA Version` should be >= 12.1, If the displayed version number is less than 12.1, please upgrade the driver.
+> Notice:`CUDA Version` should be >= 12.4, If the displayed version number is less than 12.4, please upgrade the driver.
 
 ```plaintext
 +---------------------------------------------------------------------------------------+
-| NVIDIA-SMI 537.34                 Driver Version: 537.34       CUDA Version: 12.2     |
+| NVIDIA-SMI 570.133.07             Driver Version: 572.83         CUDA Version: 12.8   |
 |-----------------------------------------+----------------------+----------------------+
 | GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |
 | Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
@@ -31,7 +31,7 @@ If no driver is installed, use the following command:
 
 ```sh
 sudo apt-get update
-sudo apt-get install nvidia-driver-545
+sudo apt-get install nvidia-driver-570-server
 ```
 
 Install the proprietary driver and restart your computer after installation.
@@ -53,17 +53,15 @@ 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
+```bash
+conda create -n mineru 'python<3.13' -y
+conda activate mineru
 ```
 
 ### 5. Install Applications
 
 ```sh
-pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
+pip install -U magic-pdf[full]
 ```
 > [!IMPORTANT]
 > After installation, make sure to check the version of `magic-pdf` using the following command:
@@ -72,7 +70,7 @@ pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
 > magic-pdf --version
 > ```
 >
-> If the version number is less than 0.7.0, please report the issue.
+> If the version number is less than 1.3.0, please report the issue.
 
 ### 6. Download Models
 
@@ -100,7 +98,7 @@ magic-pdf -p small_ocr.pdf -o ./output
 
 ### 9. Test CUDA Acceleration
 
-If your graphics card has at least **8GB** of VRAM, follow these steps to test CUDA acceleration:
+If your graphics card has at least **6GB** of VRAM, follow these steps to test CUDA acceleration:
 
 1. Modify the value of `"device-mode"` in the `magic-pdf.json` configuration file located in your home directory.
    ```json
@@ -111,15 +109,4 @@ If your graphics card has at least **8GB** of VRAM, follow these steps to test C
 2. Test CUDA acceleration with the following command:
    ```sh
    magic-pdf -p small_ocr.pdf -o ./output
-   ```
-
-### 10. Enable CUDA Acceleration for OCR
-
-1. Download `paddlepaddle-gpu`. Installation will automatically enable OCR acceleration.
-   ```sh
-   python -m pip install paddlepaddle-gpu==3.0.0rc1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/
-   ```
-2. Test OCR acceleration with the following command:
-   ```sh
-   magic-pdf -p small_ocr.pdf -o ./output
-   ```
+   ```

docs/README_Ubuntu_CUDA_Acceleration_zh_CN.md

@@ -9,11 +9,11 @@ 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
 
 > [!NOTE]
-> `CUDA Version` 显示的版本号应 >= 12.1，如显示的版本号小于12.1，请升级驱动
+> `CUDA Version` 显示的版本号应 >= 12.4，如显示的版本号小于12.4，请升级驱动
 
 ```plaintext
 +---------------------------------------------------------------------------------------+
-| NVIDIA-SMI 537.34                 Driver Version: 537.34       CUDA Version: 12.2     |
+| NVIDIA-SMI 570.133.07             Driver Version: 572.83         CUDA Version: 12.8   |
 |-----------------------------------------+----------------------+----------------------+
 | GPU  Name                     TCC/WDDM  | Bus-Id        Disp.A | Volatile Uncorr. ECC |
 | Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
@@ -31,7 +31,7 @@ nvidia-smi
 
 ```bash
 sudo apt-get update
-sudo apt-get install nvidia-driver-545
+sudo apt-get install nvidia-driver-570-server
 ```
 
 安装专有驱动，安装完成后，重启电脑
@@ -53,17 +53,15 @@ bash Anaconda3-2024.06-1-Linux-x86_64.sh
 
 ## 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
+conda create -n mineru 'python<3.13' -y
+conda activate mineru
 ```
 
 ## 5. 安装应用
 
 ```bash
-pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i https://mirrors.aliyun.com/pypi/simple
+pip install -U magic-pdf[full] -i https://mirrors.aliyun.com/pypi/simple
 ```
 
 > [!IMPORTANT]
@@ -73,7 +71,7 @@ pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i h
 > magic-pdf --version
 > ```
 >
-> 如果版本号小于0.7.0，请到issue中向我们反馈
+> 如果版本号小于1.3.0，请到issue中向我们反馈
 
 ## 6. 下载模型
 
@@ -99,7 +97,7 @@ magic-pdf -p small_ocr.pdf -o ./output
 
 ## 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
+如果您的显卡显存大于等于 **6GB** ，可以进行以下流程，测试CUDA解析加速效果
 
 **1.修改【用户目录】中配置文件magic-pdf.json中"device-mode"的值**
 
@@ -115,20 +113,4 @@ magic-pdf -p small_ocr.pdf -o ./output
 magic-pdf -p small_ocr.pdf -o ./output
 ```
 > [!TIP]
-> 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==3.0.0rc1 -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 -o ./output
-```
-> [!TIP]
-> 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。
+> 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，使用cuda加速会比cpu更快。

docs/README_Windows_CUDA_Acceleration_en_US.md

@@ -2,10 +2,11 @@
 
 ### 1. Install CUDA and cuDNN
 
-Required versions: CUDA 11.8 + cuDNN 8.7.0
+You need to install a CUDA version that is compatible with torch's requirements. Currently, torch supports CUDA 11.8/12.4/12.6.
 
-- 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
+- CUDA 12.4 https://developer.nvidia.com/cuda-12-4-0-download-archive
+- CUDA 12.6 https://developer.nvidia.com/cuda-12-6-0-download-archive
 
 ### 2. Install Anaconda
 
@@ -15,17 +16,15 @@ Download link: https://repo.anaconda.com/archive/Anaconda3-2024.06-1-Windows-x86
 
 ### 3. Create an Environment Using Conda
 
-Python version must be 3.10.
-
-```
-conda create -n MinerU python=3.10
-conda activate MinerU
+```bash
+conda create -n mineru 'python<3.13' -y
+conda activate mineru
 ```
 
 ### 4. Install Applications
 
 ```
-pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
+pip install -U magic-pdf[full]
 ```
 
 > [!IMPORTANT]
@@ -35,7 +34,7 @@ pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
 > magic-pdf --version
 > ```
 >
-> If the version number is less than 0.7.0, please report it in the issues section.
+> If the version number is less than 1.3.0, please report it in the issues section.
 
 ### 5. Download Models
 
@@ -60,12 +59,12 @@ Download a sample file from the repository and test it.
 
 ### 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 6GB of VRAM, follow these steps to test CUDA-accelerated parsing performance.
 
-1. **Overwrite the installation of torch and torchvision** supporting CUDA.
+1. **Overwrite the installation of torch and torchvision** supporting CUDA.(Please select the appropriate index-url based on your CUDA version. For more details, refer to the [PyTorch official website](https://pytorch.org/get-started/locally/).)
 
    ```
-   pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 "numpy<2.0.0" --index-url https://download.pytorch.org/whl/cu118
+   pip install --force-reinstall torch==2.6.0 torchvision==0.21.1 "numpy<2.0.0" --index-url https://download.pytorch.org/whl/cu124
    ```
 
 2. **Modify the value of `"device-mode"`** in the `magic-pdf.json` configuration file located in your user directory.
@@ -81,15 +80,4 @@ If your graphics card has at least 8GB of VRAM, follow these steps to test CUDA-
 
    ```
    magic-pdf -p small_ocr.pdf -o ./output
-   ```
-
-### 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
-   ```
-2. **Run the following command to test OCR acceleration**:
-   ```
-   magic-pdf -p small_ocr.pdf -o ./output
-   ```
+   ```

docs/README_Windows_CUDA_Acceleration_zh_CN.md

@@ -2,10 +2,11 @@
 
 ## 1. 安装cuda和cuDNN
 
-需要安装的版本 CUDA 11.8 + cuDNN 8.7.0
+需要安装符合torch要求的cuda版本，torch目前支持11.8/12.4/12.6
 
 - 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 12.4 https://developer.nvidia.com/cuda-12-4-0-download-archive
+- CUDA 12.6 https://developer.nvidia.com/cuda-12-6-0-download-archive
 
 ## 2. 安装anaconda
 
@@ -16,17 +17,15 @@ https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2024.06-1-Window
 
 ## 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
+conda create -n mineru 'python<3.13' -y
+conda activate mineru
 ```
 
 ## 4. 安装应用
 
 ```bash
-pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i https://mirrors.aliyun.com/pypi/simple
+pip install -U magic-pdf[full] -i https://mirrors.aliyun.com/pypi/simple
 ```
 
 > [!IMPORTANT]
@@ -36,7 +35,7 @@ pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i h
 > magic-pdf --version
 > ```
 >
-> 如果版本号小于0.7.0，请到issue中向我们反馈
+> 如果版本号小于 1.3.0 ，请到issue中向我们反馈
 
 ## 5. 下载模型
 
@@ -61,12 +60,12 @@ pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i h
 
 ## 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
+如果您的显卡显存大于等于 **6GB** ，可以进行以下流程，测试CUDA解析加速效果
 
-**1.覆盖安装支持cuda的torch和torchvision**
+**1.覆盖安装支持cuda的torch和torchvision**(请根据cuda版本选择合适的index-url，具体可参考[torch官网](https://pytorch.org/get-started/locally/))
 
 ```bash
-pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 "numpy<2.0.0" --index-url https://download.pytorch.org/whl/cu118
+pip install --force-reinstall torch==2.6.0 torchvision==0.21.1 "numpy<2.0.0" --index-url https://download.pytorch.org/whl/cu124
 ```
 
 **2.修改【用户目录】中配置文件magic-pdf.json中"device-mode"的值**
@@ -84,20 +83,4 @@ magic-pdf -p small_ocr.pdf -o ./output
 ```
 
 > [!TIP]
-> 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 -o ./output
-```
-> [!TIP]
-> 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。
+> 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，cuda加速后运行速度比cpu更快。