Files
deepstream_yolo/native/nvdsinfer_custom_impl_Yolo/calibrator.cpp
2021-06-19 18:48:55 -03:00

138 lines
4.6 KiB
C++

/*
* Created by Marcos Luciano
* https://www.github.com/marcoslucianops
*/
#include "calibrator.h"
#include <fstream>
#include <iterator>
namespace nvinfer1
{
int8EntroyCalibrator::int8EntroyCalibrator(const int &batchsize, const int &channels, const int &height, const int &width, const int &letterbox, const std::string &imgPath,
const std::string &calibTablePath):batchSize(batchsize), inputC(channels), inputH(height), inputW(width), letterBox(letterbox), calibTablePath(calibTablePath), imageIndex(0)
{
inputCount = batchsize * channels * height * width;
std::fstream f(imgPath);
if (f.is_open())
{
std::string temp;
while (std::getline(f, temp)) imgPaths.push_back(temp);
}
batchData = new float[inputCount];
CUDA_CHECK(cudaMalloc(&deviceInput, inputCount * sizeof(float)));
}
int8EntroyCalibrator::~int8EntroyCalibrator()
{
CUDA_CHECK(cudaFree(deviceInput));
if (batchData)
delete[] batchData;
}
bool int8EntroyCalibrator::getBatch(void **bindings, const char **names, int nbBindings)
{
if (imageIndex + batchSize > uint(imgPaths.size()))
return false;
float* ptr = batchData;
for (size_t j = imageIndex; j < imageIndex + batchSize; ++j)
{
cv::Mat img = cv::imread(imgPaths[j], cv::IMREAD_COLOR);
std::vector<float>inputData = prepareImage(img, inputC, inputH, inputW, letterBox);
int len = (int)(inputData.size());
memcpy(ptr, inputData.data(), len * sizeof(float));
ptr += inputData.size();
std::cout << "Load image: " << imgPaths[j] << std::endl;
std::cout << "Progress: " << (j + 1)*100. / imgPaths.size() << "%" << std::endl;
}
imageIndex += batchSize;
CUDA_CHECK(cudaMemcpy(deviceInput, batchData, inputCount * sizeof(float), cudaMemcpyHostToDevice));
bindings[0] = deviceInput;
return true;
}
const void* int8EntroyCalibrator::readCalibrationCache(std::size_t &length)
{
calibrationCache.clear();
std::ifstream input(calibTablePath, std::ios::binary);
input >> std::noskipws;
if (readCache && input.good())
{
std::copy(std::istream_iterator<char>(input), std::istream_iterator<char>(),
std::back_inserter(calibrationCache));
}
length = calibrationCache.size();
return length ? calibrationCache.data() : nullptr;
}
void int8EntroyCalibrator::writeCalibrationCache(const void *cache, std::size_t length)
{
std::ofstream output(calibTablePath, std::ios::binary);
output.write(reinterpret_cast<const char*>(cache), length);
}
}
std::vector<float> prepareImage(cv::Mat& img, int input_c, int input_h, int input_w, int letter_box)
{
cv::Mat out;
int image_w = img.cols;
int image_h = img.rows;
if (image_w != input_w || image_h != input_h)
{
if (letter_box == 1)
{
float ratio_w = (float)image_w / (float)input_w;
float ratio_h = (float)image_h / (float)input_h;
if (ratio_w > ratio_h)
{
int new_width = input_w * ratio_h;
int x = (image_w - new_width) / 2;
cv::Rect roi(abs(x), 0, new_width, image_h);
out = img(roi);
}
else if (ratio_w < ratio_h)
{
int new_height = input_h * ratio_w;
int y = (image_h - new_height) / 2;
cv::Rect roi(0, abs(y), image_w, new_height);
out = img(roi);
}
else {
out = img;
}
cv::resize(out, out, cv::Size(input_w, input_h), 0, 0, cv::INTER_CUBIC);
}
else
{
cv::resize(img, out, cv::Size(input_w, input_h), 0, 0, cv::INTER_CUBIC);
}
cv::cvtColor(out, out, cv::COLOR_BGR2RGB);
}
else
{
cv::cvtColor(img, out, cv::COLOR_BGR2RGB);
}
if (input_c == 3)
{
out.convertTo(out, CV_32FC3, 1.0 / 255.0);
}
else
{
out.convertTo(out, CV_32FC1, 1.0 / 255.0);
}
std::vector<cv::Mat> input_channels(input_c);
cv::split(out, input_channels);
std::vector<float> result(input_h * input_w * input_c);
auto data = result.data();
int channelLength = input_h * input_w;
for (int i = 0; i < input_c; ++i)
{
memcpy(data, input_channels[i].data, channelLength * sizeof(float));
data += channelLength;
}
return result;
}