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FII-BachelorThesis

Poketex

Poketex is a web platform that provides users with tools to generate and interact with Pokémon characters created through AI.
It is the product of a bachelor's thesis from the Faculty of Computer Science in Iasi and an extension of a project that won at FIIPractic.
Link to the paper.

Features

Community and Engagement

  • Main Page: Showcases the most popular Pokémon and includes search functionality with pagination.
Home
  • Rating and Comments: Users can rate ⭐⭐⭐⭐⭐ and comment on each Pokémon.

MonBuilder: AI-Based Pokémon Creation

  • MonBuilder: AI-Based Pokémon Creation tool where users can specify a prompt for how the Pokémon should look, a negative prompt for excluding certain elements, a seed for precise and consistent generation, and the number of steps for processing intensity.
Home
  • PokePaint: A drawing interface where users can sketch their ideas. The AI interprets these sketches to generate a Pokémon image.
    • Paint: Real-Time canvas with the ability to draw, Erase, Change color or the Brush size, Undo/Redo and image uploading.
    • ControlNET Integration: Enhances image uploads by transforming them into pencil sketches with "control_v11p_sd15s2_lineart_anime" preprocessor.
    • NSFWJS: Ensuring the content is Safe for Work testing the image for malicious or +18 content.
Paint Components NSFWJS (Adult Content Filtering) Image Uploading with ControlNET Preprocessing
  • StickPose: A stickman editor allows the user to pose figures with adjustable joints. Depth Maps and image segmentation are employed to add and layer objects, creating a scene for the AI to interpret.
    • Allows for the adding or removal of any stickman from the scene.
    • Users can add objects to the scene.
    • Stickmen and objects can be moved forwards or backwards in the scene.
    • Offers settings to adjust how much the pose affects the generated image.
    • Includes a function to save and load poses into/from a database.
StickPose examples Image Generation Saved Poses
Technologies for Image Segmentation DepthMaps Objects Menu Overlapping the Generation with Objects
  • ChatGPT Integration: Using the ChatGPT API and the prompt of the Pokemon, it generates a name and a backstory of the character.
LLM Generated Text

User Profiles and Pokémon Database

  • Profiles: Users have their profiles where their generated Pokémon are displayed with unique names and stories.
  • Breeding: Users can combine two Pokémon, one from their collection and another from their own or another user's collection.
User Profile Breeding
  • Pokémon Pages: Each Pokémon has a dedicated page featuring its story, attributes, and community ratings.
Pokemon

AI Model & Technologies

Frontend
React React official website
Konva-React Konva-React official website
TypeScript TypeScript official website

Backend
API Java Spring Boot

Database
PostgreSQL PostgreSQL official website

Stable Diffusion with LoRA and ControlNET

Other A.Is used

ChatGPT

Security

Acknowledgements

  • Bytex for organizing the "Java in the world of microservices" training (Trainers : Alexandru Cretu, Cristian Danila)
  • Justin Pinkney for the art generation model.
  • Automatic1111 for the Stable Diffusion API
  • PlexPt for the ChatGPT connexions
  • Okta for providing user authentication and management.

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  • TypeScript 74.1%
  • Java 20.5%
  • HTML 2.5%
  • CSS 2.3%
  • Other 0.6%