trash-detection Computer Vision Project

nora slimani

Updated a year ago

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Classes (70)
Aerosol
Aluminium blister pack
Aluminium foil Battery Bottle
Bottle cap
Broken glass
Carded blister pack
Cigarette
Clear plastic bottle
Corrugated carton Crisp packet Cup
Disposable food container
Disposable plastic cup
Drink can Drink carton Egg carton Foam cup
Foam food container
Food Can
Food Carton
Food waste Garbage bag Glass bottle Glass cup Glass jar
Lid
Magazine paper Meal carton
Metal bottle cap
Metal lid Normal paper Other Carton
Other can
Other carton
Other container
Other plastic
Other plastic bottle
Other plastic container
Other plastic cup
Other plastic wrapper
Paper Paper bag Paper cup Paper straw Pizza box
Plastic bag wrapper
Plastic bottle cap
Plastic film
Plastic glooves
Plastic lid Plastic straw Plastic utensils Polypropylene bag Pop tab
Rope & strings
Scrap metal Shoe
Single-use carrier bag
Six pack rings
Spread tub Squeezable tube
Straw
Styrofoam piece Tissues Toilet tube Tupperware
Unlabeled litter
Wrapping paper

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Description

Here are a few use cases for this project:

  1. Environmental Cleanliness: The "trash-detection" computer vision model can be integrated into drones for monitoring litter in public spaces like parks, beaches, or city streets. By identifying types of trash, authorities can assess the effectiveness of waste management systems and create strategic clean-up campaigns.

  2. Waste Sorting: Automated waste sorting machines can utilize this model to identify and segregate different types of waste materials for efficient recycling and disposal. This can drastically improve the efficiency of waste treatment facilities and promote sustainable practices.

  3. Damage Control at Sea: Equipping maritime vehicles like boats or unmanned sea vessels with this model can detect, track, and collect litter floating at sea, mitigating the impact on marine life and contributing to cleaner oceans.

  4. Smart Cities: This model can be used in surveillance cameras across cities as part of a "smart city" solution. It can help identify littered areas and facilitate quick cleaning responses, promoting a cleaner and healthier urban environment.

  5. Food Industry Waste Management: In food plants and kitchens, this model can be used to identify and separate food waste from other trash, promoting more efficient composting or disposal processes. It could aid in tracking the progress towards waste reduction goals within the food industry as well.

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Cite This Project

LICENSE
CC BY 4.0

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            trash-detection-otdmj_dataset,
                            title = { trash-detection Dataset },
                            type = { Open Source Dataset },
                            author = { nora slimani },
                            howpublished = { \url{ https://universe.roboflow.com/nora-slimani/trash-detection-otdmj } },
                            url = { https://universe.roboflow.com/nora-slimani/trash-detection-otdmj },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { may },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

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