RapidOCR

https://rapidai.github.io/RapidOCRDocs/
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RapidOCR is an open-source, cross-platform OCR tool that converts PaddleOCR models to ONNX and other...
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### Install Nuitka

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr_web/nuitka_package

Installs Nuitka. On first installation, mingw and ccache are automatically downloaded, or they can be configured manually.

```bash
pip install nuitka
```

--------------------------------

### Install OpenVINO

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/how_to_use_infer_engine

Install the OpenVINO inference engine.

```bash
pip install openvino
```

--------------------------------

### Install pre-commit and enable Git hooks

Source: https://rapidai.github.io/RapidOCRDocs/latest/contributing?q=

Installs pre-commit and sets up the Git hook in the repository root. After installation, every git commit automatically runs configured formatters; if checks fail, the commit is rejected.

```bash
# 在 python 目录下、已激活的虚拟环境中安装
pip install pre-commit

# 到仓库根目录 RapidOCR 下安装 Git 钩子（.pre-commit-config.yaml 在根目录）
cd ..   # 若当前在 python 目录，先回到仓库根目录
pre-commit install
```

--------------------------------

### Run main.py to start the web service

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr_web/ocrweb_multi?q=

Starts the OCR web service. After running, open http://127.0.0.1:8001 to use the application.

```bash
python main.py
```

--------------------------------

### Install rapidocr_web with pip

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr_web/usage

Install the rapidocr_web package via pip.

```bash
pip install rapidocr_web
```

--------------------------------

### Start rapidocr_api on Windows with model paths

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr_api/usage

Start the server on Windows by setting model paths via environment variables and then running rapidocr_api.

```bash
set det_model_path=I:\models\图像相关\OCR\RapidOCR\PP-OCRv4\ch_PP-OCRv4_det_server_infer.onnx
set rec_model_path=I:\models\图像相关\OCR\RapidOCR\PP-OCRv4\ch_PP-OCRv4_rec_server_infer.onnx
rapidocr_api
```

--------------------------------

### Install rapidocr_onnxruntime

Source: https://rapidai.github.io/RapidOCRDocs/latest/blog/2023/10/17/%E5%A6%82%E4%BD%95%E6%9B%B4%E6%8D%A2%E5%85%B6%E4%BB%96%E6%A3%80%E6%B5%8B%E5%92%8C%E8%AF%86%E5%88%AB%E6%A8%A1%E5%9E%8B?q=

Install the rapidocr_onnxruntime package. This is the first step before using the library to load custom PaddleOCR models.

```bash
pip install rapidocr_onnxruntime

```

--------------------------------

### Install dependencies with pip

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr_web/ocrweb_multi?q=

Changes into the ocrweb_multi directory and installs required Python packages using the Douban PyPI mirror. Run after cloning the repository.

```bash
cd ocrweb_multi
pip install -r requirements.txt -i https://pypi.douban.com/simple/
```

--------------------------------

### Install ONNX Runtime

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/how_to_use_infer_engine

Install the ONNX Runtime inference engine. The CPU version is recommended; GPU is not recommended for use with rapidocr.

```bash
pip install onnxruntime
```

--------------------------------

### RapidOCR API output example (with text)

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr_api/usage

Example output when text is detected. Shows the structure with rec_txt, dt_boxes (coordinates), and score.

```json
{
 "0": {
  "rec_txt": "香港深圳抽血，", # 识别的文本
  "dt_boxes": [  # 依次为左上角 → 右上角 → 右下角 → 左下角
   [265, 18],
   [472, 231],
   [431, 271],
   [223, 59]
  ],
  "score": "0.8176"   # 置信度
 }
}
```

--------------------------------

### 安装构建工具和依赖

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/package/build-custom-version-rapidocr-whl

升级 pip 并安装构建所需的 setuptools、wheel、setuptools-scm 和 PyYAML。

```bash
python -m pip install --upgrade pip
python -m pip install build setuptools wheel setuptools-scm PyYAML
```

--------------------------------

### Install rapidocr with ONNX Runtime

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/install

Installs the rapidocr package along with the ONNX Runtime inference engine. This is the default installation command for rapidocr versions 2.0.6 and later, where ONNX Runtime is no longer a dependency and must be installed manually.

```bash
pip install rapidocr onnxruntime
```

--------------------------------

### Install dependencies and pytest

Source: https://rapidai.github.io/RapidOCRDocs/latest/contributing?q=

Installs project dependencies, pytest for running unit tests, and optionally installs the package in editable mode for local development.

```bash
pip install -r requirements.txt
pip install pytest  # 运行单元测试需要
# 可选：以可编辑模式安装当前包，便于调试
pip install -e .
```

--------------------------------

### Start rapidocr_api on Linux with options

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr_api/usage

Start the server on Linux with default parameters, specify IP, port, and worker count, and set model paths via environment variables.

```bash
# 默认参数启动
rapidocr_api

# 指定参数：端口与进程数量；
rapidocr_api -ip 0.0.0.0 -p 9005 -workers 2

# 指定模型
export det_model_path=/mnt/sda1/models/PP-OCRv4/ch_PP-OCRv4_det_server_infer.onnx
export rec_model_path=/mnt/sda1/models/PP-OCRv4/ch_PP-OCRv4_rec_server_infer.onnx
rapidocr_api -ip 0.0.0.0 -p 9005 -workers 2
```

--------------------------------

### 准备默认模型资源

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/package/build-custom-version-rapidocr-whl

运行 prepare_wheel_assets.py 下载或校验默认模型，并生成 MANIFEST.in 以确保模型被打入 wheel。

```bash
python tools/prepare_wheel_assets.py
```

--------------------------------

### Install rapidocr_api with pip

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr_api/usage

Install the rapidocr_api package using pip.

```bash
pip install rapidocr_api
```

--------------------------------

### Check RapidOCR installation with rapidocr check

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/usage

Runs the RapidOCR installation check. It uses ONNX Runtime to process an image and verifies the result to determine if the library is installed correctly.

```bash
rapidocr check

```

--------------------------------

### Dependencies for rapidocr

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/install

Lists the dependency packages required by rapidocr. If a dependency fails to install, install it individually first, then install rapidocr. Note the version constraints for Shapely and omegaconf.

```text
pyclipper>=1.2.0
opencv_python>=4.5.1.48
numpy>=1.19.5,<3.0.0
six>=1.15.0
Shapely>=1.7.1,!=2.0.4  # python3.12 2.0.4 bug
PyYAML
Pillow
tqdm
omegaconf!=2.2.1 # https://github.com/omry/omegaconf/issues/934
requests
colorlog
```

--------------------------------

### Example wheel filename

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/package/build-custom-version-rapidocr-whl?q=

Example of the generated wheel filename for version 3.1.0.

```text
dist/rapidocr-3.1.0-py3-none-any.whl
```

--------------------------------

### Verify installation with rapidocr check

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/install

Verifies installation for rapidocr versions 2.0.3 and later. The command `rapidocr check` outputs log lines and the final message 'Success! rapidocr is installed correctly!' to confirm success.

```bash
$ rapidocr check

# 输出以下内容即证明安装成功
[INFO] 2026-06-23 12:51:43,979 [RapidOCR] base.py:23: Using engine_name: onnxruntime
[INFO] 2026-06-23 12:51:44,045 [RapidOCR] download_file.py:60: File exists and is valid: /usr/local/lib/python3.12/dist-packages/rapidocr/models/PP-OCRv6_det_small.onnx
[INFO] 2026-06-23 12:51:44,046 [RapidOCR] main.py:63: Using /usr/local/lib/python3.12/dist-packages/rapidocr/models/PP-OCRv6_det_small.onnx
[INFO] 2026-06-23 12:51:44,127 [RapidOCR] base.py:23: Using engine_name: onnxruntime
[INFO] 2026-06-23 12:51:44,129 [RapidOCR] download_file.py:60: File exists and is valid: /usr/local/lib/python3.12/dist-packages/rapidocr/models/ch_ppocr_mobile_v2.0_cls_mobile.onnx
[INFO] 2026-06-23 12:51:44,129 [RapidOCR] main.py:63: Using /usr/local/lib/python3.12/dist-packages/rapidocr/models/ch_ppocr_mobile_v2.0_cls_mobile.onnx
[INFO] 2026-06-23 12:51:44,190 [RapidOCR] base.py:23: Using engine_name: onnxruntime
[INFO] 2026-06-23 12:51:44,260 [RapidOCR] download_file.py:60: File exists and is valid: /usr/local/lib/python3.12/dist-packages/rapidocr/models/PP-OCRv6_rec_small.onnx
[INFO] 2026-06-23 12:51:44,260 [RapidOCR] main.py:63: Using /usr/local/lib/python3.12/dist-packages/rapidocr/models/PP-OCRv6_rec_small.onnx
Success! rapidocr is installed correctly!
```

--------------------------------

### Output of rapidocr download_models

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/usage

Example output from running `rapidocr download_models`, showing the download initiation, size, and save location.

```text
[INFO] 2026-03-24 10:37:01,625 [RapidOCR] download_file.py:68: Initiating download: https://www.modelscope.cn/models/RapidAI/RapidOCR/resolve/v3.7.0/onnx/PP-OCRv4/cls/ch_ppocr_mobile_v2.0_cls_infer.onnx
[INFO] 2026-03-24 10:37:03,640 [RapidOCR] download_file.py:82: Download size: 0.56MB
[INFO] 2026-03-24 10:37:04,364 [RapidOCR] download_file.py:95: Successfully saved to: /Users/xxxx/RapidOCR/python/test_models/ch_ppocr_mobile_v2.0_cls_infer.onnx

```

--------------------------------

### 运行 main.py

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr_web/ocrweb_multi

在项目根目录下运行 main.py 启动服务，默认监听 8001 端口。

```bash
python main.py

```

--------------------------------

### Install MNN with pip

Source: https://rapidai.github.io/RapidOCRDocs/latest/install_usage/rapidocr/how_to_use_infer_engine

Install the MNN package using pip. Required for using MNN as the inference engine.

```bash
pip install MNN

```
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