apps/FastDeploy
1
0
Fork 0
mirror of https://github.com/PaddlePaddle/FastDeploy.git synced 2025-10-05 16:48:03 +08:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity
Files
6be2c0367b91c6228c9ca5dec77c3c9138fb032e
FastDeploy/examples/vision/detection/yolov7/quantize/cpp
History
HCQ14 61c2f87e0c [Doc] Update English version of some documents (#1084) 
* Create README_CN.md

* Update README.md

* Update README_CN.md

* Create README_CN.md

* Update README.md

* Create README_CN.md

* Update README.md

* Create README_CN.md

* Update README.md

* Create README_CN.md

* Update README.md

* Create README_CN.md

* Update README.md

* Create README_CN.md

* Update README.md

* Create README_CN.md

* Update README.md

* Update README.md

* Update README_CN.md

* Create README_CN.md

* Update README.md

* Update README.md

* Update and rename README_en.md to README_CN.md

* Update WebDemo.md

* Update and rename WebDemo_en.md to WebDemo_CN.md

* Update and rename DEVELOPMENT_cn.md to DEVELOPMENT_CN.md

* Update DEVELOPMENT_CN.md

* Update DEVELOPMENT.md

* Update RNN.md

* Update and rename RNN_EN.md to RNN_CN.md

* Update README.md

* Update and rename README_en.md to README_CN.md

* Update README.md

* Update and rename README_en.md to README_CN.md

* Update README.md

* Update README_cn.md

* Rename README_cn.md to README_CN.md

* Update README.md

* Update README_cn.md

* Rename README_cn.md to README_CN.md

* Update export.md

* Update and rename export_EN.md to export_CN.md

* Update README.md

* Update README.md

* Create README_CN.md

* Update README.md

* Update README.md

* Update kunlunxin.md

* Update classification_result.md

* Update classification_result_EN.md

* Rename classification_result_EN.md to classification_result_CN.md

* Update detection_result.md

* Update and rename detection_result_EN.md to detection_result_CN.md

* Update face_alignment_result.md

* Update and rename face_alignment_result_EN.md to face_alignment_result_CN.md

* Update face_detection_result.md

* Update and rename face_detection_result_EN.md to face_detection_result_CN.md

* Update face_recognition_result.md

* Update and rename face_recognition_result_EN.md to face_recognition_result_CN.md

* Update headpose_result.md

* Update and rename headpose_result_EN.md to headpose_result_CN.md

* Update keypointdetection_result.md

* Update and rename keypointdetection_result_EN.md to keypointdetection_result_CN.md

* Update matting_result.md

* Update and rename matting_result_EN.md to matting_result_CN.md

* Update mot_result.md

* Update and rename mot_result_EN.md to mot_result_CN.md

* Update ocr_result.md

* Update and rename ocr_result_EN.md to ocr_result_CN.md

* Update segmentation_result.md

* Update and rename segmentation_result_EN.md to segmentation_result_CN.md

* Update README.md

* Update README.md

* Update quantize.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md

* Update README.md
2023-01-06 18:01:34 +08:00
..
CMakeLists.txt
Add Examples to deploy quantized models (#342)
2022-10-14 13:35:45 +08:00
infer.cc
[Other] Update old Api to new ones (#861)
2022-12-14 17:25:58 +08:00
README_CN.md
[Doc] Update English version of some documents (#1084)
2023-01-06 18:01:34 +08:00
README.md
[Doc] Update English version of some documents (#1084)
2023-01-06 18:01:34 +08:00

README.md

English | 简体中文

YOLOv7 Quantification Model C++ Deployment Example

This directory provides examples that infer.cc fast finishes the deployment of YOLOv7 quantification models on CPU/GPU.

Prepare the deployment

FastDeploy Environment Preparation

Prepare the quantification model

    1. Users can directly deploy quantized models provided by FastDeploy.
    1. Or users can use the One-click auto-compression tool provided by FastDeploy to automatically conduct quantification model for deployment.

Example: quantized YOLOv7 model

The compilation and deployment can be completed by executing the following command in this directory. FastDeploy version 0.7.0 or above (x.x.x>=0.7.0) is required to support this model.

mkdir build
cd build
# Download the FastDeploy precompiled library. Users can choose your appropriate version in the `FastDeploy  Precompiled Library` mentioned above 
wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-x.x.x.tgz
tar xvf fastdeploy-linux-x64-x.x.x.tgz
cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-x.x.x
make -j

# Download yolov7 quantification model files and test images provided by FastDeploy
wget https://bj.bcebos.com/paddlehub/fastdeploy/yolov7_quant.tar
tar -xvf yolov7_quant.tar
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg


# Use ONNX Runtime quantification model on CPU
./infer_demo yolov7_quant 000000014439.jpg 0
# Use TensorRT quantification model on GPU
./infer_demo yolov7_quant 000000014439.jpg 1
# Use Paddle-TensorRT quantification model on GPU
./infer_demo yolov7_quant 000000014439.jpg 2