mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-05 16:48:03 +08:00

* 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
39 lines
2.1 KiB
Markdown
Executable File
39 lines
2.1 KiB
Markdown
Executable File
English | [简体中文](README_CN.md)
|
|
# YOLOv6 Quantification Model C++ Deployment Example
|
|
|
|
This directory provides examples that `infer.cc` fast finishes the deployment of YOLOv6 quantification models on CPU/GPU.
|
|
|
|
## Prepare the deployment
|
|
### FastDeploy Environment Preparation
|
|
- 1. Software and hardware should meet the requirements. Please refer to [FastDeploy Environment Requirements](../../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
|
|
- 2. Install FastDeploy Python whl package. Refer to [FastDeploy Python Installation](../../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
|
|
|
|
### Prepare the quantification model
|
|
- 1. Users can directly deploy quantized models provided by FastDeploy.
|
|
- 2. ii. Or users can use the [One-click auto-compression tool](../../../../../../tools/common_tools/auto_compression/) provided by FastDeploy to automatically conduct quantification model for deployment.
|
|
|
|
## Example: quantized YOLOv6 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.
|
|
```bash
|
|
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 yolov6 quantification model files and test images provided by FastDeploy
|
|
wget https://bj.bcebos.com/paddlehub/fastdeploy/yolov6s_qat_model_new.tar
|
|
tar -xvf yolov6s_qat_model.tar
|
|
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
|
|
|
|
|
|
# Use ONNX Runtime quantification model on CPU
|
|
./infer_demo yolov6s_qat_model 000000014439.jpg 0
|
|
# Use TensorRT quantification model on GPU
|
|
./infer_demo yolov6s_qat_model 000000014439.jpg 1
|
|
# Use Paddle-TensorRT quantification model on GPU
|
|
./infer_demo yolov6s_qat_model 000000014439.jpg 2
|
|
```
|