Universe

Weed Detection v1 Computer Vision Model

byDr Zhang Research teamTask:
Object Detection
License:CC BY 4.0316 views17 downloads

How to use the Weed Detection v1 Detection API

Try This Model

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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="weed-detection-v1-vzg5e/6")
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Or, Use Free Weed, Soy plant and Weeds 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, soy plant, Weeds"
  },
  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 1.4k imagesWeed Detection v1 Weeds-not-weeds sampleWeed Detection v1 Weeds-not-weeds sampleWeed Detection v1 Weeds-not-weeds sample showing soy plantWeed Detection v1 Weeds-not-weeds sampleWeed Detection v1 Weeds-not-weeds sampleWeed Detection v1 Weeds-not-weeds sampleWeed Detection v1 Weeds-not-weeds sample showing weedWeed Detection v1 Weeds-not-weeds sample showing weedWeed Detection v1 Weeds-not-weeds sample showing weedWeed Detection v1 Weeds-not-weeds sample showing soy plantWeed Detection v1 Weeds-not-weeds sample showing weedWeed Detection v1 Weeds-not-weeds sample

About Weed Detection v1 Model

Here are a few use cases for this project:

  1. Precision Agriculture: The model could be used to identify weeds in farmers' fields to automatically monitor crop health and target weed control measures, increasing crop productivity and reducing the use of herbicides.

  2. Robotic Weeding: The model can be integrated into an agricultural robot to perform selective weeding, distinguishing between crop plants (such as soybeans) and different types of weeds.

  3. Environmental Research: Researchers could use this model to track the spread of invasive weed species over time and monitor the effectiveness of control measures.

  4. Botanical Education: The model could be incorporated into educational tools or apps to help students and hobbyists learn to identify different types of plants and understand the impact of weeds on plant ecosystems.

  5. Gardening Assistance: Gardeners can use an app powered by this model to identify weeds in their gardens, assisting in maintenance and plant health.

Cite This Project

LicenseCC BY 4.0

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

@misc{ weed-detection-v1-vzg5e_dataset,
  title = { Weed Detection v1 Dataset },
  type = { Open Source Dataset },
  author = { Dr Zhang Research team },
  howpublished = { \url{ https://universe.roboflow.com/dr-zhang-research-team/weed-detection-v1-vzg5e } },
  url = { https://universe.roboflow.com/dr-zhang-research-team/weed-detection-v1-vzg5e },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { jun },
  note = { visited on 2026-07-29 },
}

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