Bhargav Venkat

Activity

Image-to-Text Conversion Project part 1

Use the Hugging Face Inference API to: Generate a basic caption from an input image. Offer user options to truncate (for a short caption), expand (for a 30-word description), or summarize (for a 50-word summary) the caption using GPT-2.

Single Image AI captions

In this activity, a local image file is processed through the robust "nlpconnect/vit-gpt2-image-captioning" model from Hugging Face. The model generates a descriptive caption by analyzing visual content in the image.

Inpainting and Restoration Challenge

In this activity, you’ll explore the power of image inpainting to transform or repair images. Instead of generating an image solely from text, you’ll provide an existing image and a corresponding mask (where white areas indicate regions to be modified or restored). By supplying a textual prompt that describes the desired change, the AI model fills in the masked regions to create a seamless, restored, or altered image. This exercise is perfect for learning how to guide the creative process beyond full image synthesis—enabling detailed editing and repair of existing visuals.

Post-Processing Magic Workshop

In this activity, you'll generate an image using a text-to-image model (Stable Diffusion) and then enhance it with post-processing techniques. The session focuses on applying practical image adjustments such as increasing brightness, boosting contrast, and adding a soft-focus effect with Gaussian blur. Using Python libraries like Pillow, you'll learn how to transform raw AI-generated images into polished artworks, highlighting the impact of subtle adjustments on the overall visual quality. Enjoy exploring how post-processing can refine and elevate your creative output!

Generating Images from Text using Hugging Face Models

In this activity, students will build an interactive Text-to-Image Generator that takes textual descriptions (prompts) as input and generates corresponding images using the Hugging Face API with the Stable Diffusion model. The tool will allow users to generate creative artwork from simple descriptions, explore the potential of AI in creative fields, and understand how machine learning models process and generate images based on text.

AIEPCM5L6ACP

AIEPCM5L5ACP

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.

AIEPCM5L3ACP

AIEPCM5L2ACP

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.