Inspiration## Inspiration
Online shopping has become popular, but customers often struggle to choose clothes that fit their body shape and size. They cannot easily visualize how an outfit will look on them before purchasing it. This can lead to incorrect size selection, dissatisfaction, and product returns.
Our inspiration is to develop an AI-Based Virtual Clothing Try-On with Size Detection system that allows users to visualize different outfits on their own photos and receive suitable clothing size recommendations.
What We Learned
Through this project, we learned about Artificial Intelligence, Computer Vision, Image Processing, Human Body Pose Estimation, and Machine Learning. We explored how AI can identify body features, estimate body measurements, and help users visualize clothing digitally. We also learned about developing an interactive web application and integrating AI models into a practical solution.
How We Built the Project
We designed a web application where users can upload their photograph and select clothing items such as shirts, T-shirts, trousers, and dresses. The system uses computer vision and AI-based image processing to identify the person's body position and generate a virtual try-on preview.
A size detection module estimates body measurements from the uploaded image, when image quality and calibration permit, and recommends a suitable clothing size based on the selected garment's size chart. The interface displays the virtual outfit preview and the recommended size to help users make better purchasing decisions.
The proposed technology stack includes Python, OpenCV, MediaPipe, a suitable virtual try-on AI model, and Flask or React for the user interface. The system can be extended with garment segmentation, advanced image generation, and personalized recommendations.
Challenges We Faced
The major challenges include accurately detecting body proportions from photographs, adjusting clothing to different body poses, maintaining realistic clothing appearance, and recommending the correct size across different brands. Lighting conditions, camera angles, image resolution, and loose clothing can affect measurement accuracy. Integrating AI models while maintaining acceptable processing speed on limited hardware is another challenge.
We plan to address these challenges by using image preprocessing, body landmark detection, garment-specific size charts, and performance optimization. We also aim to clearly communicate that estimated measurements and virtual previews are approximations rather than guaranteed representations of real-world fit.
Impact and Future Scope
This project aims to improve the online shopping experience by helping customers visualize clothing before buying and choose more appropriate sizes. It has the potential to reduce size-related product returns, save customers time, and improve shopping confidence.
In the future, we plan to add real-time camera-based try-on, more realistic fabric rendering, support for multiple clothing categories, personalized fashion recommendations, and integration with online shopping platforms. Our ultimate goal is to make online fashion shopping more interactive, convenient, and personalized.
Log in or sign up for Devpost to join the conversation.