!!! warning The three packages `rapidocr_onnxruntime`, `rapidocr_openvino` and `rapidocr_paddle` are gradually being retired. Development continues on `rapidocr`. #### Introduction `rapidocr` merges `rapidocr_onnxruntime`, `rapidocr_openvino` and `rapidocr_paddle`, and adds support for PyTorch inference. In `rapidocr>=2.0.0,<=2.0.5`, the ONNX Runtime CPU build is used as the default inference engine. You can install another inference engine and switch to GPU inference through the corresponding parameters, which later pages describe in detail. Starting from `rapidocr>=2.0.6`, ONNX Runtime is no longer a dependency, although it remains the default inference engine. From that version onwards you need to install the inference engine you want to use yourself. #### Installation If all goes well, a single command is enough to get started. The `rapidocr` package is about 27.2 MB and contains three models: text detection, text line orientation classification and text recognition. The small models are compact enough to be bundled into the wheel, so pip install is all that is needed. ```bash linenums="1" pip install rapidocr onnxruntime ``` If the download is slow in your region, specify a closer mirror. For example, using the Tsinghua mirror: ```bash linenums="1" pip install rapidocr -i https://pypi.tuna.tsinghua.edu.cn/simple/ ``` #### Verify the installation === "`rapidocr>=2.0.3`" ```bash linenums="1" hl_lines="11" $ rapidocr check # The installation is correct when you see the following output [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! ``` === "`rapidocr>=2.0.0,<2.0.2`" Run the following command. The installation succeeded if the recognized text is printed in the terminal. ```bash linenums="1" rapidocr -img "https://www.modelscope.cn/models/RapidAI/RapidOCR/resolve/master/resources/test_files/ch_en_num.jpg" --vis_res ``` !!! info If a dependency fails to install, install that dependency on its own first and then install `rapidocr`. The dependencies are: ```txt linenums="1" 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 ```