Willoway Weed Segmentation Computer Vision Model
How to use the Willoway Weed Segmentation Segmentation API
Try This Model
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Model type: Roboflow RF-DETR Instance Segmentation (Small)
Dataset: willoway-weed-segmentation/1 (523 images)
Jun 17, 2026
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="willoway-weed-segmentation/1")Give your agent everything it needs
Or, Use Free Weed, 0 and 2 Detection API
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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": "Weed, 0, 2, d, Willoway-Weed-Segmentation"
},
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
About Willoway Weed Segmentation Model
Tagging of things considered weeds at an Ohian tree nursery
Roboflow Agent
Tell the agent what you want to build.
Cite This Project
LicenseCC BY 4.0If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ willoway-weed-segmentation_dataset,
title = { Willoway Weed Segmentation Dataset },
type = { Open Source Dataset },
author = { LEAP Sprayer },
howpublished = { \url{ https://universe.roboflow.com/leap-sprayer/willoway-weed-segmentation } },
url = { https://universe.roboflow.com/leap-sprayer/willoway-weed-segmentation },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2026 },
month = { jun },
note = { visited on 2026-07-29 },
}







