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EcoShop: A Sustainable E-Commerce Platform

Overview

EcoShop is a web-based sustainable e-commerce platform that promotes eco-friendly products, community-driven initiatives, and the principles of the Circular Economy. The platform allows users to register, log in, buy and sell eco-friendly products, and engage in sustainability-focused community events. It also integrates AI-driven recycling ideas and image classification to categorize products accurately.

Features

  • User Authentication: Registration, login, and logout functionalities with secure password handling.
  • Product Management: Users can upload, edit, and delete eco-friendly products. Products include categories such as "organic" and "recycle".
  • AI Chat: Users can get AI-generated recycling ideas based on their inputs.
  • Community Engagement: Users can post and manage sustainability-focused community events.
  • Image Classification: Uses a pre-trained machine learning model to classify and categorize products based on images.
  • MongoDB Database: All data is stored in MongoDB, including user accounts, products, and community posts.

Technologies Used

  • Backend: Python, Flask
  • Database: MongoDB
  • Image Processing: PIL, TensorFlow, Keras
  • Security: Flask-Bcrypt for password hashing
  • AI: Custom-trained model for product image classification
  • Web Templates: Jinja2 for rendering dynamic HTML pages
  • Frontend: HTML, CSS (Templated in Flask)

Requirements

To run this project locally, you need the following installed:

  • Python 3.x
  • MongoDB (running locally on port 27017)
  • TensorFlow
  • Flask
  • Flask-Bcrypt
  • Pillow
  • pymongo
  • numpy
  • Keras
  • Transformers

You can install the dependencies using pip:

pip install flask flask-bcrypt pymongo tensorflow pillow numpy keras

Setup Instructions

  1. Clone the Repository:

    git clone https://github.com/harichselvamc/EcoShop.git
cd EcoShop

  2. Start MongoDB: Ensure you have MongoDB installed and running on your local machine. If you haven't installed MongoDB, follow the MongoDB installation guide.

  3. Run the Flask Application: Start the Flask app by running:

    python app.py

    The app will be hosted at http://127.0.0.1:5000/ in your browser.

  4. Upload Product Images: When uploading products, ensure that you follow the correct format (images should be in .jpg, .jpeg, .png, or .gif formats).

Features in Detail

1. Home Page:

  • Displays featured products along with their details (name, price, description, etc.).
  • Users can navigate to product pages, community posts, or use the AI chat.

2. User Registration & Login:

  • Secure authentication with password hashing (Flask-Bcrypt).
  • Users can register, log in, and view personalized product listings.

3. Product Management:

  • Users can add new products with details such as name, price, description, quantity, weight, and image.
  • Products are categorized into "organic", "recycle", etc., either manually or through an AI-based classification.
  • Product images are processed and categorized based on a pre-trained machine learning model.

4. AI Chat (Qwen/Qwen2.5-0.5B):

  • Provides a real-time chat interface where users can ask for recycling tips and suggestions.
  • The backend uses the generate_recycling_idea function to provide dynamic responses.

5. Community Posts:

  • Users can create community posts for sustainability-related events or initiatives.
  • Posts support images and allow for contact information, event details, and more.

6. Image Classification for Products:

  • Products are classified using a TensorFlow model trained to identify categories like "organic" or "recycle" based on the product images.

7. Admin-Style Permissions:

  • Users can only edit or delete products and posts that they have created.

Folder Structure

EcoShop/
│
├── app.py                # Main Flask application
├── backend.py            # Backend utility functions (e.g., AI-related code)
├── llmbackend.py         # AI chat-related functions
├── static/               # Static files (CSS, images, etc.)
│   ├── css/
│   └── images/
├── templates/            # HTML Templates
│   ├── home.html
│   ├── register.html
│   ├── login.html
│   ├── products.html
│   ├── community.html
│   ├── ai_chat.html
│   └── ...
├── model_small.h5        # Pre-trained image classification model
└── requirements.txt      # List of dependencies

MongoDB Collections

  • users: Stores user information (username, email, password).
  • products: Stores information about the eco-friendly products (name, description, price, image, etc.).
  • community_posts: Stores community-driven posts related to sustainability events.
  • purchases: Stores information about user purchases.

AI Model

The project uses a TensorFlow-based model (model_small.h5) that classifies product images into categories like "organic" or "recycle". The model is trained using a dataset of images that represent different eco-friendly product types.

Model Details:

  • Model Type: CNN (Convolutional Neural Network)
  • Input Size: 80x45 pixels
  • Class Names: 'organic', 'recycle'

The model is used to process uploaded product images, predict the category, and update the product's category in the database.