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README.md
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@@ -18,7 +18,7 @@ English | [简体中文](README_ch.md)
**⚡️FastDeploy** is an **accessible and efficient** deployment Development Toolkit. It covers 🔥**hot AI models** in the industry and provides 📦**out-of-the-box** deployment experience. It covers image classification, object detection, image segmentation, face detection, face recognition, human keypoint detection, OCR, semantic understanding and other tasks to meet developers‘ industrial deployment needs for **multi-scenario**, **multi-hardware** and **multi-platform** .
**⚡️FastDeploy** is an **accessible and efficient** deployment Development Toolkit. It covers 🔥**hot AI models** in the industry and provides 📦**out-of-the-box** deployment experience. It covers image classification, object detection, image segmentation, face detection, face recognition, human keypoint detection, OCR, semantic understanding and other tasks to meet developers‘ industrial deployment needs for **multi-scenario**, **multi-hardware**, **multi-platform** .
| Potrait Segmentation | Image Matting | Semantic Segmentation | Real-Time Matting |
|:----------------------------------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------------------------------------:|:------------------------------------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------------------------------------------------------------:|
@@ -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
@@ -101,11 +101,12 @@ 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")
@@ -115,7 +116,6 @@ 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