Universe

Worm Detection Project Computer Vision Model

byProjectTask:
Object Detection
License:CC BY 4.0198 views5 downloads

How to use the Worm Detection Project Detection API

Try This Model

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Code Snippets

from inference_sdk import InferenceHTTPClient

CLIENT = InferenceHTTPClient(
    api_url="https://serverless.roboflow.com",
    api_key="API_KEY"
)

result = CLIENT.infer("YOUR_IMAGE.jpg", model_id="worm-detection-project/2")
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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": "worm"
  },
  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 
See all 4.6k imagesWorm Detection Project worm sample showing wormWorm Detection Project worm sample showing wormWorm Detection Project worm sampleWorm Detection Project worm sampleWorm Detection Project worm sampleWorm Detection Project worm sample showing wormWorm Detection Project worm sample showing wormWorm Detection Project worm sample showing wormWorm Detection Project worm sampleWorm Detection Project worm sample showing wormWorm Detection Project worm sampleWorm Detection Project worm sample showing worm

About Worm Detection Project Model

Here are a few use cases for this project:

  1. Agriculture and Gardening: This model can be used to identify the presence and type of worms in soil samples. This is helpful for farmers or gardeners to determine if they have beneficial worms or invasive, soil-degrading worms in their gardens or fields.

  2. Parasitology Research: The model can be utilized in research settings to automate the identification of different worm species, assisting in parasitology studies and understanding their impact on hosts.

  3. Fish Bait Business: Companies in the fishing industry could use this model to classify different types of worms in their inventory. This could enable easier sorting and selection processes for customers looking for specific types of bait.

  4. Composting Applications: Individuals or businesses involved in composting can utilize this model to monitor the health and diversity of worm populations in their composting systems, ensuring they have the right balance of worms for effective decomposition.

  5. Ecological Studies: The model can also be used in environmental researches or surveys to identify and count the presence of different worm species in certain habitats, aiding in understanding their role in the ecosystem.

Cite This Project

LicenseCC BY 4.0

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

@misc{ worm-detection-project_dataset,
  title = { Worm Detection Project Dataset },
  type = { Open Source Dataset },
  author = { Project },
  howpublished = { \url{ https://universe.roboflow.com/project-unguv/worm-detection-project } },
  url = { https://universe.roboflow.com/project-unguv/worm-detection-project },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { feb },
  note = { visited on 2026-07-29 },
}

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