Realtime Face Emotion Recognition using Transfer Learning in TensorFlow

Realtime Face Emotion Recognition using Transfer Learning in TensorFlow

In this post, you'll learn realtime Face Emotion Recognition using transfer learning in TensorFlow

The dataset which we’ll use is fer2013 which was published in International Conference on Machine Learning in 2013. Let’s dive into the project, first open a new project using Jupyter Notebook or any other environment you like. First and foremost, importing the libraries

import tensorflow as tf 
import cv2 
import os
import matplotlib.pyplot as plt 
import pandas as pd
import numpy as np

OpenCV-Python is a library of Python bindings designed to solve computer vision problems.cv2.imread() method loads an image from the specified file. If the image cannot be read (because of the missing file, improper permissions, unsupported or invalid format) then this method returns an empty matrix. We can read the image through the following line of code:

img_array = cv2.imread(‘train/0/Training_3908.jpg’)

deep-learning tensorflow neural-networks artificial-intelligence facial-expressions

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