Universe

geek_recycle4 Computer Vision Dataset

bygeeknamoTask:
Object Detection
License:CC BY 4.0144 views
See all 781 imagesgeek_recycle4 recycle sample showing papergeek_recycle4 recycle sample showing generalgeek_recycle4 recycle sample showing vinylgeek_recycle4 recycle sample showing generalgeek_recycle4 recycle sample showing plasticgeek_recycle4 recycle sample showing generalgeek_recycle4 recycle sample showing papergeek_recycle4 recycle sample showing glassgeek_recycle4 recycle sample showing papergeek_recycle4 recycle sample showing generalgeek_recycle4 recycle sample showing cangeek_recycle4 recycle sample showing glass

About geek_recycle4 Dataset

Here are a few use cases for this project:

  1. Smart Waste Management: The "geek_recycle4" model can be used in designing smart waste sorting machines in both domestic and commercial settings. This can effectively separate recyclable materials for proper disposal, eventually lead to a significant reduction in landfill waste.

  2. Recycling Facility Optimization: Recycling facilities can use this model to dynamically sort different types of recycling materials, thus enhancing productivity and efficiency in recycling processes.

  3. Environment Monitoring: The model can be integrated into urban management systems or drones to monitor public places and raise awareness about unsorted litter. This can drive proactive actions towards trash pick-up and recycling efforts.

  4. Education and Awareness: An app can be developed using this model to educate people on recycling habits. It can scan everyday items and tell users which recycling class it belongs to.

  5. Retail Industry: Retail businesses can incorporate the "geek_recycle4" model in their systems to identify and classify the types of recyclable materials in their waste output, fostering more effective waste management strategies.

Use Free Paper, Plastic and Glass 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, plastic, glass, can, general"
  },
  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{ geek_recycle4_dataset,
  title = { geek_recycle4 Dataset },
  type = { Open Source Dataset },
  author = { geeknamo },
  howpublished = { \url{ https://universe.roboflow.com/geeknamo/geek_recycle4 } },
  url = { https://universe.roboflow.com/geeknamo/geek_recycle4 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { nov },
  note = { visited on 2026-07-29 },
}

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