This project performs sentiment analysis on memes using a combination of image and text data. It employs deep learning models to analyze both visual and textual elements of memes. The image data is processed using a convolutional neural network (CNN), while the textual data is processed using a recurrent neural network (RNN). The models are combined to provide comprehensive sentiment analysis, including humor, sarcasm, offensiveness, motivation, and overall sentiment. The project utilizes Flask for building a web service to accept meme images, extract text from them, and provide sentiment analysis results.
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This project combines image and text data for sentiment analysis of memes using CNN and RNN models. It evaluates humor, sarcasm, offensiveness, motivation, and overall sentiment. Built with Flask, it accepts meme images, extracts text, and provides sentiment analysis.
ahmar-js/Memes-Sentiment-Analysis
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This project combines image and text data for sentiment analysis of memes using CNN and RNN models. It evaluates humor, sarcasm, offensiveness, motivation, and overall sentiment. Built with Flask, it accepts meme images, extracts text, and provides sentiment analysis.