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 withblock_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.