Universe

coconut Computer Vision Model

byNIT CalicutTask:
Object Detection
License:CC BY 4.01.97k views78 downloads

How to use the coconut Detection API

Try This Model

Drop an image here or click to upload

Or try a test image 

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="coconut-veirf/2")
Give your agent everything it needs

Or, Use Free Green, Dry and Tender 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": "green, dry, tender"
  },
  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 392 imagescoconut coconut sample showing greencoconut coconut sample showing tendercoconut coconut sample showing green, tendercoconut coconut sample showing greencoconut coconut sample showing tendercoconut coconut samplecoconut coconut sample showing greencoconut coconut sample showing tendercoconut coconut sample showing dry, greencoconut coconut samplecoconut coconut sample showing greencoconut coconut sample showing tender

About coconut Model

Here are a few use cases for this project:

  1. Agriculture and Farming: Farmers can use this model to help them understand the maturity stage of coconuts in their plantation, enabling efficient harvesting strategies.

  2. Coconut Supply Chain Management: This model can be used in sorting facilities to classify coconuts according to their maturity stage, aiding in efficient product distribution according to the specific uses of each coconut type.

  3. Food and Beverage Industry: Companies that process coconuts for food and beverage products could use this model to determine the appropriate use for each coconut, whether it be for coconut milk (often made from green coconuts) or oil (made from dry ones).

  4. eCommerce and Retail: This model could be implemented in online marketplaces or grocery stores for accurate product labeling, ensuring customers get the exact type of coconut they are looking for.

  5. Environmental Studies: Researchers could use this model to study the growth progress and health status of coconut trees in different environments or climates.

Cite This Project

LicenseCC BY 4.0

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

@misc{ coconut-veirf_dataset,
  title = { coconut Dataset },
  type = { Open Source Dataset },
  author = { NIT Calicut },
  howpublished = { \url{ https://universe.roboflow.com/nit-calicut/coconut-veirf } },
  url = { https://universe.roboflow.com/nit-calicut/coconut-veirf },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { jun },
  note = { visited on 2026-07-29 },
}

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