{"id":26801012,"url":"https://github.com/kev-1729/waste_classification","last_synced_at":"2026-05-11T02:03:55.472Z","repository":{"id":254618130,"uuid":"847068136","full_name":"Kev-1729/Waste_Classification","owner":"Kev-1729","description":"Este proyecto clasifica residuos en diferentes categorías mediante Visión por Computadora y Deep Learning. 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The model classifies waste into six categories: `organic`, `plastic`, `glass`, `metal`, `cardboard`, and `paper`.  \n\n## Project Description  \n\nThe project seeks to automate waste identification using a pre-trained convolutional neural network (DenseNet121) to improve classification accuracy. This system can be integrated into smart recycling platforms or waste management applications, enabling more efficient material separation.  \n\n### Key Features:  \n- **Classification into Six Categories**: The model identifies and classifies waste images into `organic`, `plastic`, `glass`, `metal`, `cardboard`, and `paper`.  \n- **Customized Training**: The model is trained with an image dataset split into training and testing sets.  \n- **DenseNet121 Architecture**: Utilizes the DenseNet121 architecture, optimized for image classification.  \n- **Automation**: Facilitates automatic waste classification, making it useful for recycling and waste management environments.  \n\n## Benefits  \n\nThis software provides several key benefits:  \n- **Efficiency**: Enhances waste management efficiency by automating the classification process.  \n- **Accuracy**: Leverages a state-of-the-art neural network to improve the accuracy of waste type identification.  \n- **Scalability**: The model is adaptable and can be fine-tuned to include new waste categories or improve performance with additional data.  \n- **Environmental Impact**: By enabling better waste classification, this project can contribute to improved recycling processes and reduced environmental pollution.  \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkev-1729%2Fwaste_classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fkev-1729%2Fwaste_classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fkev-1729%2Fwaste_classification/lists"}