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in this tutorial, we'll delve into the world of deep learning-based face recognition using python. we'll use the power of convolutional neural networks (cnns) to detect and recognize faces in images. specifically, we'll use the face_recognition library, which is built on top of dlib's state-of-the-art face recognition algorithms.
before we begin, make sure you have the following installed:
for this tutorial, you'll need images containing faces. make sure you have images with clear faces and preferably different people. you can load these images using face_recognition.load_image_file().
next, we'll encode the faces in these images into numerical vectors using a pre-trained cnn model.
now, let's compare the faces encoded in the images to see if they match.
you can also visualize the face recognition results by plotting the images and drawing rectangles around the detected faces.
congratulations! you've successfully implemented a face recognition system using deep learning in python. you can now recognize faces in images and even compare them to determine if they belong to the same person.
that concludes our tutorial on python deep learning face recognition. happy coding!

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