Universe

dna4 Computer Vision Dataset

byDarwin KeemTask:
Instance Segmentation
License:CC BY 4.037 views1 download
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About dna4 Dataset

Here are a few use cases for this project:

  1. Agricultural Land Monitoring: dna4 can be used by researchers, agricultural organizations, and farmers to monitor and analyze the health and growth of crops in agricultural fields. The model can identify different Field classes to provide insights on crop distribution, irrigation systems, and land utilization.

  2. Precision Agriculture: The model can be utilized to develop decision support systems for precision agriculture, which can help farmers optimize their resource usage by identifying specific Field classes. This can lead to better planting, irrigation, and fertilization strategies, resulting in increased crop yields and reduced environmental impact.

  3. Water Resource Management: By identifying water channels in the dataset, dna4 can help government agencies and environmental organizations monitor and manage water resources more effectively. This can provide valuable information for planning, conservation, and allocation of water resources while protecting ecosystems and wildlife habitats.

  4. Urban Planning and Land Use: Urban planners and authorities can use dna4 to identify the distribution of Field classes in and around cities. This can inform decisions regarding land use, zoning regulations, and the promotion of sustainable urban development.

  5. Disaster Management and Risk Assessment: Dna4 can be utilized to analyze the vulnerability of agricultural lands and water channels to natural disasters like floods, droughts, or landslides. This information can help in planning effective disaster prevention and mitigation strategies, benefiting both the environment and the people who depend on agriculture for their livelihoods.

Use Free \ and Fields 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": "\, Fields"
  },
  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{ dna4-dyhsd_dataset,
  title = { dna4 Dataset },
  type = { Open Source Dataset },
  author = { Darwin Keem },
  howpublished = { \url{ https://universe.roboflow.com/darwin-keem-3edcu/dna4-dyhsd } },
  url = { https://universe.roboflow.com/darwin-keem-3edcu/dna4-dyhsd },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { dec },
  note = { visited on 2026-07-29 },
}

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