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airplane_turnaround Computer Vision Dataset

byReallyticsAITask:
Object Detection
License:CC BY 4.0557 views
See all 4.8k imagesairplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 10, 11, 12, 13, 2, 3, 4, 5, 6, 7, 8, 9airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 2, 3, 5, 6airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 10, 2, 3, 4, 5, 9airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 10, 2, 3, 4, 5, 6, 9airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 10, 2, 3, 4, 5, 9airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 10, 2, 3, 4, 5, 9airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 10, 12, 2, 3, 4, 5, 6, 7, 8, 9airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 10, 2, 3, 4, 5, 9airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 10, 2, 3, 4, 5, 6, 9airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 10, 12, 2, 3, 4, 5, 6, 7, 8, 9airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 10, 2, 3, 4, 5, 9airplane_turnaround airplane-persons-baggagetrucks sample showing 0, 1, 2, 3, 5, 8

About airplane_turnaround Dataset

Here are a few use cases for this project:

  1. Airport Operations: This model can be used by airport staff to monitor and optimize the process of airplane turnaround, including recognizing and tracking personnel, baggage trucks, and various stages of the operation. This can help improve efficiency and safety.

  2. Airline Quality Assurance: Airlines could use the model to ensure a high standard of service by monitoring turnaround times, tracking the appropriate people and resources are present, and identifying potential bottlenecks or issues.

  3. Airport Security: The model could be useful for security purposes, identifying personnel in restricted areas, locating unattended baggage or detecting unexpected movements of baggage trucks that could suggest potential threats.

  4. Training and Simulation: The model can serve in training environments, allowing for real-time feedback based on the recognized classes. It could provide new personnel with a practical, visual way to learn procedures.

  5. Research & Development: Government or industry researchers could use the data generated by this model to study and analyze best practices for airplane turnaround, potentially informing regulations or guidelines.

Use Free Person, ++ and 0 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": "person, ++, 0, 1, 10"
  },
  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{ airplane_turnaround_dataset,
  title = { airplane_turnaround Dataset },
  type = { Open Source Dataset },
  author = { ReallyticsAI },
  howpublished = { \url{ https://universe.roboflow.com/reallyticsai/airplane_turnaround } },
  url = { https://universe.roboflow.com/reallyticsai/airplane_turnaround },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2023 },
  month = { jun },
  note = { visited on 2026-07-29 },
}

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