Build AI Powered Emoji Detector
by kandikits
Emojis are ideograms, and it smileys used in electronic messages and web pages. Emojis exist in various genres, including facial expressions, common objects, places, and types of weather, and animals. They are much like emoticons, but emojis are actual pictures instead of typography.
This Emojinator kit predicts emojis based on hand gestures from web cameras.
Development Environment
VSCode and Jupyter Notebook are used for development and debugging. Jupyter Notebook is a web based interactive environment often used for experiments, whereas VSCode is used to get a typical experience of IDE for developers.
Jupyter Notebook is used for our development.
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Image Preparation and Processing
These libraries help in preparing data by annotating and labelling images. Also processes images for running machine learning algorithm.
We use opencv library for capturing frames from live streaming videocam.
Data Analysis/Manipulation
These libraries help in analyzing data and doing data manipulations.
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Machine Learning
Below libraries and model collections helps to create the machine learning models for the core recognition use cases in our solution.
Utilities
The below utility library helps in storing huge amounts of numerical data and manipulate that data easily from NumPy.
Kit Solution Source
Hand Emoji Detector created using this kit are added in this section.The entire solution is available as a package to download from the source code repository.
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Kit Deployment Instructions
Follow below instructions to deploy and run the solution.
1. Download, extract and double-click kit_installer file to install the kit.
2. After successful installation of the kit, locate the zip file 'Emojinator.zip'
3. Extract the zip file and navigate to the directory 'Emojinator'
4. Open command prompt in the extracted directory 'Emojinator' and run the command 'jupyter notebook'
5. Locate and open the 'Emojinator-notebook.ipynb' notebook from the Jupyter Notebook browser window.
6. Execute cells in the notebook
Note: Demo source code will be downloaded to local machine. It is also available here
Support
If you need help to use this kit, you can email us at kandi.support@openweaver.com or direct message us on Twitter Message @OpenWeaverInc.