Overview / Usage

The overarching goal of the project is to provide a comprehensive and user-friendly solution for personalized hair care. The project addresses several key challenges:

1. Hair Type Identification: Users can upload images of their hair, and the system accurately classifies the hair type as straight, curly, or normal. Additionally, it aims to identify if the hair is dry, normal, or oily, providing a more in-depth analysis.
2. Hair character Identification: Users can upload images of their hair, and the system accurately classifies the hair type as frizzy, dry, or intermediate. Additionally, it aims to identify if the hair is dry, normal, or oily, providing a more in-depth analysis.
3. Users upload photos of their hair, and the algorithm processes the images to determine hair type and condition. The system then generates tailored recommendations, including suitable shampoos, conditioners, treatments, and styling products. This production system offers a valuable resource for individuals seeking to better understand and care for their hair. It combines machine learning, image analysis, and personalized product recommendations to create a holistic and user-centric approach to hair care.

Methodology / Approach

Generated a python model for predicting hair type and character. Hair type gave 44% accuracy and character gave 70% accuracy. The generated model is then applied using flask. User can upload an image to find type as well as character of it. The uploaded image is saved in an upload folder. After uploading, it gives the result accordingly.

Technologies Used

Flask, CV2, tensorflow, scikit-learn, ImageDataGenerator, MobileNetV2,

Documents and Presentations

Repository

https://github.com/ANNDANTIES/Hackathon.git

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SONA BINU

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