siddinc / smile_detection

Real-time smile detection using Tensorflow 2.0 and OpenCV3

Real-Time Smile Detection

The goal of this project is to build and train a model which is able to classify a smiling and a non smiling face in real-time.

Tech used:

• TensorFlow 2.0.0
• OpenCV 3.1.0
• Python 3.5.6

Dataset:

• SMILES Dataset used for training and testing
• 13165 images of faces that are either smiling or non-smiling
• All images are grayscale with dimensions 64 x 64 pixels
• Number of classes: 2

Trained Models:

model1.h5 has the following accuracy metrics:

• Training accuracy = 91.78%
• Validation accuracy = 90.58%

model1.h5 was trained for 20 epochs with a batch size of 64

Instructions to run:

• Using anaconda:
  • Run conda create --name <env_name> --file recog.yml
  • Run conda activate <env_name>
• Using pip:
  • Run pip install -r requirements.txt
• cd to src
• Run python main.py