sssod-uaagn-fsod-txmx Computer Vision Dataset

byRoboflow 100-VL FSODTask:
Object Detection
License:MIT

About sssod-uaagn-fsod-txmx Dataset

Overview

Introduction

This dataset is for object detection, focusing on identifying and annotating planes and ships. The primary goal is to detect these objects in various scenes to assist in automated systems for recognition and tracking.

  • Plane: Typically identified by a distinct wing structure and elongated body.
  • Ship: Recognizable by its elongated hull and the inclusion of structural elements like decks or containers.

Object Classes

Plane

Description

Planes are generally characterized by their distinct wing structures, elongated fuselage, and sometimes visible tails. They often have a central body from which wings extend horizontally, forming a cross-like appearance from a top view.

Instructions

  • Draw bounding boxes around the entire plane, ensuring all visible parts including the wings and tail are included.
  • Do not include any reflections or shadows in the bounding box.
  • If parts of the plane are occluded, estimate the bounding box to cover the full extent of the plane to the best of your ability.
  • Do not label objects if they are too blurry to confirm as a plane or if they fall below the resolution threshold where distinctive features cannot be discerned.

Ship

Description

Ships are discernible by their long, narrow hulls often accompanied by various structures on top like decks or containers. They usually appear elongated with linear or curved features along the sides, often giving a top-down view a rectangular shape.

Instructions

  • Draw bounding boxes to include the entire visible structure of the ship, covering both the hull and any superstructures.
  • Avoid covering reflections or shadows in the bounding box.
  • If the ship is partially occluded, include the unseen parts based on the visible structure.
  • Do not label any indistinct shapes or forms that cannot clearly be identified as a ship or if the resolution is insufficient to identify key features.

Use Free Ship and Plane 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": "ship, plane"
  },
  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

LicenseMIT

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

@misc{ sssod-uaagn-fsod-txmx_dataset,
  title = { sssod-uaagn-fsod-txmx Dataset },
  type = { Open Source Dataset },
  author = { Roboflow 100-VL FSOD },
  howpublished = { \url{ https://universe.roboflow.com/rf100-vl-fsod/sssod-uaagn-fsod-txmx } },
  url = { https://universe.roboflow.com/rf100-vl-fsod/sssod-uaagn-fsod-txmx },
  journal = { Roboflow Universe },
  publisher = { Roboflow },
  year = { 2025 },
  month = { apr },
  note = { visited on 2026-07-29 },
}

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