object_detection Computer Vision Dataset

byObject detectionTask:

Object Detection

License:CC BY 4.0

How to use the object_detection Detection API

Try This Model

Drop an image here or click to upload

Or try a test image

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="aquantic-research/object_detection-ptrcw-instant-1")

Give your agent everything it needs

Or, Use Free Car, Airplane and Ship Detection API

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": "car, airplane, ship, speedboat"
  },
  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

See all 524 images

object_detection airplane-car-ship-speedboat sample showing ship

object_detection airplane-car-ship-speedboat sample

object_detection airplane-car-ship-speedboat sample showing car

About object_detection Model

🛰️ SkySeaLand Dataset

The SkySeaLand Dataset is a high-resolution, satellite-based, multi-domain image collection designed for advanced research in object detection, recognition, and classification. It contains over 1,300 high-resolution images, each precisely annotated with four core transportation-related object categories: airplane, boat, car, and ship. Images are captured across diverse geographic regions, environmental conditions, and lighting scenarios, providing robust real-world variability.

✅ Key Features:

4 Object Categories: Airplane, Boat, Car, Ship.

Global Coverage: Europe, Asia, Russia, United States, and more.

Multi-Environment Scenarios: Airports, highways, seaports, marinas, offshore regions, and coastal zones.

High-Resolution Imagery: Clear object detail for accurate detection and classification.

Precisely Annotated: Bounding boxes created with high accuracy.

Dataset Size: 1,300+ images with labels.

Structured Splits: Training, validation, and testing sets for reproducible research.

🎯 Ideal For

Object detection.
Object classification.
Satellite and aerial computer vision tasks
Multi-domain and cross-environment model training
Scene understanding in real-world geographic contexts.

**Dataset Images: ** All renamed and annotated images are available for download here: click here

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Cite This Project

LicenseCC BY 4.0

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

@misc{ object_detection-ptrcw_dataset,
  title = { object_detection Dataset },
  type = { Open Source Dataset },
  author = { Object detection },
  howpublished = { \url{ https://universe.roboflow.com/aquantic-research/object_detection-ptrcw } },
  url = { https://universe.roboflow.com/aquantic-research/object_detection-ptrcw },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2025 },
  month = { nov },
  note = { visited on 2026-07-29 },
}

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