| # Nanodet | |
| Nanodet: NanoDet is a FCOS-style one-stage anchor-free object detection model which using Generalized Focal Loss as classification and regression loss.In NanoDet-Plus, we propose a novel label assignment strategy with a simple assign guidance module (AGM) and a dynamic soft label assigner (DSLA) to solve the optimal label assignment problem in lightweight model training. | |
| **Note**: | |
| - This version of nanodet: Nanodet-m-plus-1.5x_416 | |
| - `object_detection_nanodet_2022nov_int8bq.onnx` represents the block-quantized version in int8 precision and is generated using [block_quantize.py](../../tools/quantize/block_quantize.py) with `block_size=64`. | |
| ## Demo | |
| ### Python | |
| Run the following command to try the demo: | |
| ```shell | |
| # detect on camera input | |
| python demo.py | |
| # detect on an image | |
| python demo.py --input /path/to/image -v | |
| ``` | |
| Note: | |
| - image result saved as "result.jpg" | |
| ### 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 camera input | |
| ./build/opencv_zoo_object_detection_nanodet | |
| # detect on an image | |
| ./build/opencv_zoo_object_detection_nanodet -i=/path/to/image | |
| # get help messages | |
| ./build/opencv_zoo_object_detection_nanodet -h | |
| ``` | |
| ## Results | |
| Here are some of the sample results that were observed using the model, | |
|  | |
|  | |
| Check [benchmark/download_data.py](../../benchmark/download_data.py) for the original images. | |
| Video inference result, | |
|  | |
| ## Model metrics: | |
| The model is evaluated on [COCO 2017 val](https://cocodataset.org/#download). Results are showed below: | |
| <table> | |
| <tr><th>Average Precision </th><th>Average Recall</th></tr> | |
| <tr><td> | |
| | area | IoU | Average Precision(AP) | | |
| |:-------|:------|:------------------------| | |
| | all | 0.50:0.95 | 0.304 | | |
| | all | 0.50 | 0.459 | | |
| | all | 0.75 | 0.317 | | |
| | small | 0.50:0.95 | 0.107 | | |
| | medium | 0.50:0.95 | 0.322 | | |
| | large | 0.50:0.95 | 0.478 | | |
| </td><td> | |
| area | IoU | Average Recall | | |
| |:-------|:------|:----------------| | |
| | all | 0.50:0.95 | 0.278 | | |
| | all | 0.50:0.95 | 0.434 | | |
| | all | 0.50:0.95 | 0.462 | | |
| | small | 0.50:0.95 | 0.198 | | |
| | medium | 0.50:0.95 | 0.510 | | |
| | large | 0.50:0.95 | 0.702 | | |
| </td></tr> </table> | |
| | class | AP50 | mAP | class | AP50 | mAP | | |
| |:--------------|:-------|:------|:---------------|:-------|:------| | |
| | person | 67.5 | 41.8 | bicycle | 35.4 | 18.8 | | |
| | car | 45.0 | 25.4 | motorcycle | 58.9 | 33.1 | | |
| | airplane | 77.3 | 58.9 | bus | 68.8 | 56.4 | | |
| | train | 81.1 | 60.5 | truck | 38.6 | 24.7 | | |
| | boat | 35.5 | 16.7 | traffic light | 30.5 | 14.0 | | |
| | fire hydrant | 69.8 | 54.5 | stop sign | 60.9 | 54.6 | | |
| | parking meter | 55.1 | 38.5 | bench | 26.8 | 15.9 | | |
| | bird | 38.3 | 23.6 | cat | 82.5 | 62.1 | | |
| | dog | 67.0 | 51.4 | horse | 64.3 | 44.2 | | |
| | sheep | 57.7 | 35.8 | cow | 61.2 | 39.9 | | |
| | elephant | 79.9 | 56.2 | bear | 81.8 | 63.0 | | |
| | zebra | 85.4 | 59.5 | giraffe | 84.1 | 59.9 | | |
| | backpack | 12.4 | 5.9 | umbrella | 46.5 | 28.8 | | |
| | handbag | 8.4 | 3.7 | tie | 35.2 | 19.6 | | |
| | suitcase | 38.1 | 23.8 | frisbee | 60.7 | 43.9 | | |
| | skis | 30.5 | 14.5 | snowboard | 32.3 | 18.2 | | |
| | sports ball | 37.6 | 24.5 | kite | 51.1 | 30.4 | | |
| | baseball bat | 28.9 | 13.6 | baseball glove | 40.1 | 21.6 | | |
| | skateboard | 59.4 | 35.2 | surfboard | 47.9 | 26.6 | | |
| | tennis racket | 55.2 | 30.5 | bottle | 34.7 | 20.2 | | |
| | wine glass | 27.8 | 16.3 | cup | 35.5 | 23.7 | | |
| | fork | 25.9 | 14.8 | knife | 10.9 | 5.6 | | |
| | spoon | 8.7 | 4.1 | bowl | 42.8 | 29.4 | | |
| | banana | 35.5 | 18.5 | apple | 19.4 | 12.9 | | |
| | sandwich | 46.7 | 33.4 | orange | 35.2 | 25.9 | | |
| | broccoli | 36.4 | 19.1 | carrot | 30.9 | 17.8 | | |
| | hot dog | 42.7 | 29.3 | pizza | 61.0 | 44.9 | | |
| | donut | 47.3 | 34.0 | cake | 39.9 | 24.4 | | |
| | chair | 28.8 | 16.1 | couch | 60.5 | 42.6 | | |
| | potted plant | 29.0 | 15.3 | bed | 63.3 | 46.0 | | |
| | dining table | 39.6 | 27.5 | toilet | 71.3 | 55.3 | | |
| | tv | 66.5 | 48.1 | laptop | 62.6 | 46.9 | | |
| | mouse | 63.5 | 44.1 | remote | 19.8 | 10.3 | | |
| | keyboard | 62.1 | 41.5 | cell phone | 33.7 | 22.8 | | |
| | microwave | 54.9 | 39.6 | oven | 48.1 | 30.4 | | |
| | toaster | 30.0 | 16.4 | sink | 44.5 | 27.8 | | |
| | refrigerator | 63.2 | 46.1 | book | 18.4 | 7.3 | | |
| | clock | 57.8 | 35.8 | vase | 33.7 | 22.1 | | |
| | scissors | 27.8 | 17.8 | teddy bear | 54.1 | 35.4 | | |
| | hair drier | 2.9 | 1.1 | toothbrush | 13.1 | 8.2 | | |
| ## License | |
| All files in this directory are licensed under [Apache 2.0 License](./LICENSE). | |
| #### Contributor Details | |
| - Google Summer of Code'22 | |
| - Contributor: Sri Siddarth Chakaravarthy | |
| - Github Profile: https://github.com/Sidd1609 | |
| - Organisation: OpenCV | |
| - Project: Lightweight object detection models using OpenCV | |
| ## Reference | |
| - Nanodet: https://zhuanlan.zhihu.com/p/306530300 | |
| - Nanodet Plus: https://zhuanlan.zhihu.com/p/449912627 | |
| - Nanodet weight and scripts for training: https://github.com/RangiLyu/nanodet | |