PP-OCRv3: More Attempts for the Improvement of Ultra Lightweight OCR System.

Note:

• The int8 quantization model may produce unstable results due to some loss of accuracy.
• Original Paddle Models source of English: here.
• Original Paddle Models source of Chinese: here.
• IC15 in the filename means the model is trained on IC15 dataset, which can detect English text instances only.
• TD500 in the filename means the model is trained on TD500 dataset, which can detect both English & Chinese instances.
• Visit https://docs.opencv.org/master/d4/d43/tutorial_dnn_text_spotting.html for more information.
• text_detection_xx_ppocrv3_2023may_int8bq.onnx represents the block-quantized version in int8 precision and is generated using block_quantize.py with block_size=64.

Run the following command to try the demo:

# detect on camera input
python demo.py
# detect on an image
python demo.py --input /path/to/image -v

# get help regarding various parameters
python demo.py --help

Install latest OpenCV and CMake >= 3.24.0 to get started with:

# A typical and default installation path of OpenCV is /usr/local
cmake -B build -D OPENCV_INSTALLATION_PATH=/path/to/opencv/installation .
cmake --build build
# detect on camera input
./build/opencv_zoo_text_detection_ppocr -m=/path/to/model
# detect on an image
./build/opencv_zoo_text_detection_ppocr -m=/path/to/model -i=/path/to/image -v
# get help messages
./build/opencv_zoo_text_detection_ppocr -h

All files in this directory are licensed under Apache 2.0 License.

• https://arxiv.org/abs/2206.03001
• https://github.com/PaddlePaddle/PaddleOCR
• https://docs.opencv.org/master/d4/d43/tutorial_dnn_text_spotting.html