This project is developed as a part of the assignment for Algorithmic marketing analyst role at QU analytics. The client for this project is a large e-tailer, SmartFashion, who wants to enhance the user-experience of their clientele by providing rich and engaging interfaces without leaving their couches. Visual search is one of the ways to achieve this objective.
The project is divided into three tasks:
In this task, we will use the approach discussed in https://github.com/matsui528/sis to implement a search for a dataset from the https://mmlab.ie.cuhk.edu.hk/projects/DeepFashion.html site. The task requires us to develop an application using Streamlit that searches objects based on uploaded images. We will use 100 images to keep the problem small enough.
In this task, we will use Dall-e to build a site to customize fashion accessories. We will use Streamlit and Dall-e to prototype an application.
In this task, we will use Pinecone's vector database to speed up the search for images. We will integrate Pinecone's approach with Streamlit for the data used in Task 1. We will also compare the performance of Task 1 and Task 3 to see the improvement in search speed.
The deliverables for this project are as follows:
- Working code on Github - https://github.com/parvashah-create/image-search
- Deployed application on Streamlit - https://parvashah-create-image-search-app-nx8kxu.streamlit.app/
- Documentation on Codelabs - https://codelabs-preview.appspot.com/?file_id=1LPZ37K-IXY1ouRWRyelt--iZLZyXlMpLjT04QVGe-MM#5
This project is developed by Sri Krishnamurthy as a part of the assignment for Algorithmic marketing analyst role at QU analytics.
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