| # ResNet | |
| Deep Residual Learning for Image Recognition | |
| This model is ported from [PaddleHub](https://github.com/PaddlePaddle/PaddleHub) using [this script from OpenCV](https://github.com/opencv/opencv/blob/master/samples/dnn/dnn_model_runner/dnn_conversion/paddlepaddle/paddle_resnet50.py). | |
| Results of accuracy evaluation with [tools/eval](../../tools/eval). | |
| | Models | Top-1 Accuracy | Top-5 Accuracy | | |
| | --------------- | -------------- | -------------- | | |
| | PP-ResNet | 82.28 | 96.15 | | |
| | PP-ResNet quant | 0.22 | 0.96 | | |
| \*: 'quant' stands for 'quantized'. | |
| ## Demo | |
| Run the following commands to try the demo: | |
| ### Python | |
| ```shell | |
| python demo.py --input /path/to/image | |
| # get help regarding various parameters | |
| python demo.py --help | |
| ``` | |
| ### C++ | |
| Install latest OpenCV and CMake >= 3.24.0 to get started with: | |
| ```shell | |
| # 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 an image | |
| ./build/opencv_zoo_image_classification_ppresnet -i=/path/to/image | |
| # detect on an image and display top N classes | |
| ./build/opencv_zoo_image_classification_ppresnet -i=/path/to/image -k=N | |
| # get help messages | |
| ./build/opencv_zoo_image_classification_ppresnet -h | |
| ``` | |
| ## License | |
| All files in this directory are licensed under [Apache 2.0 License](./LICENSE). | |
| ## Reference | |
| - https://arxiv.org/abs/1512.03385 | |
| - https://github.com/opencv/opencv/tree/master/samples/dnn/dnn_model_runner/dnn_conversion/paddlepaddle | |
| - https://github.com/PaddlePaddle/PaddleHub | |