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
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
Python version must be 3.10.
conda create -n MinerU python=3.10
conda activate MinerU
pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
Important
After installation, verify the version of magic-pdf
:
magic-pdf --version
If the version number is less than 0.7.0, please report it in the issues section.
Refer to detailed instructions on how to download model files.
After completing the 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】 .
Tip
The user directory for Windows is "C:/Users/username".
Download a sample file from the repository and test it.
wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf -O small_ocr.pdf
magic-pdf -p small_ocr.pdf -o ./output
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
-
Modify the value of
"device-mode"
in themagic-pdf.json
configuration file located in your user directory.{ "device-mode": "cuda" }
-
Run the following command to test CUDA acceleration:
magic-pdf -p small_ocr.pdf -o ./output
- 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 -p small_ocr.pdf -o ./output