EthnicityRecognition-UTKFaces

Overview

EthnicityPredictor-UTK is a project focused on predicting ethnicities from images using PyTorch. The project utilizes the UTKfaces dataset, which contains a diverse collection of facial images annotated with age, gender, and ethnicity information.

Features

• Ethnicity prediction from facial images.
• PyTorch-based implementation.
• Integration of ResNet architectures for effective feature extraction.
• Utilizes the UTKfaces dataset for training and evaluation.

Getting Started

Prerequisites

TODO: The prerequisites for this project will be updated.

How to use

Follow these steps:

1. Clone the repository to your local machine:

   git clone https://github.com/anasserhussien/EthnicityRecognition-UTKFaces.git

2. Navigate to the project directory:

   cd EthnicityRecognition-UTKFaces

3. Execute the Python script to build the dataset:

   You can modify the CONSTANTS at the begin of the file if needed, the script will generate the data/utk_races dir which has the four ethnicities. The scrip will generate 3 splits train, val, and test based on the ratios defined in the CONSTANTS.

   python utk_dataset_builder.py

   Labels mapping:

    | Label | Ethnicity   |
    |-------|-------------|
    | 0     | White       |
    | 1     | Black       |
    | 2     | Asian       |
    | 3     | Indian      |
   

   Dataset distribution:

   

4. Model training:

   python train.py

   Model Training Configurations:

    Maximum Epochs (MAX_EPOCHS): 30
    Batch Size (BATCH_SIZE): 64
    Learning Rate (LR): 0.001
    Optimizer: Adam
    Model Architecture: Non-pretrained ResNet-18
    Data splits:
        60% training
        20% validation
        20% testing 
   

5. Evaluation and Results:

   Accuracy of the model on the test set: 88.261 %

   The model is available @ https://shorturl.at/3vRuj .