Universe

Trash_Recognition_2 (600/1998) Computer Vision Dataset

byTrash RecognitionTask:
Object Detection
License:CC BY 4.0276 views9 downloads
See all 2k imagesTrash_Recognition_2 (600/1998) Trash sample showing metalTrash_Recognition_2 (600/1998) Trash sample showing plastic, plastic bottleTrash_Recognition_2 (600/1998) Trash sample showing PaperTrash_Recognition_2 (600/1998) Trash sample showing Cigarette, general waste, paper, plastic, plastic bottleTrash_Recognition_2 (600/1998) Trash sample showing general wasteTrash_Recognition_2 (600/1998) Trash sample showing general wasteTrash_Recognition_2 (600/1998) Trash sample showing plasticTrash_Recognition_2 (600/1998) Trash sample showing plasticTrash_Recognition_2 (600/1998) Trash sample showing aluminium wrapTrash_Recognition_2 (600/1998) Trash sample showing Metal, Plastic cupTrash_Recognition_2 (600/1998) Trash sample showing metal, paperTrash_Recognition_2 (600/1998) Trash sample showing plastic

About Trash_Recognition_2 (600/1998) Dataset

Here are a few use cases for this project:

  1. Waste Sorting and Recycling: This model can be utilized in waste sorting and recycling facilities to improve the speed and accuracy of material identification, resulting in more efficient recycling processes.

  2. Environment Cleanup: The model can assist in cleanup initiatives, to quickly distinguish and classify litter in public places, beaches, and parks.

  3. Smart Waste Bins: It can be incorporated in smart waste bin systems to identify and sort waste, adding to the convenience for users and promoting environmental sustainability.

  4. Educational Tool: This model can be used as an educational tool to help individuals learn about different types of waste, so they can better sort their trash at home and office.

  5. Retail Industry: In the retail industry, the model can be used to automate the identification and categorization of waste products, aiding in more accurate waste management and potentially reducing costs.

Use Free Paper, Paper and Plastic Detection API

Powered by general detection model

Code
pip install inference-sdk
# 1. Import the library
from inference_sdk import InferenceHTTPClient

# 2. Connect to your workspace
client = InferenceHTTPClient(
  api_url="https://serverless.roboflow.com",
  api_key="API_KEY"
)

# 3. Run your workflow on an image
result = client.run_workflow(
  workspace_name="<YOUR_WORKSPACE>",
  workflow_id="<YOUR_WORKFLOW_ID>",
  images={
    "image": "YOUR_IMAGE.jpg"  # Path to your image file
  },
  parameters={
    "classes": "paper, Paper, Plastic, plastic, Glass"
  },
  use_cache=True  # cache workflow definition for 15 minutes
)

# 4. Get your results
print(result)

Run on custom image

Drop an image here or click to upload

Detecting classes:
Or try a test image 

Cite This Project

LicenseCC BY 4.0

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

@misc{ trash_recognition_2--600-1998_dataset,
  title = { Trash_Recognition_2 (600/1998) Dataset },
  type = { Open Source Dataset },
  author = { Trash Recognition },
  howpublished = { \url{ https://universe.roboflow.com/trash-recognition/trash_recognition_2--600-1998 } },
  url = { https://universe.roboflow.com/trash-recognition/trash_recognition_2--600-1998 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { apr },
  note = { visited on 2026-07-29 },
}

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