Rizwan-Majeed/Sentiment-Analysis-from-Images-Using-Deep-Learning
Convolutional Neural Network (CNN) was trained on 48x48 pixel grayscale images to predict 5 different emotions from images. Ten different models with different settings were trained to find the best model and The best model was able to predict 5 emotions from images with 88% training accuracy and 70% testing accuracy.
This tool helps you automatically identify five different human emotions (happy, sad, angry, surprised, neutral) from facial images. You provide an image, and it tells you the likely emotion expressed. It's ideal for researchers studying human behavior, marketers analyzing reactions to content, or anyone needing to categorize emotional expressions in visual data.
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Use this if you need to quickly and automatically classify basic emotions from grayscale facial images.
Not ideal if you require nuanced emotional analysis beyond five basic categories or need to process high-resolution color images.
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Sep 21, 2022
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