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286 | #include <limits.h>
#include <stdlib.h>
#include <filesystem>
#include <iostream>
#include <string>
#include <vector>
#include "ExampleMain.h"
#include "SaigeVisionAPI.h"
#include "SaigeVisionUtil.h"
namespace ien {
int run() {
std::string dataDir =
get_env_var("SAIGE_HOME") + "/SaigeVision/engine/Examples/data/enhancement/images/test/";
// trained model path
std::string trainedModelPath = dataDir + "../../models/ien_example.saigeien";
// image paths to classify
// used filesystem library of c++17 standard.
// u8string means 8byte character string so, it doesn't support unicode system of filesystem.
std::vector<std::string> imagePaths;
std::cout << trainedModelPath << std::endl;
for (const auto& file : std::filesystem::recursive_directory_iterator(dataDir)) {
if (file.is_regular_file() && file.path().extension() == ".png") {
imagePaths.push_back(std::string(file.path().u8string()));
}
}
int retval = 0;
int verbosity = 2;
int deviceIndex = 0;
bool detailedTime = false;
bool optimize = false;
const char* oversizedImageHandlingMethod = SAIGE_DO_NOT_ENHANCE;
// Display config
double overlayAlpha = 0.7;
int waitkeyMilliSecond = -1;
/***********************************************************
* 1. 모델 파일 및 검사 결과 핸들 생성,
* Create handles for model files and inference results
***********************************************************/
SaigeInferenceHandle handle = nullptr;
SaigeHandleConfig config;
unsigned int handleFlags = 0;
/*config.inspectionSizeWidth = 640;
config.inspectionSizeHeight = 1100;
handleFlags |= SAIGE_SET_INSPECTION_SIZE;*/
if (optimize) {
handleFlags |= SAIGE_OPTIMIZE_HANDLE;
}
retval = SaigeCreateInferenceHandle(&handle, kProjectTypeIEN, trainedModelPath.c_str(),
deviceIndex, &config, handleFlags);
if (retval < 0) {
std::cerr << "SaigeCreateInferenceHandle failed - " << SaigeStrError(retval) << std::endl;
return retval;
}
SaigeInferenceResult result = nullptr;
retval = SaigeCreateInferenceResult(&result);
if (retval < 0) {
std::cerr << "SaigeCreateInferenceResult failed - " << SaigeStrError(retval) << std::endl;
return retval;
}
/***********************************************************
* 2. 모델 정보 확인 (Optional)
* Check model information
***********************************************************/
std::cout << SaigeGetModuleVersion() << std::endl;
SaigeModelInfo* modelInfo = new SaigeModelInfo;
retval = SaigeGetModelInfo(handle, modelInfo);
if (retval < 0) {
std::cerr << "SaigeGetModelInfo() failed - " << SaigeStrError(retval) << std::endl;
} else if (verbosity >= 1) {
std::cout << "[Image Enhancement Model Info]" << std::endl;
std::cout << "Network Type: " << modelInfo->networkType << std::endl;
std::cout << "Trained Developer Version: " << modelInfo->developerVersion << std::endl;
std::cout << "Server Version: " << modelInfo->serverVersion << std::endl;
std::cout << "Module Version: " << modelInfo->moduleVersion << std::endl;
std::cout << "TrainingTimeStarted: " << modelInfo->trainingTimeStarted << std::endl;
std::cout << "TrainingTimeCompleted: " << modelInfo->trainingTimeCompleted << std::endl;
std::cout << "TrainingTimeElapsed: " << modelInfo->trainingTimeElapsed << std::endl;
std::cout << "UsedGpuName: " << modelInfo->usedGpuName << std::endl;
std::cout << "Number of Train Images: " << modelInfo->numOfTrainImages << std::endl;
std::cout << "Number of Validation Images: " << modelInfo->numOfValidationImages<< std::endl;
std::cout << "Number of Iterations: " << modelInfo->numOfIterations << std::endl;
std::cout << "ROI Info" << std::endl
<< "- ROI Mode: " << modelInfo->roiInfo.roiMode << std::endl
<< "- ROI LTRB Ratio: " << modelInfo->roiInfo.left << ", " << modelInfo->roiInfo.top
<< ", " << modelInfo->roiInfo.right << ", " << modelInfo->roiInfo.bottom
<< std::endl;
std::cout << "Crop Size (W, H): (" << modelInfo->cropSizeWidth << ", "
<< modelInfo->cropSizeHeight << ")" << std::endl;
if (modelInfo->roiInfo.blindMask != nullptr) {
// show blind mask
SaigeShowImage(modelInfo->roiInfo.blindMask, modelInfo->roiInfo.blindMaskWidth,
modelInfo->roiInfo.blindMaskHeight, 1, SaigeImageType::SV_U8, false, true,
255.0, 0);
}
}
/***********************************************************
* 3. 검사 옵션 확인 및 수정 (Optional)
* Check inference options and set new values
***********************************************************/
SaigeInferenceOption* options = new SaigeInferenceOption;
do {
// Get Module Info 실패 시 검사옵션 확인 불가
if (retval < 0) {
break;
}
retval = SaigeGetInferenceOption(handle, options);
if (retval < 0) {
std::cerr << "SaigeGetInferenceOption() failed - " << SaigeStrError(retval)
<< std::endl;
SaigeDestroyInferenceHandle(handle);
SaigeDestroyInferenceResult(result);
return retval;
}
if (detailedTime) {
options->calcTime = true;
retval = SaigeSetInferenceOption(handle, options, SAIGE_SET_CALC_TIME);
if (retval < 0) {
std::cerr << "SaigeSetInferenceOption() failed - " << SaigeStrError(retval)
<< std::endl;
SaigeDestroyInferenceHandle(handle);
SaigeDestroyInferenceResult(result);
return retval;
}
}
options->oversizedImageHandling = oversizedImageHandlingMethod;
retval = SaigeSetInferenceOption(handle, options, SAIGE_SET_OVERSIZED_IMAGE_HANDLING);
if (retval < 0) {
std::cerr << "SaigeSetInferenceOption() failed - " << SaigeStrError(retval)
<< std::endl;
SaigeDestroyInferenceHandle(handle);
SaigeDestroyInferenceResult(result);
return retval;
}
if (verbosity >= 1) {
std::cout.precision(17);
std::cout << "[Image Enhancement Inference Options]" << std::endl;
std::cout << "Calc Time: " << (options->calcTime ? "True" : "False") << std::endl;
std::cout << "Batch Size: " << options->batchSize << std::endl;
std::cout << "Inspection Size W, H: (" << options->inspectionSizeWidth << ", "
<< options->inspectionSizeHeight << ")" << std::endl;
std::cout << "Oversized Image Handling: " << options->oversizedImageHandling
<< std::endl;
}
} while (false);
/***********************************************************
* 4. 이미지 검사하기, Inspect images
* 이미지 사이즈는 같다고 가정한다.
***********************************************************/
int h = 0, w = 0, c = 0, type = -1;
int nbatch = 1;
unsigned char* ucImageData = nullptr;
std::vector<long long> inferenceTimes;
for (auto i = 0; i < imagePaths.size(); ++i) {
// 이미지 데이터 메모리를 해제합니다. (루프일관성)
if (ucImageData != nullptr) {
retval = SaigeFreeImageData(ucImageData);
if (retval < 0) {
std::cerr << "SaigeFreeImageData() Failed - " << SaigeStrError(retval) << std::endl;
}
ucImageData = nullptr;
}
// 이미지 데이터를 로드합니다.
ucImageData = (unsigned char*)SaigeGetImageData(imagePaths[i].c_str(), &w, &h, &c, &type);
if (ucImageData == nullptr) {
std::cerr << "SaigeGetImageData() failed - " << imagePaths[i] << std::endl;
continue;
}
/***********************************************************
* 4-1. 검사 함수 호출하기, Call Infer API
***********************************************************/
if (verbosity >= 2) {
std::cout << "\n================================" << std::endl;
std::cout << "(Start): Infer From Image: " << imagePaths[i] << std::endl;
std::cout << "---" << std::endl;
}
unsigned int imageFlag = SaigeConvertImageType(c, type);
retval = SaigeInferFromByteArray(handle, (const unsigned char*)ucImageData, w, h, imageFlag,
result);
if (retval < 0) {
std::cerr << "SaigeInferFromByteArray() failed - " << SaigeStrError(retval)
<< std::endl;
continue;
}
/***********************************************************
* 4-2. 검사 결과 받아오기, Retrieve inference results
***********************************************************/
unsigned char* enhanced_image;
long long imreadTime, inferenceTime, postProcessingTime;
retval = SaigeGetInferenceResultEnhancedImage(result, &enhanced_image);
if (retval < 0) {
std::cerr << "SaigeGetInferenceResultEnhancedImage() failed - "
<< SaigeStrError(retval) << std::endl;
SaigeDestroyInferenceHandle(handle);
SaigeDestroyInferenceResult(result);
return retval;
}
retval = SaigeGetInferenceResultInspectionTime(result, &imreadTime, &inferenceTime,
&postProcessingTime);
if (retval < 0) {
std::cerr << "SaigeGetInferenceResultInspectionTime() failed - "
<< SaigeStrError(retval) << std::endl;
SaigeDestroyInferenceHandle(handle);
SaigeDestroyInferenceResult(result);
return retval;
}
inferenceTimes.push_back(imreadTime + inferenceTime + postProcessingTime);
if (verbosity >= 2) {
std::cout << "Success to get enhanced image" << std::endl;
}
if (verbosity >= 3) {
long long diffsum = 0;
for (int j = 0; j < w; ++j) {
for (int k = 0; k < h; ++k) {
diffsum += abs((int)ucImageData[j * h + k] - (int)enhanced_image[j * h + k]);
}
}
std::cout << "Sum of pixel difference (= |input - enhanced|): " << diffsum << std::endl;
if (verbosity >= 4) {
SaigeDrawImage(enhanced_image, w, h, 1, 1, SaigeImageType::SV_U8, false,
waitkeyMilliSecond);
}
}
if (verbosity >= 2) {
if (detailedTime) {
std::cout << "---\n(End) Image Read, Infer, Postprocess Times (ms): (" << imreadTime
<< ", " << inferenceTime << ", " << postProcessingTime << ")"
<< std::endl;
} else {
std::cout << "---\n(End) Inspection Time: " << inferenceTime << " ms" << std::endl;
}
}
}
if (verbosity >= 1) {
long long totalInferenceTime = 0;
for (auto time : inferenceTimes) {
totalInferenceTime += time;
}
std::cout << "Total Elapsed Time: " << totalInferenceTime << " ms" << std::endl;
}
if (ucImageData != nullptr) {
retval = SaigeFreeImageData(ucImageData);
if (retval < 0) {
std::cerr << "SaigeFreeImageData() Failed - " << SaigeStrError(retval) << std::endl;
}
ucImageData = nullptr;
}
delete modelInfo;
delete options;
/***********************************************************
* 5. 핸들 파괴, Destruct handles
***********************************************************/
retval = SaigeDestroyInferenceHandle(handle);
if (retval < 0) {
std::cerr << "SaigeDestroyInferenceHandle() failed - " << SaigeStrError(retval)
<< std::endl;
// if you get this error, it's possible that the input pointer is not allocated (nullptr).
return retval;
}
retval = SaigeDestroyInferenceResult(result);
if (retval < 0) {
std::cerr << "SaigeDestroyInferenceResult() failed - " << SaigeStrError(retval)
<< std::endl;
// if you get this error, it's possible that the input pointer is not allocated (nullptr).
return retval;
}
return 0;
}
} // namespace seg
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