Annotating Fashion Images and Scraping Similar Products Over Web

The fashion sector plays a significant role in the global economy, and there is an increasing need for tools that can direct customers to specific clothing they have seen or want. In response, we present a system that enables users to contribute photographs of fashion items and then obtain related products from various e-commerce sites. This two-stage method starts by extracting comprehensive annotations from the image using an AI model. These annotations therefore make it easier for web crawlers to find related products from online merchants. The system, which was created with Django, places a focus on user security against common web vulnerabilities. Users can also monitor trending searches, access their search history, and get customized recommendations. The AI model, created using transfer learning, performed admirably when compared to models that are considered industry standards on the DeepFashion Dataset.