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Tool-for-creating-lip-recognition-datasets

This program is an open source tool which will culd be used to create datasets suitable train lip recognition machine learning algorithms. All of the results are saved locally. No subtitle to audio or audio to video alignment is applied at the moment. The video is chopped at the times in which subtitles are presented in the video. There are alot of improvements that could be made.

Requirements

Make sure you are connected to the internet. You will need ffmpeg and youtube-dl installed. The code was tested on Ubuntu 19.04 and python 3.7.7 in the anaconda environment. Note: In order for the code to run download the shape_predictor_68_face_landmarks.dat file from here https://github.com/AKSHAYUBHAT/TensorFace/blob/master/openface/models/dlib/ and place it in the same folder with main.py and the rest of the scripts. Make sure the name is exactly 'shape_predictor_68_face_landmarks.dat'. An IDE such as spyder is recommended as it displays the variables values.

Instructions

Simply open main.py and run it to for an example result. Just specify the URL and a name.

For a realtime demo of face detection and cropping open DEMO_face_detect.py, uncomment some example code in the file and run it.

Please make sure that youtube-dl is installed and up to date.

For more information and list of Options

Please read the pdf file 'Demetrios Loizides Final Year Project.pdf' or see the video demonstration I have made here https://drive.google.com/file/d/1pw_bmya_RYbQ8jZJynZV7JgTkbRnmK-O/view?usp=sharing.

Thank you.

About

The following python code is the first step to creating an open source tool which will be used to create datasets that could be used to train lip recognition machine learning algorithms. The program typical takes a given video URL (typically from youtube) and downloads the video along with the available English subtitles. It then chops the video…

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