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DOTA Aerial Image Object Detection

Oriented bounding box detection in aerial images (Xia et al., CVPR 2018). Detect 15 object categories with arbitrary orientations including planes, ships, vehicles, and sports facilities.

Labels:outdoornatureurbanpeopleanimal+−

Configuration Fileconfig.yaml

# DOTA Aerial Image Object Detection Configuration
# Based on Xia et al., CVPR 2018

annotation_task_name: "DOTA Aerial Object Detection"
task_dir: "."

data_files:
  - "sample-data.json"

item_properties:
  id_key: "id"
  text_key: "image_url"
  context_key: "context"

user_config:
  allow_all_users: true

annotation_schemes:
  - annotation_type: "multiselect"
    name: "object_classes"
    description: "Select all object classes visible"
    labels:
      - name: "plane"
        tooltip: "Airplanes"
      - name: "ship"
        tooltip: "Ships and vessels"
      - name: "storage_tank"
        tooltip: "Storage tanks"
      - name: "baseball_diamond"
        tooltip: "Baseball diamonds"
      - name: "tennis_court"
        tooltip: "Tennis courts"
      - name: "basketball_court"
        tooltip: "Basketball courts"
      - name: "ground_track_field"
        tooltip: "Running tracks"
      - name: "harbor"
        tooltip: "Harbors"
      - name: "bridge"
        tooltip: "Bridges"
      - name: "large_vehicle"
        tooltip: "Large vehicles (trucks, buses)"
      - name: "small_vehicle"
        tooltip: "Small vehicles (cars)"
      - name: "helicopter"
        tooltip: "Helicopters"
      - name: "roundabout"
        tooltip: "Roundabouts"
      - name: "soccer_field"
        tooltip: "Soccer fields"
      - name: "swimming_pool"
        tooltip: "Swimming pools"

  - annotation_type: "radio"
    name: "difficulty"
    description: "Annotation difficulty"
    labels:
      - name: "easy"
        tooltip: "Clear, large objects"
      - name: "difficult"
        tooltip: "Small, occluded, or crowded"

  - annotation_type: "text"
    name: "oriented_bbox"
    description: "Oriented bounding box: x1,y1,x2,y2,x3,y3,x4,y4,class,difficulty"

interface_config:
  item_display_format: "<img src='{{text}}' style='max-width:100%; max-height:500px;'/><br/><small>{{context}}</small>"

output_annotation_format: "json"
output_annotation_dir: "annotations"

Sample Datasample-data.json

[
  {
    "id": "dota_001",
    "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/1/10/Empire_State_Building_%28aerial_view%29.jpg/800px-Empire_State_Building_%28aerial_view%29.jpg",
    "context": "Aerial image. Detect objects with oriented bounding boxes. Objects may appear at any angle."
  },
  {
    "id": "dota_002",
    "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/1/1e/San_Francisco_from_the_Marin_Headlands_in_March_2019.jpg/1200px-San_Francisco_from_the_Marin_Headlands_in_March_2019.jpg",
    "context": "Aerial view. Mark all DOTA categories: planes, ships, vehicles, sports facilities, etc."
  }
]

// ... and 1 more items

Get This Design

View on GitHub

Clone or download from the repository

Quick start:

git clone https://github.com/davidjurgens/potato-showcase.git
cd potato-showcase/image/aerial/dota-aerial
potato start config.yaml

Details

Annotation Types

multiselectradiotext

Domain

Remote SensingAerial Imagery

Use Cases

Object DetectionOriented DetectionAerial Analysis

Tags

dotaaerialoriented-bboxremote-sensingcvpr2018

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