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README_Ubuntu_CUDA_Acceleration_en_US.md

Ubuntu 22.04 LTS

1. Check if NVIDIA Drivers Are Installed

   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.

   +---------------------------------------------------------------------------------------+
   | 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:

   sudo apt-get update
   sudo apt-get install nvidia-driver-545

Install the proprietary driver and restart your computer after installation.

   reboot

3. Install Anaconda

If Anaconda is already installed, skip this step.

   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.

   conda create -n MinerU python=3.10
   conda activate MinerU

5. Install Applications

   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:

   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 how to download model files.

7. Understand the Location of the Configuration File

After completing the 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.

   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:

  1. Modify the value of "device-mode" in the magic-pdf.json configuration file located in your home directory.

    {
     "device-mode": "cuda"
    }
    
  2. Test CUDA acceleration with the following command:

    magic-pdf -p small_ocr.pdf
    

10. Enable CUDA Acceleration for OCR

❗ The following operations require a graphics card with at least 16GB of VRAM; otherwise, the program may crash or experience reduced performance.

  1. Download paddlepaddle-gpu. Installation will automatically enable OCR acceleration.

    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:

    magic-pdf -p small_ocr.pdf