Age-Gender-Ethnicity-Predictor

Predicts age,gender,ethnicty of image of person uploaded

Go to the app to test :)

may take few minutes to load

zoom-out to 75% on PC for better experience.

Details of Files present in Repository

• images

  • contains images needed for frontend

• static

  • css
    • contains CSS files
  • js
    • contains Java script files

• templates

  • contains HTML files

• uploads

  • image uploaded during prediction are temporarily stored in this folder. Make sure this folder is not empty during deployment, as git will not track empty folders.

• app.py : python file

• mobilenet_model.zip : pretrained model (lucky that the compressed model is less than 25MB 😄)

• Procfile : needed for Heroku to know what commands it need to run.

• requirements.txt : to specify the libraries needed to install to Heroku.

• runtime.txt : to specify specific version of python.

Details of Project

Age Gender Ethnicity Predictor is web-app deployed on Heroku.

• Model Training

  Go to my training notebook on kaggle
  • Library used : TensorFlow
  • Pretrained Model : MobileNetV2 (Due to 500MB limit on heroku I used smaller model. A big model with better training will give better results)
  • Technique used : MultiLabel classification.
  • Dataset : UTK Face Dataset
  • My model will output a 19D array as output when given an image as input (resized to (200,200,3))
  • ID 0-11 gives information about Age
    • MultiClass classification.
    • if argmax(predicted[:12] = 3) that means the age is between 3*10+1 and 3*10+10 ie., 31-40.
  • ID 12-13 gives information about Gender
    • Binary Classification
    • 0- Male 1- Female
  • ID 14-18 gives information about Ethnicity
    • MultiClass Classification
    • 0- White, 1- Black, 2- Asian, 3-Indian, 4-Others

Note : All the labels used are defined in UTK Face Dataset

• Frontend

  • used an online template and made changes to HTML,CSS,JS files.

• Deployment

  • You can go through this YT playlist created by me for reference Deploying ML model on Heroku using Flask.
  • For more details visit Heroku.

Things I couldn't do because of memory constraint 😢

• Using MTCNN to detect whether the face is present in uploaded image or not.
• Using better pretrained models for training on UTK face dataset.