Boost With Cuda ================ If your device supports CUDA and meets the GPU requirements of the mainline environment, you can use GPU acceleration. Please select the appropriate guide based on your system: - :ref:`ubuntu_22_04_lts_section` - :ref:`windows_10_or_11_section` - Quick Deployment with Docker > Docker requires a GPU with at least 16GB of VRAM, and all acceleration features are enabled by default. .. note:: Before running this Docker, you can use the following command to check if your device supports CUDA acceleration on Docker. bash docker run --rm --gpus=all nvidia/cuda:12.1.0-base-ubuntu22.04 nvidia-smi .. code:: sh wget https://github.com/opendatalab/MinerU/raw/master/Dockerfile docker build -t mineru:latest . docker run --rm -it --gpus=all mineru:latest /bin/bash magic-pdf --help .. _ubuntu_22_04_lts_section: Ubuntu 22.04 LTS ----------------- 1. Check if NVIDIA Drivers Are Installed ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. code:: 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. Notice:``CUDA Version`` should be >= 12.1, If the displayed version number is less than 12.1, please upgrade the driver. .. code:: text +---------------------------------------------------------------------------------------+ | 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: .. code:: sh sudo apt-get update sudo apt-get install nvidia-driver-545 Install the proprietary driver and restart your computer after installation. .. code:: sh reboot 3. Install Anaconda ~~~~~~~~~~~~~~~~~~~ If Anaconda is already installed, skip this step. .. code:: 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. .. code:: sh conda create -n MinerU python=3.10 conda activate MinerU 5. Install Applications ~~~~~~~~~~~~~~~~~~~~~~~ .. code:: 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: .. code:: 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 :doc:`download_model_weight_files` 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. .. code:: sh wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf 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: 1. Modify the value of ``"device-mode"`` in the ``magic-pdf.json`` configuration file located in your home directory. .. code:: json { "device-mode": "cuda" } 2. Test CUDA acceleration with the following command: .. code:: 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. .. code:: sh python -m pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/ 2. Test OCR acceleration with the following command: .. code:: sh magic-pdf -p small_ocr.pdf -o ./output .. _windows_10_or_11_section: 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``: .. code:: 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 :doc:`download_model_weight_files` 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. .. code:: powershell wget https://github.com/opendatalab/MinerU/raw/master/demo/small_ocr.pdf -O small_ocr.pdf magic-pdf -p small_ocr.pdf -o ./output 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. .. code:: json { "device-mode": "cuda" } 3. **Run the following command to test CUDA acceleration**: :: 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