This project is developed as a part of Flipkart Grid 2.0 Hackathon by me(Susanka Majumder) and my classmate Souvik Dutta (Team NeoSaints).
A fashion retailer wants to source ongoing and upcoming fashion trends from major online fashion portals and online magazines in a consumable and actionable format, so that they are able to effectively and efficiently design an upcoming fashion product portfolio.
Deliverables:
- Identify products that are better performers (in a rank ordered fashion)
- Help the user view the products that are both trending and lagging
- Identify a logic for classifying products as per their trendiness
We were asked to complete the challenge for just the t-shirt product vertical, but to ensure that our solution would be scalable to other products as well.
here a youtube video explaining how the project works.
This project consists of two major components
- Backend - consists of jupypet notebooks that were used to collect data and train our models on that data.
- Frontend - consists of a ReactJs project in order to serve the result to the end user.
- Clone this repository
git clone https://github.com/susanka068/Diana.git
- Run the bash script for initial setup
./setup.sh
- From the root directory run the stage_0.py file to download, extract and refine the data. (Note : As the dataset is quite large , it might take some time to download all the data)
python ./Backend/stage_0.py
( Hit Ctrl + C
if you want to terminate data extraction at any point .Although it's crucial to download the complete dataset to train the model properly )
- Run the final script to train the model and start the frontend.
./run.sh
I believe in the power of open source hence feel free to contribute in any way possible(Bug Fixes or Enhancements). Also if you liked the project you can give it a star 🌟 😁.