A convolutional neural network (CNN) in Keras from scratch to recognize facial expressions. The data consists of 48x48 pixel grayscale images of faces. The objective is to classify each face based on the emotion shown in the facial expression into one of seven categories. (0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral). You will use OpenCV to automatically detect faces in images and draw bounding boxes around them. Once you have trained, saved, and exported the CNN, you will directly serve the trained model to a web interface and perform real-time facial expression recognition on video and image data. Link: https://github.com/sulthan1625/Facial-Expression-Recognition-model
Hey there, This is Sulthan Khan. I've been working on many sites of Artificial Intelligence such as Machine learning , Deep Learning , Reinforcement Learning , Computer vision. If anyone are interested in joining me. Find me on the Github (sulthan1625). Thank You.