Hello! I can help you with implementing facial recognition using Tensorflow in C++.
First, you need to download and install the Tensorflow library for C++. You can find the installation instructions in the Tensorflow documentation. Once you have installed the library, you can start writing your code.
For facial recognition, you can use a pre-trained model like FaceNet. You can download the pre-trained model from the Tensorflow website. Once you have the model, you can load it into your C++ code using the Tensorflow C++ API.
As for the GUI, you can use any C++ GUI framework of your choice like Qt or wxWidgets. You can create a simple interface where the user can input an image and the program will recognize the person in the image using the pre-trained model.
Here is a sample code that loads the FaceNet model and uses it for facial recognition:
C++:
#include <tensorflow/cc/client/client_session.h>
#include <tensorflow/cc/ops/standard_ops.h>
#include <tensorflow/core/framework/tensor.h>
#include <tensorflow/core/public/session.h>
void recognize_face(cv::Mat img) {
// Load the pre-trained FaceNet model
tensorflow::Session* session;
tensorflow::GraphDef graph_def;
tensorflow::Status status = tensorflow::ReadBinaryProto(tensorflow::Env::Default(), "facenet_model.pb", &graph_def);
if (!status.ok()) {
std::cerr << "Unable to load FaceNet model: " << status.ToString() << std::endl;
return;
}
session = tensorflow::NewSession(tensorflow::SessionOptions());
status = session->Create(graph_def);
if (!status.ok()) {
std::cerr << "Unable to create FaceNet session: " << status.ToString() << std::endl;
return;
}
// Preprocess the input image
cv::resize(img, img, cv::Size(160, 160));
cv::cvtColor(img, img, CV_BGR2RGB);
img.convertTo(img, CV_32F);
img = (img - 127.5) / 128.0;
// Convert the image to a Tensor and run it through the FaceNet model
tensorflow::Tensor input_tensor(tensorflow::DT_FLOAT, tensorflow::TensorShape({1, 160, 160, 3}));
auto input_tensor_mapped = input_tensor.tensor<float, 4>();
for (int y = 0; y < input_tensor_mapped.dimension(1); ++y) {
const float* source_row = img.ptr<float>(y);
for (int x = 0; x < input_tensor_mapped.dimension(2); ++x) {
const float* source_pixel = source_row + (x * 3);
input_tensor_mapped(0, y, x, 0) = source_pixel[0];
input_tensor_mapped(0, y, x, 1) = source_pixel[1];
input_tensor_mapped(0, y, x, 2) = source_pixel[2];
}
}
std::vector<tensorflow::Tensor> outputs;
status = session->Run({{"input:0", input_tensor}}, {"embeddings:0"}, {}, &outputs);
if (!status.ok()) {
std::cerr << "Unable to run FaceNet session: " << status.ToString() << std::endl;
return;
}
// Use the output embeddings for recognition
// TODO: Implement recognition logic here
}
This code loads the FaceNet model from a binary protobuf file and preprocesses the input image to match the input format of the model. It then runs the input image through the model and gets the embeddings output. You can use these embeddings for facial recognition by comparing them to a database of known embeddings.
I hope this helps you get started with implementing facial recognition using Tensorflow in C++! Let me know if you have any further questions.
