还在开发中。。。
OpenCV-lite 是一个轻量化版本的opencv，专注dnn模型部署场景。主要的修改包括：
- 移除一些不太常用的模块：features2d, flann, gapi, ml, objdetect, stitching, video.
- 保留dnn模块API，直接使用MNN、ONNXRuntime、Tflite和TensorRT去做相应的模型推理。
相关项目：
OpenCV-lite相比于原始OpenCV的优势：裁剪掉多余模块，减少包体；引入模型格式对应的推理引擎，让对应的推理引擎推理对应的模型结构。
- The API of opencv is easy to use, but the compatibility with ONNX model is poor.
- ONNXRuntime is very compatible with ONNX, but the API is hard to use and changes all the time.
The compatibility with ONNX model is poor.
It's a headache, user always encounter such error:
[ERROR:[email protected]] global onnx_importer.cpp:xxxx cv::dnn::xxxx::ONNXImporter::handleNode ...
In view of the fact that OpenCV DNN does not fully support dynamic shape input and has low coverage for ONNX. That means user may either in readNet(), or in net.forward(), always get an error.
It is expected that after the release of OpenCV 5.0, things will improve.
If you have a model that needs to be inferred and deployed in a C++ environment, and you encounter errors above, maybe you can try this library.
In this project, I removed all dnn implementation codes, only kept the dnn's API. And connected to the C++ API of ONNXRuntime.
| Project | ONNX op coverage (%) |
|---|---|
| OpenCV DNN | 30.22%** |
| OpenCV-ORT | 91.69%* |
| ONNXRuntime | 92.22% |
**: Statistical methods:
(All_test - all_denylist - parser_denylist)/All_test = (867 - 56 - 549)/867 = 30.2%
*: the unsupported test case can be found here.
- Fix some bugs in imgproc.
- Add Github Action.
- video demo.
- Add ORT-CUDA support, and compatible with
net.setPreferableBackend(DNN_BACKEND_CUDA)API.
Please choose it by your platform. https://github.com/microsoft/onnxruntime/releases
I have tested it with ONNXRuntime version: 1.14.1, and it works well.
The keywork of ORT_SDK will be used in the OpenCV compiler.
export ORT_SDK=/opt/onnxruntime-osx-arm64-1.14.1 # Fix the ORT_SDK path.The compilation process is same from original OpenCV project.
And only difference is that we need to set the one PATH:ORT, so that cmake can find ONNXRuntime lib file and ONNXRuntime head file correctly.
git clone https://github.com/zihaomu/opencv_ort.git
cd opencv_ort
mkdir build & cd build
cmake -D ORT_SDK=/opt/onnxruntime-osx-arm64-1.14.1 .. # Fix the ORT_SDK path.The code is the totally same as original OpenCV DNN.
#include <iostream>
#include <vector>
#include <opencv2/dnn.hpp>
#include <opencv2/imgproc.hpp>
#include <opencv2/highgui.hpp>
#include<algorithm>
using namespace std;
using namespace cv;
using namespace cv::dnn;
int main()
{
// load input
Mat image = imread("PATH_TO_image");
Scalar meanValue(0.485, 0.456, 0.406);
Scalar stdValue(0.229, 0.224, 0.225);
Mat blob = blobFromImage(image, 1.0/255.0, Size(224, 224), meanValue, true);
blob /= stdValue;
Net net = readNetFromONNX("PATH_TO_MODEL/resnet50-v1-12.onnx");
std::vector<Mat> out;
net.setInput(blob);
net.forward(out);
double min=0, max=0;
Point minLoc, maxLoc;
minMaxLoc(out[0], &min, &max, &minLoc, &maxLoc);
cout<<"class num = "<<maxLoc.x<<std::endl;
}