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@@ -49,11 +49,11 @@ Including image classification, object detection, image segmentation, face detec
- **🖥️ Server-side and Cloud Deployment: Support more CV models, improve deployment performance**
- Support [PaddleClas](./examples/vision/classification/paddleclas/serving) model service-based deployment;
- Support [Stable Diffusion](./examples/multimodal/stable_diffusion) model deployment;
- Upgrade PaddleClas、PaddleDetection、YOLOv5 deployment code to support predict and batch_predict;
- Upgrade PaddleClas、PaddleDetection、YOLOv5 deployment code to support `predict` and `batch_predict`;
- Add the Pad function operator for the FDTensor to support Padding of the input during batch prediction;
- Add Python API to_dlpack interface for FDTensor to support copyless transfer of FDTensor between frameworks.
- **📱 Mobile and Edge Device Deployment: support new backend，support more CV model**
- Support Paddle Lite TIM-VX for supporting hardware such as Rockchip RV1109,RV1126, RK1808, Amlogic A311D, etc. And provide a seamless deployment experience with other inference engines include Paddle Inference、Paddle Inference TensorRT、Paddle Lite、TensorRT、OpenVINO、ONNX Runtime、RKNPU2;
- Integrate Paddle Lite TIM-VX for supporting hardware such as Rockchip RV1109,RV1126, RK1808, Amlogic A311D, etc. And provide a seamless deployment experience with other inference engines include Paddle Inference、Paddle Inference TensorRT、Paddle Lite、TensorRT、OpenVINO、ONNX Runtime、RKNPU2;
- Support Image classification model [ResNet50_vd](./examples/vision/classification/paddleclas/rk1126/cpp) on Rockchip RV1126;
- Support Face detection model [SCRFD](./examples/vision/facedet/scrfd/rknpu2) on Rockchip RK3588, RK3568 and other hardware.