# 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 -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). 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 -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. 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 >❗️This operation requires at least 16GB of VRAM on your graphics card, otherwise it will cause the program to crash or slow down. 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 ```