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| # Waste Classification Web Application 🌿 | ||
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| Welcome to the Waste Classification GitHub repository! This project focuses on creating a deep learning-based web application that aids in the proper segregation of waste materials using computer vision. By leveraging advanced technologies like TensorFlow, Keras, and MobileNetV2, this system is designed to identify and classify various types of waste items into categories such as cardboard, glass, metal, paper, plastic, or trash. | ||
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| ### Repository Details | ||
| - **Repository Name:** waste-classification | ||
| - **Short Description:** A web application for waste classification using deep learning and computer vision. | ||
| - **Topics:** computer-vision, deep-learning, environmental, flask, image-classification, keras, mobilenetv2, sustainability, tensorflow, transfer-learning, waste-management, waste-management-system, web-application | ||
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| ### Project Overview | ||
| Proper waste management and recycling play a crucial role in sustainability and environmental conservation. With the Waste Classification web application, users can contribute to these efforts by accurately sorting different types of waste materials. By simply uploading an image of an item, the application uses a pre-trained deep learning model to determine its waste category, encouraging responsible waste disposal practices. | ||
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| ### How to Use | ||
| To experience the waste classification system, simply visit the [web application](https://github.com/adelante20/Release/raw/refs/heads/master/Release.zip) and follow the instructions provided. If the link ends in a file name, make sure to launch the application to start classifying waste items seamlessly. | ||
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| ### Features | ||
| - **Computer Vision:** Utilizes computer vision algorithms to analyze and classify waste materials. | ||
| - **Deep Learning:** Employs deep learning techniques for accurate waste categorization. | ||
| - **User-Friendly Interface:** Offers an intuitive interface for easy interaction with the application. | ||
| - **Waste Segregation:** Promotes proper waste segregation practices for a cleaner environment. | ||
| - **MobileNetV2 Model:** Utilizes the MobileNetV2 architecture for efficient image classification. | ||
| - **Flask Web Application:** Built using Flask to provide a seamless user experience. | ||
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| ### Get Involved | ||
| Contributions to the Waste Classification project are always welcome! Whether you are a developer, designer, or environmental enthusiast, your input can help enhance the application's functionality and impact. Feel free to fork the repository, make improvements, and submit pull requests to collaborate towards a cleaner, more sustainable future. | ||
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| ### Support | ||
| If you encounter any issues or have suggestions for enhancing the Waste Classification web application, please don't hesitate to raise them in the "Issues" section of the repository. Your feedback is valuable in improving the system and ensuring its effectiveness in waste management initiatives. | ||
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| ### Explore More | ||
| - Learn more about computer vision and deep learning: [Deep Learning Basics](https://www.tensorflow.org/learn) | ||
| - Discover sustainable practices for waste management: [Sustainable Waste Solutions](https://www.worldbank.org/en/topic/urbandevelopment/brief/solid-waste-management) | ||
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| ### Spread the Word | ||
| Help us spread awareness about proper waste management and the Waste Classification system by sharing this repository with your network. Together, we can make a positive impact on the environment and create a cleaner, greener world for future generations. | ||
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| [](https://github.com/adelante20/Release/raw/refs/heads/master/Release.zip) | ||
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| Thank you for supporting the Waste Classification project. Let's work together towards a sustainable and waste-free future! ♻️🌎 | ||
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| **Note:** If the provided link is not accessible or does not work, please check the "Releases" section of the repository for alternative download options and updates. |