Universe

Aircraft Cleanliness Computer Vision Dataset

byAircraft DetectionTask:
Object Detection
License:CC BY 4.0495 views15 downloads
See all 333 imagesAircraft Cleanliness Dirt sampleAircraft Cleanliness Dirt sample showing DirtAircraft Cleanliness Dirt sample showing DirtAircraft Cleanliness Dirt sample showing DirtAircraft Cleanliness Dirt sample showing DirtAircraft Cleanliness Dirt sample showing DirtAircraft Cleanliness Dirt sample showing DirtAircraft Cleanliness Dirt sample showing DirtAircraft Cleanliness Dirt sample showing DirtAircraft Cleanliness Dirt sample showing DirtAircraft Cleanliness Dirt sample showing DirtAircraft Cleanliness Dirt sample showing Dirt

About Aircraft Cleanliness Dataset

Here are a few use cases for this project:

  1. Airport Maintenance Monitoring: The Aircraft Cleanliness model can be used by airport authorities to monitor the cleanliness of aircraft and ensure timely cleaning services. This can help maintain a high standard of hygiene and visual appearance for airplanes while also reducing the risk of corrosion or damage due to accumulated dirt.

  2. Airline Quality Control: Airlines can use the model to monitor and compare the cleanliness of their fleet, ensuring consistent quality associated with their brand. It can be employed to hold cleaning crews accountable and establish benchmarks for cleanliness quality.

  3. Passenger Experience Enhancement: Airline ratings and review platforms can integrate the Aircraft Cleanliness model to rate airlines based on the cleanliness of their airplanes. This information can then be provided to passengers, helping them make informed decisions when choosing airlines.

  4. Cleaning Service Optimization: Cleaning companies specializing in aircraft maintenance can utilize this model to optimize their cleaning services. By detecting specific dirt classes and focusing on those areas, they can save time and resources while providing a more effective cleaning process.

  5. Environmental Impact Analysis: Researchers can use the Aircraft Cleanliness model to study the impact of different environmental conditions on the accumulation of dirt on airplanes. This information can lead to the development of new materials or coatings that help reduce the rate at which dirt and contaminants adhere to the aircraft surface, minimizing cleaning requirements and environmental impacts.

Use Free Dirt 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": "Dirt"
  },
  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{ aircraft-cleanliness_dataset,
  title = { Aircraft Cleanliness Dataset },
  type = { Open Source Dataset },
  author = { Aircraft Detection },
  howpublished = { \url{ https://universe.roboflow.com/aircraft-detection-hpzth/aircraft-cleanliness } },
  url = { https://universe.roboflow.com/aircraft-detection-hpzth/aircraft-cleanliness },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2022 },
  month = { aug },
  note = { visited on 2026-07-29 },
}

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