navinkti / Fashion-recoomendation-system

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Fashion Recommender system

With an increase in the standard of living, peoples' attention gradually moved towards fashion that is concerned to be a popular aesthetic expression. Humans are inevitably drawn towards something that is visually more attractive. This tendency of humans has led to the development of the fashion industry over the course of time. However, given too many options of garments on the e-commerce websites, has presented new challenges to the customers in identifying their correct outfit. Thus, in this project, we proposed a personalized Fashion Recommender system that generates recommendations for the user based on an input given. Unlike the conventional systems that rely on the user's previous purchases and history, this project aims at using an image of a product given as input by the user to generate recommendations since many-a-time people see something that they are interested in and tend to look for products that are similar to that. We use neural networks to process the images from Fashion Product Images Dataset and the Nearest neighbour backed recommender to generate the final recommendations.

Why use it?

Its useful for choose desired accessory in very less time.

Dataset Link

Kaggle Dataset Big size 15 GB

Kaggle Dataset Small size 572 MB

Setup for local developement

Installation

Use pip to install the requirements.

pip install -r requirements.txt

Usage

To run the web server, simply execute streamlit with the main recommender app:

streamlit run main.py

Built With

  • OpenCV - Open Source Computer Vision and Machine Learning software library
  • Tensorflow - TensorFlow is an end-to-end open source platform for machine learning.
  • Tqdm - tqdm is a Python library that allows you to output a smart progress bar by wrapping around any iterable.
  • streamlit - Streamlit is an open-source app framework for Machine Learning and Data Science teams. Create beautiful data apps in hours, not weeks.
  • pandas - pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
  • Pillow - PIL is the Python Imaging Library by Fredrik Lundh and Contributors.
  • scikit-learn - Scikit-learn is a free software machine learning library for the Python programming language.
  • opencv-python - OpenCV is a huge open-source library for computer vision, machine learning, and image processing.
  • love ❤️

Conclusion

In this project, we have presented a novel framework for fashion recommendation that is driven by data, visually related and simple effective recommendation systems for generating fashion product images. The proposed approach uses a two-stage phase. Initially, our proposed approach extracts the features of the image using CNN classifier ie., for instance allowing the customers to upload any random fashion image from any E-commerce website and later generating similar images to the uploaded image based on the features and texture of the input image. It is imperative that such research goes forward to facilitate greater recommendation accuracy and improve the overall experience of fashion exploration for direct and indirect consumers alike.

Issues

  • Feel free to submit more issues and enhancement requests.
  • If Website is not working properly, please file a report in the Feedback Hub.

Contributing

Any kind of contributions are welcome.

  1. Fork the repo on GitHub.
  2. Clone the project to your own machine.
  3. Commit changes to development branch.
  4. Push your work back up to your fork.
  5. Submit a Pull request so that i can review your changes.

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