FARMieNG Computer Vision Model
How to use the FARMieNG Detection API
Try This Model
Drop an image here or click to upload
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="farmieng/5")Or, Use Free HEALTHY, BACTERIAL DISEASE and GERMINATED Detection API
Powered by general detection model
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": "HEALTHY, BACTERIAL DISEASE, GERMINATED, VIRAL DISEASE"
},
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
About FARMieNG Model
Here are a few use cases for this project:
-
Precision Agriculture: FARMieNG can be used by farmers or agronomists to monitor crop health in real-time, enabling better decision-making in the fields. Early detection of diseases or unhealthy plants can prevent further spread and help farmers take appropriate action to maintain yield and reduce losses.
-
Greenhouse Management: This computer vision model can be applied in greenhouses or indoor farming systems to keep a close eye on plant health. By detecting potential issues early on, greenhouse operators can take corrective measures to ensure optimal plant growth and productivity.
-
Plant Disease Database: FARMieNG could be utilized to build a comprehensive plant disease and pest database, aiding researchers, and agriculture professionals in studying and developing more effective control methods for various plant diseases and pests.
-
Remote Sensing for Agriculture: Coupling FARMieNG with satellite or drone imagery, governments, and organizations can assess the overall health of crops in agricultural areas. This information can be used for crop yield prediction, disaster management, and to develop strategies to tackle food security issues.
-
Educational Tool: FARMieNG could serve as an educational resource for students, researchers, or hobbyist gardeners to learn more about plant diseases and overall plant health. By gaining better understating of these conditions, users may develop effective preventive measures and improve their plant care practices.
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{ farmieng_dataset,
title = { FARMieNG Dataset },
type = { Open Source Dataset },
author = { Alienor Duron },
howpublished = { \url{ https://universe.roboflow.com/alienor-duron/farmieng } },
url = { https://universe.roboflow.com/alienor-duron/farmieng },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2021 },
month = { oct },
note = { visited on 2026-07-29 },
}