A Deep learning based streamlit web app which can recommened you various types of fasion products with respect to your choices.
Recommender systems are the systems that are designed to recommend things to the user based on many different factors. These systems predict the most likely product that the users are most likely to purchase and are of interest to. Companies like Netflix, Amazon, etc. use recommender systems to help their users to identify the correct product or movies for them.
The recommender system deals with a large volume of information present by filtering the most important information based on the data provided by a user and other factors that take care of the user’s preference and interest. It finds out the match between user and item and imputes the similarities between users and items for recommendation.
Both the users and the services provided have benefited from these kinds of systems. The quality and decision-making process has also improved through these kinds of systems.
This is a methods of identifying similar products check various aspects on pictures, including: shape, colors, edges, features (including the lighting of the photo) and euclidean distance of vectors in a 'n' dim features space.
You can also use others images
Clone the repository
git clone https://github.com/deepakthakur-92/Fashion-Recommender-System.gitCreate an environment
conda create -n fasion python=3.7 -yInstall the requirements
pip install -r requirements.txtTo open the streamlit
streamlit run app.pyAuthor: Deepak Thakur