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Memes Classification

example

Description

Memes classification is the process of categorizing internet memes into different groups based on their features, such as the image, caption, and context. This task is commonly performed using machine learning techniques, where an algorithm is trained on a large dataset of labeled memes to identify the characteristics that define different meme categories. The goal of memes classification is to enable the automatic organization and discovery of memes, as well as to support the development of meme-related applications such as search engines, recommendation systems, and analysis tools. The output of a memes classification model it's binary, true, or false.

Installation

Please use python version 3.8.10 or above

git clone https://github.com/hafidh561/memes-classification.git
pip3 install -r requirements.txt
python3 download_model.py

Usage

streamlit run app.py

License

MIT LICENSE

© Developed by hafidh561