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 9. Test CUDA Acceleration ~~~~~~~~~~~~~~~~~~~~~~~~~ If your graphics card has at least **8GB** of VRAM, follow these steps to test CUDA acceleration: ❗ Due to the extremely limited nature of 8GB VRAM for running this application, you need to close all other programs using VRAM to ensure that 8GB of VRAM is available when running this application. 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 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 .. _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 8. Test CUDA Acceleration ~~~~~~~~~~~~~~~~~~~~~~~~~ If your graphics card has at least 8GB of VRAM, follow these steps to test CUDA-accelerated parsing performance. ❗ Due to the extremely limited nature of 8GB VRAM for running this application, you need to close all other programs using VRAM to ensure that 8GB of VRAM is available when running this application. 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 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