diff --git a/README.md b/README.md index c15ff4185..740e4d8da 100644 --- a/README.md +++ b/README.md @@ -34,11 +34,11 @@ English | [简体中文](README_ch.md) - **New server-side deployment upgrade: faster inference performance, support more visual model** - Release high-performance inference engine SDK based on x86 CPUs and NVIDIA GPUs, with significant increase in inference speed - Integrate Paddle Inference, ONNXRuntime, TensorRT and other inference engines and provide a seamless deployment experience - - Supports full range of object detection models such as YOLOv7, YOLOv6, YOLOv5, PP-YOLOE and provides [End-To-End Deployment Demos]](examples/vision/detection/) + - Supports full range of object detection models such as YOLOv7, YOLOv6, YOLOv5, PP-YOLOE and provides [End-To-End Deployment Demos](examples/vision/detection/) - Support over 40 key models and [Demo Examples](examples/vision/) including face detection, face recognition, real-time portrait matting, image segmentation. - Support deployment in both Python and C++ - **Supports Rexchip, Amlogic, NXP and other NPU chip deployment capabilities on end-side deployment** - - Release Lightweight Object Detection [Picodet-NPU Deployment Demo](https://github.com/PaddlePaddle/Paddle-Lite-Demo/tree/develop/object_detection/linux/picodet_ detection), providing the full quantized inference capability for INT8. + - Release Lightweight Object Detection [Picodet-NPU Deployment Demo](https://github.com/PaddlePaddle/Paddle-Lite-Demo/tree/develop/object_detection/linux/picodet_detection), providing the full quantized inference capability for INT8. ## Contents @@ -101,12 +101,11 @@ wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/0000000 * Test inference resultsTest inference results - ```python - # For deployment of GPU/TensorRT, please refer to examples/vision/detection/paddledetection/python - import cv2 - import fastdeploy.vision as vision - ``` - +```python +# For deployment of GPU/TensorRT, please refer to examples/vision/detection/paddledetection/python +import cv2 +import fastdeploy.vision as vision + model = vision.detection.PPYOLOE("ppyoloe_crn_l_300e_coco/model.pdmodel", "ppyoloe_crn_l_300e_coco/model.pdiparams", "ppyoloe_crn_l_300e_coco/infer_cfg.yml") @@ -116,6 +115,7 @@ print(result) vis_im = vision.vis_detection(im, result, score_threshold=0.5) cv2.imwrite("vis_image.jpg", vis_im) +``` ### A Quick Start for C++ SDK