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Sentiment-Analysis_Fer2013

The dataset used for this project is the one published in the "Challenges in Representation Learning: Facial Expression Recognition Challenge" by Kaggle.

The data consists of 48x48 pixel grayscale images of faces.

The task is to categorize each face based on the emotion shown in the facial expression in to one of seven categories (0=Angry, 1=Disgust, 2=Fear, 3=Happy, 4=Sad, 5=Surprise, 6=Neutral).

The csv file given contains two main columns, "emotion" and "pixels". The "emotion" column contains a numeric code ranging from 0 to 6, inclusive, for the emotion that is present in the image.

The "pixels" column contains a string surrounded in quotes for each image. The contents of this string a space-separated pixel values in row major order. test.csv contains only the "pixels" column and your task is to predict the emotion column.

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Computer vision, face recognition, opencv, EDNN model, Tensorflow, Pytorch,

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