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438 Stars 189 Forks MIT License 41 Commits 7 Opened issues


A simple emoji classifier for humans.

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This code helps you to recognize and classify different emojis. As of now, we are only supporting hand emojis.


Rock Paper Scissor Lizard Spock

Emojinator 2.0

Code Requirements

You can install Conda for python which resolves all the dependencies for machine learning.

pip install requirements.txt


Emojis are ideograms and smileys used in electronic messages and web pages. Emoji exist in various genres, including facial expressions, common objects, places and types of weather, and animals. They are much like emoticons, but emoji are actual pictures instead of typographics.


1) Filters to detect hand. 2) CNN for training the model.

Python Implementation

1) Network Used- Convolutional Neural Network

If you face any problem, kindly raise an issue


1) First, you have to create a gesture database. For that, run
. Enter the gesture name and you will get 2 frames displayed. Look at the contour frame and adjust your hand to make sure that you capture the features of your hand. Press 'c' for capturing the images. It will take 1200 images of one gesture. Try moving your hand a little within the frame to make sure that your model doesn't overfit at the time of training. 2) Repeat this for all the features you want. 3) Run
for converting the images to a CSV file 4) If you want to train the model, run '' 5) Finally, run
for testing your model via webcam.


1) Akshay Bahadur
2) Raghav Patnecha


Rock Paper Scissor Lizard Spock

Emojinator 2.0

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