spidy20 / music_player_with_emotions_recognition Goto Github PK

• Tensorflow
• Download my repository
• Own Expression dataset(NOTE: You can downlaod expression images from google, or you can record your video make diffrent expression ,and converts into Grayscale images(For more accurate prediction))
• Song dataset

• Download my repository
• Make 'Images' folder in your project ,make subfolder for emotions like Happy,sad,Angry.
• Put Face_crop.py & haarcascade_frontalface_alt.xml in every type of image folder,ex : put this program in "happy' image folder and run this program it will detect faces from images and convert it into grayscale and make a new images in same folder.
• Make 'Songs' folder make subfolders for emotions and put Songs,Like Happy songs in happy folder.
• After that you have to create model, for that copy code from code.txt file and open CMD in your project folder and paste it & enter
• It will take training aaround 20-25 minutes so keep patience.
• After training it will create two files retrained_graph.pb & retrained_labels.txt
• Now run music_player_webcam.py (give proper path of songs and Mediaplayer according to your location in code)
• If you want to fetch video from your mobile cam than use music_player_android.py,but you have to install IPWebcam app in your system and replace your server URL with my URL
• That's all

Youtube

• This is just coded version with no GUI, i ggiven it to opensource ,but if you want to purchase a GUI version ,then go to here STORE

• Full GUI (Tkinter)
• Own developed Music player with all basic functionalities
• See here are some screenshots of full GUI version.

• It will require high processing power(I have 8 GB RAM & 2 GB GC)
• If you think it will recognise expression just like humans,than leave it ,its not possible.
• Download 300 Images for every expression(you can use batch downloader)
• Noisy image can reduce your accuracy so quality of images matter.