ncnn-android-ppocrv5

PPOCRv5

This is a sample ncnn android project, it depends on ncnn library and opencv

https://github.com/Tencent/ncnn

https://github.com/nihui/opencv-mobile

android apk file download

https://github.com/nihui/ncnn-android-ppocrv5/releases/latest

how to build and run

step1

https://github.com/Tencent/ncnn/releases

• Download ncnn-YYYYMMDD-android-vulkan.zip or build ncnn for android yourself
• Extract ncnn-YYYYMMDD-android-vulkan.zip into app/src/main/jni and change the ncnn_DIR path to yours in app/src/main/jni/CMakeLists.txt

step2

https://github.com/nihui/opencv-mobile

• Download opencv-mobile-XYZ-android.zip
• Extract opencv-mobile-XYZ-android.zip into app/src/main/jni and change the OpenCV_DIR path to yours in app/src/main/jni/CMakeLists.txt

step3

• Open this project with Android Studio, build it and enjoy!

some notes

• Android ndk camera is used for best efficiency
• Crash may happen on very old devices for lacking HAL3 camera interface
• All models are manually modified to accept dynamic input shape
• Most small models run slower on GPU than on CPU, this is common
• FPS may be lower in dark environment because of longer camera exposure time

screenshot

guidelines for converting PPOCRv5 models

1. install paddleocr

   pip install paddlepaddle==3.0.0
   pip install paddleocr==3.0.0
   paddlex --install paddle2onnx

2. test paddleocr and export onnx models

   paddleocr ocr -i test.png
   paddlex --paddle2onnx --paddle_model_dir ~/.paddlex/official_models/PP-OCRv5_mobile_det --onnx_model_dir PP-OCRv5_mobile_det
   paddlex --paddle2onnx --paddle_model_dir ~/.paddlex/official_models/PP-OCRv5_mobile_rec --onnx_model_dir PP-OCRv5_mobile_rec

3. convert onnx models to ncnn with pnnx tool

   pip install -U pnnx
   pnnx PP-OCRv5_mobile_det.onnx inputshape=[1,3,320,320] inputshape2=[1,3,256,256]
   pnnx PP-OCRv5_mobile_rec.onnx inputshape=[1,3,48,160] inputshape2=[1,3,48,256]
   pnnx PP-OCRv5_server_det.onnx inputshape=[1,3,320,320] inputshape2=[1,3,256,256] fp16=0
   pnnx PP-OCRv5_server_rec.onnx inputshape=[1,3,48,160] inputshape2=[1,3,48,256] fp16=0