Pricing Prediction from Images of Clothing Items

The general objective of this project is to develop and implement an innovative AI-powered solution that enables resellers and small-medium-sized eCommerce businesses to generate pricing predictions of items from product images enabling them to save time and maintain consistency across pricing. The solution aims to reduce the time-consuming and expensive process of manually predicting prices of one-of-a-kind resale items, ultimately removing pricing bias and saving time on each eCommerce listing. Additionally, the project seeks to promote sustainable consumption by extending the lifecycle of goods through responsible reselling.

Data creation for items at the source will save brands and resellers precious time and maintain the accuracy of traceable data across different business models – resale, recycle of fashion items. Pricing prediction for items from images will aid in creation of product data.

Faculty Supervisor:

Andre Augusto Cire

Student:

Partner:

SnapWrite AI Inc.

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program: