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Commit a778645b authored by myhloli's avatar myhloli
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docs(gpu): update CUDA acceleration documentation 

- Update CUDA version requirements to12.4
- Recommend nvidia-driver-570-server for Ubuntu
- Remove Python version specification for conda environment
- Update magic-pdf version requirement to 1.3.0
- Simplify CUDA acceleration testing instructions
- Remove OCR acceleration with paddlepaddle-gpu
- Update torch and torchvision installation instructions for Windows
parent 298305dd
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docs/README_Ubuntu_CUDA_Acceleration_en_US.md
View file @ a778645b
......@@ -9,11 +9,11 @@ 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.
> [!NOTE]
> Notice:`CUDA Version` should be >= 12.1, If the displayed version number is less than 12.1, please upgrade the driver.
> Notice:`CUDA Version` should be >= 12.4, If the displayed version number is less than 12.4, please upgrade the driver.
```plaintext
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 537.34 Driver Version: 537.34 CUDA Version: 12.2 |
| NVIDIA-SMI 570.133.07 Driver Version: 572.83 CUDA Version: 12.8 |
|-----------------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
......@@ -31,7 +31,7 @@ If no driver is installed, use the following command:
```sh
sudo apt-get update
sudo apt-get install nvidia-driver-545
sudo apt-get install nvidia-driver-570-server
```
Install the proprietary driver and restart your computer after installation.
......@@ -53,17 +53,15 @@ In the final step, enter `yes`, close the terminal, and reopen it.
### 4. Create an Environment Using Conda
Specify Python version 3.10.
```sh
conda create -n MinerU python=3.10
conda activate MinerU
```bash
conda create -n mineru 'python<3.13' -y
conda activate mineru
```
### 5. Install Applications
```sh
pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
pip install -U magic-pdf[full]
```
> [!IMPORTANT]
> After installation, make sure to check the version of `magic-pdf` using the following command:
......@@ -72,7 +70,7 @@ pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
> magic-pdf --version
> ```
>
> If the version number is less than 0.7.0, please report the issue.
> If the version number is less than 1.3.0, please report the issue.
### 6. Download Models
......@@ -100,7 +98,7 @@ 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:
If your graphics card has at least **6GB** 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.
```json
......@@ -111,15 +109,4 @@ If your graphics card has at least **8GB** of VRAM, follow these steps to test C
2. Test CUDA acceleration with the following command:
```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.
```sh
python -m pip install paddlepaddle-gpu==3.0.0rc1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/
```
2. Test OCR acceleration with the following command:
```sh
magic-pdf -p small_ocr.pdf -o ./output
```
```
\ No newline at end of file
docs/README_Ubuntu_CUDA_Acceleration_zh_CN.md
View file @ a778645b
......@@ -9,11 +9,11 @@ nvidia-smi
如果看到类似如下的信息，说明已经安装了nvidia驱动，可以跳过步骤2
> [!NOTE]
> `CUDA Version` 显示的版本号应 >= 12.1，如显示的版本号小于12.1，请升级驱动
> `CUDA Version` 显示的版本号应 >= 12.4，如显示的版本号小于12.4，请升级驱动
```plaintext
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 537.34 Driver Version: 537.34 CUDA Version: 12.2 |
| NVIDIA-SMI 570.133.07 Driver Version: 572.83 CUDA Version: 12.8 |
|-----------------------------------------+----------------------+----------------------+
| GPU Name TCC/WDDM | Bus-Id Disp.A | Volatile Uncorr. ECC |
| Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. |
......@@ -31,7 +31,7 @@ nvidia-smi
```bash
sudo apt-get update
sudo apt-get install nvidia-driver-545
sudo apt-get install nvidia-driver-570-server
```
安装专有驱动，安装完成后，重启电脑
......@@ -53,17 +53,15 @@ bash Anaconda3-2024.06-1-Linux-x86_64.sh
## 4. 使用conda 创建环境
需指定python版本为3.10
```bash
conda create -n MinerU python=3.10
conda activate MinerU
conda create -n mineru 'python<3.13' -y
conda activate mineru
```
## 5. 安装应用
```bash
pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i https://mirrors.aliyun.com/pypi/simple
pip install -U magic-pdf[full] -i https://mirrors.aliyun.com/pypi/simple
```
> [!IMPORTANT]
......@@ -73,7 +71,7 @@ pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i h
> magic-pdf --version
> ```
>
> 如果版本号小于0.7.0，请到issue中向我们反馈
> 如果版本号小于1.3.0，请到issue中向我们反馈
## 6. 下载模型
......@@ -99,7 +97,7 @@ magic-pdf -p small_ocr.pdf -o ./output
## 9. 测试CUDA加速
如果您的显卡显存大于等于 **8GB** ，可以进行以下流程，测试CUDA解析加速效果
如果您的显卡显存大于等于 **6GB** ，可以进行以下流程，测试CUDA解析加速效果
**1.修改【用户目录】中配置文件magic-pdf.json中"device-mode"的值**
......@@ -115,20 +113,4 @@ magic-pdf -p small_ocr.pdf -o ./output
magic-pdf -p small_ocr.pdf -o ./output
```
> [!TIP]
> CUDA加速是否生效可以根据log中输出的各个阶段cost耗时来简单判断，通常情况下，`layout detection cost` 和 `mfr time` 应提速10倍以上。
## 10. 为ocr开启cuda加速
**1.下载paddlepaddle-gpu, 安装完成后会自动开启ocr加速**
```bash
python -m pip install paddlepaddle-gpu==3.0.0rc1 -i https://www.paddlepaddle.org.cn/packages/stable/cu118/
```
**2.运行以下命令测试ocr加速效果**
```bash
magic-pdf -p small_ocr.pdf -o ./output
```
> [!TIP]
> CUDA加速是否生效可以根据log中输出的各个阶段cost耗时来简单判断，通常情况下，`ocr cost`应提速10倍以上。
> CUDA加速是否生效可以根据log中输出的各个阶段cost耗时来简单判断，通常情况下，使用cuda加速会比cpu更快。
docs/README_Windows_CUDA_Acceleration_en_US.md
View file @ a778645b
......@@ -2,10 +2,11 @@
### 1. Install CUDA and cuDNN
Required versions: CUDA 11.8 + cuDNN 8.7.0
You need to install a CUDA version that is compatible with torch's requirements. Currently, torch supports CUDA 11.8/12.4/12.6.
- 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
- CUDA 11.8 https://developer.nvidia.com/cuda-11-8-0-download-archive
- CUDA 12.4 https://developer.nvidia.com/cuda-12-4-0-download-archive
- CUDA 12.6 https://developer.nvidia.com/cuda-12-6-0-download-archive
### 2. Install Anaconda
......@@ -15,17 +16,15 @@ Download link: https://repo.anaconda.com/archive/Anaconda3-2024.06-1-Windows-x86
### 3. Create an Environment Using Conda
Python version must be 3.10.
```
conda create -n MinerU python=3.10
conda activate MinerU
```bash
conda create -n mineru 'python<3.13' -y
conda activate mineru
```
### 4. Install Applications
```
pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
pip install -U magic-pdf[full]
```
> [!IMPORTANT]
......@@ -35,7 +34,7 @@ pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com
> magic-pdf --version
> ```
>
> If the version number is less than 0.7.0, please report it in the issues section.
> If the version number is less than 1.3.0, please report it in the issues section.
### 5. Download Models
......@@ -60,12 +59,12 @@ Download a sample file from the repository and test it.
### 8. Test CUDA Acceleration
If your graphics card has at least 8GB of VRAM, follow these steps to test CUDA-accelerated parsing performance.
If your graphics card has at least 6GB of VRAM, follow these steps to test CUDA-accelerated parsing performance.
1. **Overwrite the installation of torch and torchvision** supporting CUDA.
1. **Overwrite the installation of torch and torchvision** supporting CUDA.(Please select the appropriate index-url based on your CUDA version. For more details, refer to the [PyTorch official website](https://pytorch.org/get-started/locally/).)
```
pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 "numpy<2.0.0" --index-url https://download.pytorch.org/whl/cu118
pip install --force-reinstall torch==2.6.0 torchvision==0.21.1 "numpy<2.0.0" --index-url https://download.pytorch.org/whl/cu124
```
2. **Modify the value of `"device-mode"`** in the `magic-pdf.json` configuration file located in your user directory.
......@@ -81,15 +80,4 @@ If your graphics card has at least 8GB of VRAM, follow these steps to test CUDA-
```
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
```
```
\ No newline at end of file
docs/README_Windows_CUDA_Acceleration_zh_CN.md
View file @ a778645b
......@@ -2,10 +2,11 @@
## 1. 安装cuda和cuDNN
需要安装的版本 CUDA 11.8 + cuDNN 8.7.0
需要安装符合torch要求的cuda版本，torch目前支持11.8/12.4/12.6
- 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
- CUDA 12.4 https://developer.nvidia.com/cuda-12-4-0-download-archive
- CUDA 12.6 https://developer.nvidia.com/cuda-12-6-0-download-archive
## 2. 安装anaconda
......@@ -16,17 +17,15 @@ https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda3-2024.06-1-Window
## 3. 使用conda 创建环境
需指定python版本为3.10
```bash
conda create -n MinerU python=3.10
conda activate MinerU
conda create -n mineru 'python<3.13' -y
conda activate mineru
```
## 4. 安装应用
```bash
pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i https://mirrors.aliyun.com/pypi/simple
pip install -U magic-pdf[full] -i https://mirrors.aliyun.com/pypi/simple
```
> [!IMPORTANT]
......@@ -36,7 +35,7 @@ pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i h
> magic-pdf --version
> ```
>
> 如果版本号小于0.7.0，请到issue中向我们反馈
> 如果版本号小于 1.3.0 ，请到issue中向我们反馈
## 5. 下载模型
......@@ -61,12 +60,12 @@ pip install -U magic-pdf[full] --extra-index-url https://wheels.myhloli.com -i h
## 8. 测试CUDA加速
如果您的显卡显存大于等于 **8GB** ，可以进行以下流程，测试CUDA解析加速效果
如果您的显卡显存大于等于 **6GB** ，可以进行以下流程，测试CUDA解析加速效果
**1.覆盖安装支持cuda的torch和torchvision**
**1.覆盖安装支持cuda的torch和torchvision**(请根据cuda版本选择合适的index-url，具体可参考[torch官网](https://pytorch.org/get-started/locally/))
```bash
pip install --force-reinstall torch==2.3.1 torchvision==0.18.1 "numpy<2.0.0" --index-url https://download.pytorch.org/whl/cu118
pip install --force-reinstall torch==2.6.0 torchvision==0.21.1 "numpy<2.0.0" --index-url https://download.pytorch.org/whl/cu124
```
**2.修改【用户目录】中配置文件magic-pdf.json中"device-mode"的值**
......@@ -84,20 +83,4 @@ magic-pdf -p small_ocr.pdf -o ./output
```
> [!TIP]
> CUDA加速是否生效可以根据log中输出的各个阶段的耗时来简单判断，通常情况下，`layout detection time` 和 `mfr time` 应提速10倍以上。
## 9. 为ocr开启cuda加速
**1.下载paddlepaddle-gpu, 安装完成后会自动开启ocr加速**
```bash
pip install paddlepaddle-gpu==2.6.1
```
**2.运行以下命令测试ocr加速效果**
```bash
magic-pdf -p small_ocr.pdf -o ./output
```
> [!TIP]
> CUDA加速是否生效可以根据log中输出的各个阶段cost耗时来简单判断，通常情况下，`ocr time`应提速10倍以上。
> CUDA加速是否生效可以根据log中输出的各个阶段的耗时来简单判断，通常情况下，cuda加速后运行速度比cpu更快。
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