Offered By: IBMSkillsNetwork
Build a Fashion Design Web App with DALL-E, Gradio and SAM
Build an AI fashion assistant with CLIPSeg, SAM, and DALL·E 2 that lets users virtually try on, restyle, and redesign clothes through text prompts. Use CLIPSeg and SAM to detect and segment clothing items or accessories in any image, then integrate DALL·E 2 to inpaint and redesign those regions from simple text prompts. Experiment with new fabrics, styles, and colors, all generated intelligently and seamlessly. By the end, you’ll have created a shareable web app that empowers anyone to visualize and prototype fashion ideas instantly through the power of computer vision and generative AI.
Continue readingGuided Project
Artificial Intelligence
At a Glance
Build an AI fashion assistant with CLIPSeg, SAM, and DALL·E 2 that lets users virtually try on, restyle, and redesign clothes through text prompts. Use CLIPSeg and SAM to detect and segment clothing items or accessories in any image, then integrate DALL·E 2 to inpaint and redesign those regions from simple text prompts. Experiment with new fabrics, styles, and colors, all generated intelligently and seamlessly. By the end, you’ll have created a shareable web app that empowers anyone to visualize and prototype fashion ideas instantly through the power of computer vision and generative AI.
Fashion design is a deeply creative process, but traditional editing tools demand time, precision, and technical skill. What if AI could understand your description, automatically identify the clothing item you want to change, and instantly generate your new design? In this project, you’ll build an AI-powered fashion design assistant that combines the CLIPSeg segmentation and Segment Anything Model (SAM) with DALL·E 2 to make text-guided fashion editing effortless. Together, these models form a seamless workflow: SAM figures out what to edit, and DALL·E 2 decides how to recreate it. You’ll integrate both into a user-friendly Gradio web app, where users can upload an image, select a fashion item, describe the desired transformation, and see the result generated in seconds. Along the way, you’ll learn how to bridge computer vision and generative AI to build real-world creative tools.
What You’ll Learn
- Apply the CLIPSeg and Segment Anything Model for automatic mask generation: Use SAM to detect and segment fashion elements from uploaded images, enabling precise and flexible edits without manual input.
- Leverage DALL·E 2 for text-guided inpainting: Use OpenAI’s generative model to redesign masked regions according to user prompts, changing textures, colors, and styles seamlessly.
- Build an interactive Gradio web interface: Create a shareable AI design assistant where users can visualize edits, experiment with different looks, and generate new outfit ideas from plain language.
- Combine vision and generative AI workflows: Understand how to connect segmentation models with diffusion-based image generators for practical, creative applications.
Who Should Enroll
- AI enthusiasts and developers interested in combining computer vision and generative models.
- Designers, artists, or fashion students curious about how AI can accelerate and inspire the design process.
- Students and researchers who want hands-on experience building multi-model AI systems with real-world creative use cases.
Why Enroll
What You'll Need
- Basic Python programming skills.
- Some familiarity with computer vision or generative AI concepts (helpful but not required).
- Curiosity about how AI can revolutionize creative design workflows.
Estimated Effort
45 Min + 45 Min
Level
Intermediate
Skills You Will Learn
Computer Vision, DALL-E, Image Inpainting, Image Segmentation, PyTorch
Language
English
Course Code
GPXX06I5EN