intermediateimage
MovieNet Scene Classification
Classify movie scenes by type, place, and cinematic attributes. Annotators label scenes with location, time of day, weather, and narrative function.
設定ファイルconfig.yaml
# MovieNet Scene Classification Configuration
# Based on Qian et al., ECCV 2020
# Task: Classify movie scenes by various attributes
annotation_task_name: "MovieNet Scene Classification"
task_dir: "."
data_files:
- data.json
item_properties:
id_key: "id"
text_key: "video_url"
output_annotation_dir: "annotation_output/"
output_annotation_format: "json"
annotation_schemes:
- name: "place_type"
description: "What type of place/location is this scene set in?"
annotation_type: radio
labels:
- "Indoor - Home/Apartment"
- "Indoor - Office/Workplace"
- "Indoor - Public (restaurant, store, etc.)"
- "Indoor - Vehicle"
- "Outdoor - Urban/City"
- "Outdoor - Nature/Rural"
- "Outdoor - Road/Street"
- "Mixed/Transitional"
- name: "time_of_day"
description: "What time of day is depicted?"
annotation_type: radio
labels:
- "Day - Morning"
- "Day - Afternoon"
- "Day - Evening/Dusk"
- "Night"
- "Unclear/Mixed"
- name: "weather"
description: "What is the weather/lighting condition?"
annotation_type: radio
labels:
- "Clear/Sunny"
- "Cloudy/Overcast"
- "Rainy"
- "Snowy"
- "Foggy/Misty"
- "Indoor (N/A)"
- "Unclear"
- name: "scene_function"
description: "What narrative function does this scene serve?"
annotation_type: multiselect
labels:
- "Exposition (introduces information)"
- "Action/Chase"
- "Dialogue/Conversation"
- "Emotional/Dramatic"
- "Comedic"
- "Romantic"
- "Suspense/Tension"
- "Flashback/Dream"
- "Montage/Transition"
- name: "shot_scale"
description: "What is the predominant shot scale?"
annotation_type: radio
labels:
- "Extreme Close-up"
- "Close-up"
- "Medium Shot"
- "Full Shot"
- "Long Shot"
- "Extreme Long Shot"
- "Mixed/Varied"
allow_all_users: true
instances_per_annotator: 50
annotation_per_instance: 2
annotation_instructions: |
## Movie Scene Classification Task
Classify movie scenes by their visual and narrative attributes.
### Attributes to Label:
**Place Type**: Where does the scene take place?
**Time of Day**: When does the scene occur?
**Weather**: What's the lighting/weather condition?
**Scene Function**: What purpose does this scene serve narratively?
**Shot Scale**: What's the typical camera distance?
### Tips:
- Consider the OVERALL scene, not just one shot
- Scene function can have multiple labels
- If unsure, choose the most prominent/frequent option
サンプルデータsample-data.json
[
{
"id": "movienet_001",
"video_url": "https://example.com/videos/movie_scene_office.mp4",
"movie": "Sample Movie",
"scene_number": 1
},
{
"id": "movienet_002",
"video_url": "https://example.com/videos/movie_scene_outdoor.mp4",
"movie": "Sample Movie",
"scene_number": 2
}
]このデザインを取得
View on GitHub
Clone or download from the repository
クイックスタート:
git clone https://github.com/davidjurgens/potato-showcase.git cd potato-showcase/video/scene-understanding/movienet-scene-classification potato start config.yaml
詳細
アノテーションタイプ
multiselectradio
ドメイン
Computer VisionFilm Studies
ユースケース
Scene ClassificationMovie UnderstandingContent Analysis
タグ
videomoviesceneclassificationmovienetcinematic
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