Inspiration- The world is moving forward with the technology of AI and ML. We came to attend the hackathon at Wittyhacks and brainstormed upon many innovative ideas we couldn't think of before. Our main motive was to get experience and network with some great people, who will motivate us to move forward enthusiastically towards our future journey into the world of code.
What it does - The idea of using an AR based model was to enhance and personalize the user experience. The UI interface consist of a scanner which will scan the user, simultaneously understanding the physique of the user. The application will then analyze the body colour, type of body and based on the conclusions, it will recommend the best choice of fashion which he/she is interested in.
How we built it - The tools we used for building this application include Tensorflow, Kaggle, Opencv and Streamlit. We extracted the data through Kaggle and imported the files into our program through Tensorflow. The opencv library of python is useful in detecting and analyzing the face and body of the user. Streamlit was used to create the UI of the application.
Challenges we ran into- This was our first hackathon, so the whole of it was a big challenge for us. We came here keeping only the frontend part in our minds, but the environment was totally new. We took it as a challenge and pushed ourselves into learning new technologies in this 36 hour hackathon.
Accomplishments that we're proud of- Our biggest accomplishment was learning new technologies, getting exposed to the atmosphere to continuous code, it actually was a Code, Eat, Sleep, Repeat scenario for the whole 3 days of hackathon.
What's next for AR Based Shopping Assistant - By leveraging these technologies, e-commerce websites can enhance product discovery, offer personalized recommendations, and provide better visualization of products.
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