Waste Recognizer
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Waste Recognizer Model
This waste recognition model can identify the type of waste and provide guidance on the appropriate disposal method or bin. The model enhances waste management efficiency by ensuring proper sorting and recycling. It contributes to environmental sustainability by reducing contamination in waste streams.

Plastic Waste!
Beverage bottles,food wrappers,straws,shopping bags and cigarette butts etc.

Metal Waste!
Aluminium,copper,iron,tin,gold,lead,silver, titanium, uranium,zinc,bronze and steel etc.

Organic Waste!
Biodegradable material such as Food waste,yard waste,human waste and manure etc

Glass Waste!
Broken glass,bottles,plates,planesglassware,jars and cosmetic containers

Electronic Waste!
Computers,televisions,mobile phones,home appliances such as air conditioners,televisions etc

Textile Waste!
Old and torn clothes,waste from spining yarn and weaving fabric,knitting and dyeing waste etc.

Medical Waste!
Blood,infectious agents(socks),swabs and dresings,medicines,syringes and needles and surgical gloves etc.

Wood Waste!
Construction wood,wooden pallets,furniture,sawdust,tree branches and tree stumps etc

Paper Waste!
Newspapers,magazines,letters, envelopes,receipts,flyers,posters, Journals and Instruction manuals etc

Shoes Waste!
Shoe waste can include manufacturing scraps, defective shoes, packaging, and post-consumer waste

Features
- Accurate Waste Identification: Recognizes various types of waste materials with high precision.
- Disposal Guidance: Provides recommendations for the appropriate disposal method or bin for each type of waste.
- Efficiency Enhancement: Improves waste management processes by ensuring proper sorting and recycling.
- Environmental Sustainability: Reduces contamination in waste streams, promoting eco-friendly practices.
- Versatile Application: Can be deployed in diverse settings, such as smart waste management systems and public recycling initiatives.
- User-Friendly Interface: Designed for easy integration and use in existing waste management systems.
📝 Setup Instructions:
- Clone the repository, install dependencies, and run the model in Jupyter Notebooks or Google Colab for testing and further development.
- For more details, check out the full documentation.