Universe

vegetation Computer Vision Model

bysegmentsTask:
Semantic Segmentation
License:CC BY 4.02.89k views133 downloads

How to use the vegetation Segmentation 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="vegetation-gvb0s/7")
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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": "grass"
  },
  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 
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About vegetation Model

Here are a few use cases for this project:

  1. Botanical Research: The "vegetation" model can be used by botanists or ecologists to identify and classify different types of grass in a field or garden. It can help to accelerate the process of plant identification and data collection for scientific research.

  2. Lawn Care Businesses: Professional landscapers could use this model to identify different types of grass on their clients' properties to ascertain the optimal care and treatment.

  3. Precision Agriculture: The model can be used by farmers or agricultural specialists to identify the type of grass in their field, understand its growth patterns and thus enable them to apply the right fertilizers and growth supplements.

  4. Golf Course Maintenance: This model can be used for managing golf course greens, by assisting in identification of grass types, which can lead to informed decisions about maintenance, mowing schedules, and disease control.

  5. Environmental Conservation: Conservationists can use this computer vision model to track and monitor different types of grass species in a given location. This could be particularly useful in understanding and combating the spread of invasive species.

Cite This Project

LicenseCC BY 4.0

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

@misc{ vegetation-gvb0s_dataset,
  title = { vegetation Dataset },
  type = { Open Source Dataset },
  author = { segments },
  howpublished = { \url{ https://universe.roboflow.com/segments/vegetation-gvb0s } },
  url = { https://universe.roboflow.com/segments/vegetation-gvb0s },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { may },
  note = { visited on 2026-07-29 },
}

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