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

2. Install Anaconda

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

4. Install Applications

   pip install magic-pdf[full]==0.6.2b1 detectron2 --extra-index-url https://wheels.myhloli.com

❗️After installation, verify the version of magic-pdf:

   >  magic-pdf --version
   >  ```
   > If the version number is less than 0.6.2, 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).  
   After downloading, move the `models` directory to an SSD with more space.
   
   >❗ After downloading the models, ensure they are complete:
   >- Check that the file sizes match the description on the website.
   >- If possible, verify the integrity using SHA256.

### 6. Configuration Before the First Run
   Obtain the configuration template file `magic-pdf.template.json` from the repository root directory.
    
   >❗️Execute the following command to copy the configuration file to your user directory, or the program will not run.
   >   
   > In Windows, user directory is "C:\Users\username"

powershell

 (New-Object System.Net.WebClient).DownloadFile('https://github.com/opendatalab/MinerU/raw/master/magic-pdf.template.json', 'magic-pdf.template.json')
 cp magic-pdf.template.json ~/magic-pdf.json


   Find the `magic-pdf.json` file in your user directory and configure `"models-dir"` to point to the directory where the model weights from step 5 were downloaded.
   
   > ❗️Ensure the absolute path of the model weights directory is correctly configured, or the program will fail to run due to not finding the model files.
   >    
   > In Windows, this path should include the drive letter and replace all `"\"` to `"/"`.
   >   
   > Example: If the models are placed in the root directory of drive D, the value for `model-dir` should be `"D:/models"`.

json {

 "models-dir": "/tmp/models"

}


### 7. First Run
   Download a sample file from the repository and test it.

powershell

 (New-Object System.Net.WebClient).DownloadFile('https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf', 'small_ocr.pdf')
 magic-pdf pdf-command --pdf 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.

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.
Modify the value of "device-mode" in the magic-pdf.json configuration file located in your user directory.
```
  {
    "device-mode": "cuda"
  }
```
Run the following command to test CUDA acceleration:
```
  magic-pdf pdf-command --pdf small_ocr.pdf
```

9. Enable CUDA Acceleration for OCR

❗️This operation requires at least 16GB of VRAM on your graphics card, otherwise it will cause the program to crash or slow down.
Download paddlepaddle-gpu, which will automatically enable OCR acceleration upon installation.
  pip install paddlepaddle-gpu==2.6.1
Run the following command to test OCR acceleration:
  magic-pdf pdf-command --pdf small_ocr.pdf

README_Windows_CUDA_Acceleration_en_US.md 4.2 KB Історія Запис