QualFruit Computer Vision Dataset
About QualFruit Dataset
A description for this project has not been published yet.
Use Free Bad_Apple 0-1 day, Bad_Banana-0-day and Bad_Guava-0-day Detection API
Powered by general detection model
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": "Bad_Apple 0-1 day, Bad_Banana-0-day, Bad_Guava-0-day, Bad_Lime-0-1-day, Bad_Orange-0-1-day"
},
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
Roboflow Agent
Tell the agent what you want to build.
Cite This Project
LicensePublic DomainIf you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{ qualfruit_dataset,
title = { QualFruit Dataset },
type = { Open Source Dataset },
author = { FruitQual },
howpublished = { \url{ https://universe.roboflow.com/fruitqual/qualfruit } },
url = { https://universe.roboflow.com/fruitqual/qualfruit },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { aug },
note = { visited on 2026-07-29 },
}










