Built a Facial Recognition Model in Python. Used Face Recognition library, to detect the face locations and their encoding in the training dataset. Compared faces with the test dataset, using the face_distance, if the face_distance of the test and training dataset is more than the threshold value then the result is saved and stored along with the time of input in the file.
Built a Facial Recognition Model in Python. Used Face Recognition library, to detect the face locations and its encoding in training dataset. Compared faces with test dataset, using the face_distance, if the face_distance of the test and training dataset is more than threshold value then the result is saved and stored along with time of input in the file.
Built a Facial Recognition Model in Python. Used Face Recognition library, to detect the face locations and their encoding in the training dataset. Compared faces with the test dataset, using the face_distance, if the face_distance of the test and training dataset is more than the threshold value then the result is saved and stored along with the time of input in the file.
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