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@Dobiasd
Last active December 28, 2020 12:39
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// Example code for how to:
// - load an image using OpenCV
// - convert it to a fdeep::tensor3
// - use it as input for a forward pass on an image classification model
// - print the class number
// compile with:
// g++ -std=c++14 -O3 opencv_example.cpp -lopencv_core -lopencv_imgproc -lopencv_imgcodecs -o opencv_example
#include <fdeep/fdeep.hpp>
#include <opencv2/opencv.hpp>
int main()
{
const cv::Mat image = cv::imread("image.jpg");
cv::cvtColor(image, image, cv::COLOR_BGR2RGB);
assert(image.isContinuous());
const auto model = fdeep::load_model("model.json");
// Use the correct scaling, i.e. low and high.
const auto input = fdeep::tensor5_from_bytes(image.ptr(),
static_cast<std::size_t>(image.rows),
static_cast<std::size_t>(image.cols),
static_cast<std::size_t>(image.channels()),
0.0f, 1.0f);
const auto result = model.predict_class({input});
std::cout << result << std::endl;
}
@kshitij-netskope
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Hi Dobias,
Thanks for this snippet. This is similar to what I am looking for. Although, I have a different question, I was not able to get OpenCV working in my environment with Keras. Can you point me any documentation that would help?

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