uvos/SDImagePreprocess
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more effectively multithread

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This commit is contained in:
uvos 2024-04-05 12:23:11 +02:00
parent 35cfa8a906
commit 81475815fb
2 changed files with 37 additions and 15 deletions
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50
main.cpp
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@ -253,7 +253,7 @@ static void reduceSize(cv::Mat& image, const cv::Size& targetSize)
}
}
void pipeline(const std::filesystem::path& path, const Config& config, Yolo& yolo, std::mutex& yoloMutex, FaceRecognizer* recognizer,
void pipeline(const std::filesystem::path& path, const Config& config, Yolo& yolo, FaceRecognizer* recognizer,
std::mutex& reconizerMutex, const std::filesystem::path& debugOutputPath)
{
InteligentRoi intRoi(yolo);
@ -266,9 +266,7 @@ void pipeline(const std::filesystem::path& path, const Config& config, Yolo& yol
reduceSize(image, config.targetSize);
yoloMutex.lock();
std::vector<Yolo::Detection> detections = yolo.runInference(image);
yoloMutex.unlock();
Log(Log::DEBUG)<<"Got "<<detections.size()<<" detections for "<<path;
for(Yolo::Detection& detection : detections)
@ -297,9 +295,7 @@ void pipeline(const std::filesystem::path& path, const Config& config, Yolo& yol
bool ret = seamCarveResize(image, detections, config.targetSize.aspectRatio());
if(ret && image.size().aspectRatio() != config.targetSize.aspectRatio())
{
yoloMutex.lock();
detections = yolo.runInference(image);
yoloMutex.unlock();
}
}
@ -336,6 +332,35 @@ void pipeline(const std::filesystem::path& path, const Config& config, Yolo& yol
Log(Log::WARN)<<"could not save image to "<<config.outputDir/path.filename()<<" skipping";
}
void threadFn(const std::vector<std::filesystem::path>& images, const Config& config, FaceRecognizer* recognizer,
std::mutex& reconizerMutex, const std::filesystem::path& debugOutputPath)
{
Yolo yolo(config.modelPath, {640, 480}, config.classesPath, false);
for(std::filesystem::path path : images)
pipeline(path, config, yolo, recognizer, reconizerMutex, debugOutputPath);
}
template<typename T>
std::vector<std::vector<T>> splitVector(const std::vector<T>& vec, size_t parts)
{
std::vector<std::vector<T>> out;
size_t length = vec.size()/parts;
size_t remain = vec.size() % parts;
size_t begin = 0;
size_t end = 0;
for (size_t i = 0; i < std::min(parts, vec.size()); ++i)
{
end += (remain > 0) ? (length + !!(remain--)) : length;
out.push_back(std::vector<T>(vec.begin() + begin, vec.begin() + end));
begin = end;
}
return out;
}
int main(int argc, char* argv[])
{
Log::level = Log::INFO;
@ -370,8 +395,6 @@ int main(int argc, char* argv[])
return 1;
}
Yolo yolo(config.modelPath, {640, 480}, config.classesPath, true);
if(!std::filesystem::exists(config.outputDir))
{
if(!std::filesystem::create_directory(config.outputDir))
@ -403,13 +426,14 @@ int main(int argc, char* argv[])
recognizer->setThreshold(config.threshold);
}
std::mutex yoloMutex;
std::vector<std::thread> threads;
std::vector<std::vector<std::filesystem::path>> imagePathParts = splitVector(imagePaths, std::thread::hardware_concurrency());
auto pipelineLambda = [&yolo, &debugOutputPath, &config, &yoloMutex, &recognizer, &recognizerMutex](const std::filesystem::path& path)
{
pipeline(path, config, yolo, yoloMutex, recognizer, recognizerMutex, debugOutputPath);
};
std::for_each(std::execution::par_unseq, imagePaths.begin(), imagePaths.end(), pipelineLambda);
for(size_t i = 0; i < std::thread::hardware_concurrency(); ++i)
threads.push_back(std::thread(threadFn, imagePathParts[i], std::ref(config), recognizer, std::ref(recognizerMutex), std::ref(debugOutputPath)));
for(std::thread& thread : threads)
thread.join();
return 0;
}

2
yolo.cpp
View file

@ -42,13 +42,11 @@ Yolo::Yolo(const std::filesystem::path &onnxModelPath, const cv::Size &modelInpu
}
if(runWithOCl)
{
std::cout << "\nRunning on OCV" << std::endl;
net.setPreferableBackend(cv::dnn::DNN_BACKEND_DEFAULT);
net.setPreferableTarget(cv::dnn::DNN_TARGET_OPENCL);
}
else
{
std::cout << "\nRunning on CPU" << std::endl;
net.setPreferableBackend(cv::dnn::DNN_BACKEND_OPENCV);
net.setPreferableTarget(cv::dnn::DNN_TARGET_CPU);
}