AI-Powered Clothing Size Finder App Development
Budget / Salary₹12,500–37,500
TypeFreelance project
LocationRemote
Posted1 hour ago
SmartFit is an AI-powered web application designed to help users determine the appropriate clothing size using their camera and body-pose analysis, reducing the uncertainty involved in online clothing purchases.
The application uses computer vision and pose estimation to analyze a user's body structure through a live camera feed. It uses TensorFlow MoveNet, which detects 17 body keypoints in real time, such as the shoulders, elbows, hips, knees, and ankles. MoveNet is specifically designed for fast real-time pose estimation, making it suitable for browser-based interactive applications.
How SmartFit works
User opens the SmartFit application
The user accesses the application through a web browser.
The camera is activated for body analysis.
Body detection
The camera captures the user's body.
MoveNet identifies important body landmarks and generates a skeletal representation.
Body measurement estimation
The application uses the detected keypoints and their relative positions to estimate body proportions.
User-provided information such as height can be used to improve the scale of the measurements.
Size recommendation
The estimated body dimensions are compared against predefined sizing parameters.
SmartFit then recommends an appropriate clothing size.
Virtual fitting experience
The user can see their body representation and interact with the sizing interface rather than relying purely on manual measurements.
Technology Stack
Frontend
React
Vite
JavaScript/TypeScript
HTML/CSS
Responsive UI
AI / Computer Vision
TensorFlow.js
MoveNet Pose Detection
@tensorflow-models/pose-detection
WebGL backend for accelerated browser inference
MoveNet provides real-time detection of 17 body keypoints, with Lightning optimized for speed and Thunder optimized more toward accuracy.
Main Problem It Solves
Online clothing shopping has a major size and fit problem. Users often don't know which size to select, resulting in poor-fitting clothes and potentially unnecessary returns. Research on smartphone-based clothing fit systems has similarly explored using body-shape detection and machine learning to provide clothing-fit recommendations.
The application uses computer vision and pose estimation to analyze a user's body structure through a live camera feed. It uses TensorFlow MoveNet, which detects 17 body keypoints in real time, such as the shoulders, elbows, hips, knees, and ankles. MoveNet is specifically designed for fast real-time pose estimation, making it suitable for browser-based interactive applications.
How SmartFit works
User opens the SmartFit application
The user accesses the application through a web browser.
The camera is activated for body analysis.
Body detection
The camera captures the user's body.
MoveNet identifies important body landmarks and generates a skeletal representation.
Body measurement estimation
The application uses the detected keypoints and their relative positions to estimate body proportions.
User-provided information such as height can be used to improve the scale of the measurements.
Size recommendation
The estimated body dimensions are compared against predefined sizing parameters.
SmartFit then recommends an appropriate clothing size.
Virtual fitting experience
The user can see their body representation and interact with the sizing interface rather than relying purely on manual measurements.
Technology Stack
Frontend
React
Vite
JavaScript/TypeScript
HTML/CSS
Responsive UI
AI / Computer Vision
TensorFlow.js
MoveNet Pose Detection
@tensorflow-models/pose-detection
WebGL backend for accelerated browser inference
MoveNet provides real-time detection of 17 body keypoints, with Lightning optimized for speed and Thunder optimized more toward accuracy.
Main Problem It Solves
Online clothing shopping has a major size and fit problem. Users often don't know which size to select, resulting in poor-fitting clothes and potentially unnecessary returns. Research on smartphone-based clothing fit systems has similarly explored using body-shape detection and machine learning to provide clothing-fit recommendations.
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