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# OpenCV Zoo and Benchmark
A zoo for models tuned for OpenCV DNN with benchmarks on different platforms.
Guidelines:
- Clone this repo to download all models and demo scripts:
```shell
# Install git-lfs from https://git-lfs.github.com/
git clone https://github.com/opencv/opencv_zoo && cd opencv_zoo
git lfs install
git lfs pull
```
- To run benchmarks on your hardware settings, please refer to [benchmark/README](./benchmark/README.md).
## Models & Benchmark Results
| Model | Input Size | INTEL-CPU | RPI-CPU | JETSON-GPU |
|-------|------------|-----------|---------|------------|
| [YuNet](./models/face_detection_yunet) | 160x120 | 1.45 | 6.22 | 12.18 |
| [DB-IC15](./models/text_detection_db) | 640x480 | 142.91 | 2835.91 | 208.41 |
| [DB-TD500](./models/text_detection_db) | 640x480 | 142.91 | 2841.71 | 210.51 |
| [CRNN-EN](./models/text_recognition_crnn) | 100x32 | 50.21 | 234.32 | 196.15 |
| [CRNN-CN](./models/text_recognition_crnn) | 100x32 | 73.52 | 322.16 | 239.76 |
| [SFace](./models/face_recognition_sface) | 112x112 | 8.65 | 99.20 | 24.88 |
| [PP-ResNet](./models/image_classification_ppresnet) | 224x224 | 56.05 | 602.58 | 98.64 |
| [PP-HumanSeg](./models/human_segmentation_pphumanseg) | 192x192 | 19.92 | 105.32 | 67.97 |
| [WeChatQRCode](./models/qrcode_wechatqrcode) | 100x100 | 7.04 | 37.68 | --- |
| [DaSiamRPN](./models/object_tracking_dasiamrpn) | 1280x720 | 36.15 | 705.48 | 76.82 |
| [YoutuReID](./models/person_reid_youtureid) | 128x256 | 35.81 | 521.98 | 90.07 |
Hardware Setup:
- `INTEL-CPU`: [Intel Core i7-5930K](https://www.intel.com/content/www/us/en/products/sku/82931/intel-core-i75930k-processor-15m-cache-up-to-3-70-ghz/specifications.html) @ 3.50GHz, 6 cores, 12 threads.
- `RPI-CPU`: [Raspberry Pi 4B](https://www.raspberrypi.com/products/raspberry-pi-4-model-b/specifications/), Broadcom BCM2711, Quad core Cortex-A72 (ARM v8) 64-bit SoC @ 1.5GHz.
- `JETSON-GPU`: [NVIDIA Jetson Nano B01](https://developer.nvidia.com/embedded/jetson-nano-developer-kit), 128-core NVIDIA Maxwell GPU.
***Important Notes***:
- The data under each column of hardware setups on the above table represents the elapsed time of an inference (preprocess, forward and postprocess).
- The time data is the median of 10 runs after some warmup runs. Different metrics may be applied to some specific models.
- Batch size is 1 for all benchmark results.
- `---` represents the model is not availble to run on the device.
- View [benchmark/config](./benchmark/config) for more details on benchmarking different models.
## License
OpenCV Zoo is licensed under the [Apache 2.0 license](./LICENSE). Please refer to licenses of different models.
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