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Emojinator

Emojinator is an open-source Python machine-learning project that recognizes and classifies hand gestures into emoji labels. Its repository contains gesture-creation, model-training and application files, plus gesture data folders and emoji images used for prediction.

Explore the practical guide ↓

Independent OpenViST project profile, based on linked sources.

Emojinator — OpenViST project profile in AI Models.
OpenViST project illustration. See the linked sources for product details.
Understand the project

Practical overview

When it fits

Use it as a code reference or starting point when investigating a hand-gesture-to-emoji classification workflow.

Who it is for

  • Developers exploring hand-gesture recognition and image classification.
  • Learners who want to inspect a project organized around gesture capture, model training and prediction.

Documented uses

  • Create gesture examples for a classifier.
  • Train a machine-learning model on gesture data.
  • Map recognized hand gestures to emoji images.
Before you choose

Requirements & limits

The repository is public and lists an MIT license.

  • The README identifies three project versions: Emojinator, Emojinator 2.0 and Emojinator 3.0.
  • The documented file structure names the gesture creation, training and application scripts, but does not provide a complete setup or run procedure.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Prepare the Emojinator project structure

Locate the gesture-creation, model-training, and application components for hand-emoji classification.

Before you start

  • The Emojinator repository.

Steps

  1. Open the repository’s Emojinator directory.

  2. Identify CreateGest.py for creating gestures, TrainEmojinator.py for training the machine-learning model, and Emojinator.py as the application.

  3. Locate the gestures data folder and the hand_emo images used in prediction.

Expected outcome

The main project components and their documented roles are identified.

Guide limitations

  • The README identifies these files and folders but does not provide commands, dependency requirements, or operating instructions for collecting gestures, training the model, or running the application.
Documentation 1 ↗
Evidence and transparency

Sources & review

Official repository ↗
Source record details
Source availability
Active
Sources checked
16 October 2026
Original website title
akshaybahadur21/Emojinator · Official homepage title · retained in its source language
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