An AI model can generate many animated SVG shapes. These shapes are based on specific words and categories. A developer can use tools to create, organize, and view these shapes.
By Pawan Nayar · from the LLOS AI Learning record
An AI model can generate many animated SVG shapes.
These shapes are based on specific words and categories. A developer can use tools to create, organize, and view these shapes.
The project has 1,989 animated SVG shapes. Forty shapes were made by hand. The rest were made by an AI model in two large groups. These shapes are stored in a data file called `icons-emojis/gerund_shapes.json`.
A developer wants to add animated icons to a website. The developer uses the `gerund_explorer.html` tool. This tool lets the developer browse 1,989 animated shapes. The developer can filter shapes by category and see their details.
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An AI model should use a database like SQLite for all data storage. This means all information, such as images or text, is saved in the database.
A keyword must appear in at least five long content panels. These panels are usually part of different sections.
A specific emotional tone must be defined for each section of content. This tone should be present in at least four different places within that section.
An AI model should never save word origins on a user's device. The server is the single source of truth for this data.
An AI model can generate many animated SVG shapes. These shapes are based on specific words and categories. A developer can use tools to create, organize, and view these shapes.