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@@ -53,7 +53,7 @@ Including [image classification](examples/vision/classification), [object detect
## 🌠 Recent updates
- ✨✨✨ In **2023.01.17** we released [**YOLOv8**](./examples/vision/detection/paddledetection/) for deployment on FastDeploy series hardware, which includes [**Paddle YOLOv8**](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8) and [**ultralytics YOLOv8**](https://github.com/ultralytics/ultralytics)
- Deployable hardware for [**Paddle YOLOv8**](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)：[**Intel CPU**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**NVIDIA GPU**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**Jetson**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**Phytium**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**Kunlunxin**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**HUAWEI Ascend**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**ARM CPU**](./examples/vision/detection/paddledetection/cpp/infer_yolov8.cc), both **Python** deployments and **C++** deployments are included. [**Sophgo TPU**]() and [**RK3588**]() are being updated
- Deployable hardware for [**Paddle YOLOv8**](https://github.com/PaddlePaddle/PaddleYOLO/tree/release/2.5/configs/yolov8)：[**Intel CPU**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**NVIDIA GPU**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**Jetson**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**Phytium**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**Kunlunxin**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**HUAWEI Ascend**](./examples/vision/detection/paddledetection/python/infer_yolov8.py), [**ARM CPU**](./examples/vision/detection/paddledetection/cpp/infer_yolov8.cc),[**RK3588**](./examples/vision/detection/paddledetection/rknpu2) and [**Sophgo TPU**](./examples/vision/detection/paddledetection/sophgo),including **Python** deployments and **C++** deployments.
- Deployable hardware for [**ultralytics YOLOv8**](https://github.com/ultralytics/ultralytics): [**Intel CPU**](./examples/vision/detection/yolov8), [**NVIDIA GPU**](./examples/vision/detection/yolov8), [**Jetson**](./examples/vision/detection/yolov8), both **Python** deployments and **C++** deployments are included
- FastDeploy one-line model API switch, which can achieve **YOLOv8**, **PP-YOLOE+**, **YOLOv5** and other model performance comparison