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Places365 Scene Classification

Scene recognition and classification following the Places365 dataset (Zhou et al., TPAMI 2017). Classify images into 365 scene categories spanning indoor, outdoor, and natural environments.

Labels:outdoornatureurbanpeopleanimal+−

Configuration Fileconfig.yaml

# Places365 Scene Classification Configuration
# Based on Zhou et al., TPAMI 2017

annotation_task_name: "Places365 Scene Classification"
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: "radio"
    name: "scene_category"
    description: "Select the primary scene category"
    labels:
      - name: "indoor_home"
        tooltip: "Indoor home environments (bedroom, kitchen, living room)"
      - name: "indoor_work"
        tooltip: "Indoor work environments (office, conference room)"
      - name: "indoor_public"
        tooltip: "Indoor public spaces (mall, museum, restaurant)"
      - name: "outdoor_urban"
        tooltip: "Outdoor urban scenes (street, plaza, parking lot)"
      - name: "outdoor_nature"
        tooltip: "Natural outdoor scenes (forest, beach, mountain)"
      - name: "outdoor_sports"
        tooltip: "Sports venues (stadium, tennis court, golf course)"
      - name: "transportation"
        tooltip: "Transportation scenes (airport, train station, highway)"
      - name: "water"
        tooltip: "Water-related scenes (ocean, lake, river)"

  - annotation_type: "multiselect"
    name: "scene_attributes"
    description: "Select scene attributes that apply"
    labels:
      - name: "natural"
        tooltip: "Scene contains natural elements"
      - name: "man-made"
        tooltip: "Scene contains man-made structures"
      - name: "open"
        tooltip: "Open, expansive space"
      - name: "enclosed"
        tooltip: "Enclosed or bounded space"
      - name: "rugged"
        tooltip: "Uneven, rough terrain"
      - name: "smooth"
        tooltip: "Smooth, even surfaces"
      - name: "vegetation"
        tooltip: "Contains plants or greenery"
      - name: "water"
        tooltip: "Contains water"
      - name: "crowded"
        tooltip: "Contains many people"
      - name: "empty"
        tooltip: "Few or no people"

  - annotation_type: "radio"
    name: "indoor_outdoor"
    description: "Is this an indoor or outdoor scene?"
    labels:
      - name: "indoor"
        tooltip: "Scene is indoors"
      - name: "outdoor"
        tooltip: "Scene is outdoors"
      - name: "semi_outdoor"
        tooltip: "Partially covered or transitional space"

  - annotation_type: "text"
    name: "specific_place"
    description: "Enter a more specific place description if known"

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": "places_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": "Classify this scene. Consider whether it's indoor/outdoor and what category it belongs to."
  },
  {
    "id": "places_002",
    "image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/e/ea/Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg/1200px-Van_Gogh_-_Starry_Night_-_Google_Art_Project.jpg",
    "context": "Identify the scene type and applicable attributes."
  }
]

// ... 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/classification/places365
potato start config.yaml

Details

Annotation Types

multiselectradiotext

Domain

Computer VisionScene Recognition

Use Cases

Scene ClassificationPlace RecognitionEnvironment Understanding

Tags

placessceneclassificationindoor-outdoortpami2017

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