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DeepStream 7.1 + Fixes + New model output format

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This commit is contained in:
Marcos Luciano
2024-11-07 11:25:17 -03:00
parent bca9e59d07
commit b451b036b2
75 changed files with 2383 additions and 1113 deletions
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51
nvdsinfer_custom_impl_Yolo/calibrator.cpp
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@@ -8,9 +8,10 @@
#include <fstream>
#include <iterator>
Int8EntropyCalibrator2::Int8EntropyCalibrator2(const int& batchSize, const int& channels, const int& height, const int& width,
const float& scaleFactor, const float* offsets, const std::string& imgPath, const std::string& calibTablePath) :
batchSize(batchSize), inputC(channels), inputH(height), inputW(width), scaleFactor(scaleFactor), offsets(offsets),
Int8EntropyCalibrator2::Int8EntropyCalibrator2(const int& batchSize, const int& channels, const int& height,
const int& width, const float& scaleFactor, const float* offsets, const int& inputFormat,
const std::string& imgPath, const std::string& calibTablePath) : batchSize(batchSize), inputC(channels),
inputH(height), inputW(width), scaleFactor(scaleFactor), offsets(offsets), inputFormat(inputFormat),
calibTablePath(calibTablePath), imageIndex(0)
{
inputCount = batchSize * channels * height * width;
@@ -54,7 +55,7 @@ Int8EntropyCalibrator2::getBatch(void** bindings, const char** names, int nbBind
return false;
}
std::vector<float> inputData = prepareImage(img, inputC, inputH, inputW, scaleFactor, offsets);
std::vector<float> inputData = prepareImage(img, inputC, inputH, inputW, scaleFactor, offsets, inputFormat);
size_t len = inputData.size();
memcpy(ptr, inputData.data(), len * sizeof(float));
@@ -93,32 +94,46 @@ Int8EntropyCalibrator2::writeCalibrationCache(const void* cache, std::size_t len
}
std::vector<float>
prepareImage(cv::Mat& img, int input_c, int input_h, int input_w, float scaleFactor, const float* offsets)
prepareImage(cv::Mat& img, int inputC, int inputH, int inputW, float scaleFactor, const float* offsets, int inputFormat)
{
cv::Mat out;
cv::cvtColor(img, out, cv::COLOR_BGR2RGB);
if (inputFormat == 0) {
cv::cvtColor(img, out, cv::COLOR_BGR2RGB);
}
else if (inputFormat == 2) {
cv::cvtColor(img, out, cv::COLOR_BGR2GRAY);
}
else {
out = img;
}
int image_w = img.cols;
int image_h = img.rows;
int imageW = img.cols;
int imageH = img.rows;
if (image_w != input_w || image_h != input_h) {
float resizeFactor = std::max(input_w / (float) image_w, input_h / (float) img.rows);
if (imageW != inputW || imageH != inputH) {
float resizeFactor = std::max(inputW / (float) imageW, inputH / (float) imageH);
cv::resize(out, out, cv::Size(0, 0), resizeFactor, resizeFactor, cv::INTER_CUBIC);
cv::Rect crop(cv::Point(0.5 * (out.cols - input_w), 0.5 * (out.rows - input_h)), cv::Size(input_w, input_h));
cv::Rect crop(cv::Point(0.5 * (out.cols - inputW), 0.5 * (out.rows - inputH)), cv::Size(inputW, inputH));
out = out(crop);
}
out.convertTo(out, CV_32F, scaleFactor);
cv::subtract(out, cv::Scalar(offsets[2] / 255, offsets[1] / 255, offsets[0] / 255), out, cv::noArray(), -1);
std::vector<cv::Mat> input_channels(input_c);
cv::split(out, input_channels);
std::vector<float> result(input_h * input_w * input_c);
if (inputFormat == 2) {
cv::subtract(out, cv::Scalar(offsets[0] / 255), out);
}
else {
cv::subtract(out, cv::Scalar(offsets[0] / 255, offsets[1] / 255, offsets[3] / 255), out);
}
std::vector<cv::Mat> inputChannels(inputC);
cv::split(out, inputChannels);
std::vector<float> result(inputH * inputW * inputC);
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));
int channelLength = inputH * inputW;
for (int i = 0; i < inputC; ++i) {
memcpy(data, inputChannels[i].data, channelLength * sizeof(float));
data += channelLength;
}