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Installation

PyPI

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.

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pip install rapidocr onnxruntime

If the download is slow in your region, specify a closer mirror. For example, using the Tsinghua mirror:

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pip install rapidocr -i https://pypi.tuna.tsinghua.edu.cn/simple/

Verify the installation

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$ 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!

Run the following command. The installation succeeded if the recognized text is printed in the terminal.

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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:

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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

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