Universe

INFECTED5 Computer Vision Dataset

by[email protected]Task:
Object Detection
License:CC BY 4.045 views5 downloads
See all 318 imagesINFECTED5 infected sample showing infectedINFECTED5 infected sample showing infectedINFECTED5 infected sample showing infectedINFECTED5 infected sample showing infectedINFECTED5 infected sample showing infectedINFECTED5 infected sample showing infectedINFECTED5 infected sample showing infectedINFECTED5 infected sample showing infected, rejectedINFECTED5 infected sample showing infected, rejectedINFECTED5 infected sample showing infectedINFECTED5 infected sample showing infected, rejectedINFECTED5 infected sample showing infected

About INFECTED5 Dataset

Here are a few use cases for this project:

  1. Agriculture Management: This model could be used in smart farming systems to identify and sort out infected, over-ripe, or rejected fruits during harvest. This will streamline quality control and waste management processes in farms or orchards, leading to improved crop quality and profitability.

  2. Supermarkets and Grocery Stores: INFECTED5 could be utilized in supermarkets and grocery stores to ensure that only fresh and healthy fruits are displayed for consumers. By identifying over-ripe and infected fruits, the model can help avoid food wastage and enhance customer satisfaction.

  3. Food Processing Plants: In factories where fruits are processed for making juices, canned fruits or jams, this model could improve efficiency by quickly sorting out infected and rejected fruits before they enter the processing line.

  4. Supply Chain Monitoring: The model can be deployed in supply chain systems for perishables, acting as an automated quality check tool. It can help detect any infected or over-ripe fruits at any point in the chain, from the farm to the retail shelves.

  5. Research and Development: Scientists and researchers can use INFECTED5 in studying disease patterns in fruits. With its ability to identify infected specimens, this model could help in developing more disease-resistant crops in the future.

Use Free Infected, Over-ripe and Rejected 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": "infected, Over-ripe, rejected"
  },
  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 

Cite This Project

LicenseCC BY 4.0

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

@misc{ infected5_dataset,
  title = { INFECTED5 Dataset },
  type = { Open Source Dataset },
  author = { [email protected] },
  howpublished = { \url{ https://universe.roboflow.com/azureen-naja98-gmail-com/infected5 } },
  url = { https://universe.roboflow.com/azureen-naja98-gmail-com/infected5 },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { feb },
  note = { visited on 2026-07-29 },
}

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