seed segregation Computer Vision Model
How to use the seed segregation 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="seed-segregation-cxczc/3")Or, Use Free Bad Black Channa, Bad Kabuli Chana and Bad Rajma 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": "Bad Black Channa, Bad Kabuli Chana, Bad Rajma, Bad Soya, Good Black Channa"
},
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 seed segregation Model
Here are a few use cases for this project:
-
Quality Control in Agricultural Industry: This model could be employed in the agriculture industry for segregating different types of seeds based on quality. The segregation process can help in sorting good from bad seeds, improving productivity and yield.
-
Seed Retail Businesses: Seed retailers can use this model to ensure the quality of seeds they sell, creating trust and reliability among customers. They can remove bad seeds from their stock and ensure they provide only high-quality seeds to their buyers.
-
Home Gardening Purposes: Home gardeners can use an app that integrates this model to identify the quality of seeds they bought or harvested from previous crops. This can help them optimize their gardening practices.
-
Agricultural Research: Researchers could use this model to automatically identify and sort seeds for various studies. It could save time and reduce error from manual sorting.
-
Food Processing Units: Food processing units like those producing grain-based products, cereals, or legume-based foods can use this model to separate bad seeds from good ones, improving the quality of their final product.
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{ seed-segregation-cxczc_dataset,
title = { seed segregation Dataset },
type = { Open Source Dataset },
author = { 1MS19EC112 },
howpublished = { \url{ https://universe.roboflow.com/1ms19ec112/seed-segregation-cxczc } },
url = { https://universe.roboflow.com/1ms19ec112/seed-segregation-cxczc },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2023 },
month = { may },
note = { visited on 2026-07-29 },
}