mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-11-01 04:12:58 +08:00
866d044898
* model done, CLA fix * remove letter_box and ConvertAndPermute, use resize hwc2chw and convert in preprocess * remove useless values in preprocess * remove useless values in preprocess * fix reviewed problem * fix reviewed problem pybind * fix reviewed problem pybind * postprocess fix * add test_fastestdet.py, coco_val2017_500 fixed done, ready to review * fix reviewed problem * python/.../fastestdet.py * fix infer.cc, preprocess, python/fastestdet.py * fix examples/python/infer.py
88 lines
3.4 KiB
Markdown
88 lines
3.4 KiB
Markdown
# FastestDet C++部署示例
|
||
|
||
本目录下提供`infer.cc`快速完成FastestDet在CPU/GPU，以及GPU上通过TensorRT加速部署的示例。
|
||
|
||
在部署前，需确认以下两个步骤
|
||
|
||
- 1. 软硬件环境满足要求，参考[FastDeploy环境要求](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
|
||
- 2. 根据开发环境，下载预编译部署库和samples代码，参考[FastDeploy预编译库](../../../../../docs/cn/build_and_install/download_prebuilt_libraries.md)
|
||
|
||
以Linux上CPU推理为例，在本目录执行如下命令即可完成编译测试
|
||
|
||
```bash
|
||
mkdir build
|
||
cd build
|
||
wget https://bj.bcebos.com/fastdeploy/release/cpp/fastdeploy-linux-x64-1.0.3.tgz
|
||
tar xvf fastdeploy-linux-x64-1.0.3.tgz
|
||
cmake .. -DFASTDEPLOY_INSTALL_DIR=${PWD}/fastdeploy-linux-x64-1.0.3
|
||
make -j
|
||
|
||
#下载官方转换好的FastestDet模型文件和测试图片
|
||
wget https://bj.bcebos.com/paddlehub/fastdeploy/FastestDet.onnx
|
||
wget https://gitee.com/paddlepaddle/PaddleDetection/raw/release/2.4/demo/000000014439.jpg
|
||
|
||
|
||
# CPU推理
|
||
./infer_demo FastestDet.onnx 000000014439.jpg 0
|
||
# GPU推理
|
||
./infer_demo FastestDet.onnx 000000014439.jpg 1
|
||
# GPU上TensorRT推理
|
||
./infer_demo FastestDet.onnx 000000014439.jpg 2
|
||
```
|
||
|
||
运行完成可视化结果如下图所示
|
||
|
||
<img width="640" src="https://user-images.githubusercontent.com/44280887/206176291-61eb118b-391b-4431-b79e-a393b9452138.jpg">
|
||
|
||
以上命令只适用于Linux或MacOS, Windows下SDK的使用方式请参考:
|
||
- [如何在Windows中使用FastDeploy C++ SDK](../../../../../docs/cn/faq/use_sdk_on_windows.md)
|
||
|
||
## FastestDet C++接口
|
||
|
||
### FastestDet类
|
||
|
||
```c++
|
||
fastdeploy::vision::detection::FastestDet(
|
||
const string& model_file,
|
||
const string& params_file = "",
|
||
const RuntimeOption& runtime_option = RuntimeOption(),
|
||
const ModelFormat& model_format = ModelFormat::ONNX)
|
||
```
|
||
|
||
FastestDet模型加载和初始化，其中model_file为导出的ONNX模型格式。
|
||
|
||
**参数**
|
||
|
||
> * **model_file**(str): 模型文件路径
|
||
> * **params_file**(str): 参数文件路径，当模型格式为ONNX时，此参数传入空字符串即可
|
||
> * **runtime_option**(RuntimeOption): 后端推理配置，默认为None，即采用默认配置
|
||
> * **model_format**(ModelFormat): 模型格式，默认为ONNX格式
|
||
|
||
#### Predict函数
|
||
|
||
> ```c++
|
||
> FastestDet::Predict(cv::Mat* im, DetectionResult* result,
|
||
> float conf_threshold = 0.65,
|
||
> float nms_iou_threshold = 0.45)
|
||
> ```
|
||
>
|
||
> 模型预测接口，输入图像直接输出检测结果。
|
||
>
|
||
> **参数**
|
||
>
|
||
> > * **im**: 输入图像，注意需为HWC，BGR格式
|
||
> > * **result**: 检测结果，包括检测框，各个框的置信度, DetectionResult说明参考[视觉模型预测结果](../../../../../docs/api/vision_results/)
|
||
> > * **conf_threshold**: 检测框置信度过滤阈值
|
||
> > * **nms_iou_threshold**: NMS处理过程中iou阈值
|
||
|
||
### 类成员变量
|
||
#### 预处理参数
|
||
用户可按照自己的实际需求，修改下列预处理参数，从而影响最终的推理和部署效果
|
||
|
||
> > * **size**(vector<int>): 通过此参数修改预处理过程中resize的大小，包含两个整型元素，表示[width, height], 默认值为[352, 352]
|
||
|
||
- [模型介绍](../../)
|
||
- [Python部署](../python)
|
||
- [视觉模型预测结果](../../../../../docs/api/vision_results/)
|
||
- [如何切换模型推理后端引擎](../../../../../docs/cn/faq/how_to_change_backend.md)
|