Coding Projects by Bhargav Venkat

AI-Powered Image-to-Text Conversion Project – Part 2

Students will apply AI-powered tools to generate captions, descriptions, and summaries from images. By expanding on a simple image caption, they will utilize a text generation model (GPT-2) and a text-to-image model (Stable Diffusion) to create a complete, interactive workflow for text-to-image conversion. They will practice generating descriptive text, summarizing the content, and exploring creative applications.

Snap-to-Caption

Practice generating a basic image caption and optionally expand it using GPT-2, with simplified code and minimal user interaction.

Multi-Image AI Captioning Challenge

Extend the basic image captioning script to handle multiple images, track captions in a report, and prompt for user input. Strengthen Python fundamentals while exploring deeper AI-driven captioning workflows.

Vintage Photo Healer

Strengthen students’ skills in AI-driven inpainting by restoring damaged areas of a single vintage photograph with Stable Diffusion, using masks and descriptive prompts exactly as practiced in class.

AI Image Stylist: Your Signature Look

To reinforce students’ understanding of AI image generation and post-processing using Stable Diffusion and Pillow by creating a themed image enhancement pipeline.

Text-to-Image Payload Customization

Extend the text-to-image script to fine-tune prompt parameters. Modify the payload structure for stylistic nuances, adjust response settings, and explore optional fields to gain deeper control over generated images.

Building and Experimenting with Summarization Tools Using Hugging Face API

Students will apply the text summarization techniques learned in class by experimenting with different models (Pegasus, BART) and adjusting the summarization length and style based on various input texts.

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Text Classification with Hugging Face API: Sentiment Analysis

Students will practice using the Hugging Face API to perform text classification using pre-trained models. The objective is to classify sample texts such as movie reviews into sentiment labels like positive or negative.

Exploring Different Endpoints in Facts APIs

Students will expand their knowledge of APIs by experimenting with various endpoints in the Random Useless Facts API. They'll fetch and display facts from different categories, building on their previous work.

Building a Trivia Quiz Using a Public API

In this assignment, you will continue working with APIs to fetch trivia questions from a public API and create a basic interactive quiz application. The goal is to learn how to fetch data from APIs, handle JSON responses, and display the results in a user-friendly manner.

Exploring Public APIs and Understanding JSON Data

In this assignment, you will practice fetching data from public APIs using Python's requests library. You will work with JSON data, extract useful information, and display it. The goal is to solidify your understanding of how APIs work and how to interact with them effectively.