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POST
/
video
/
{video_id}
/
scenes
/
Create video scenes
curl --request POST \
  --url https://api.videodb.io/video/{video_id}/scenes/ \
  --header 'Content-Type: application/json' \
  --header 'x-access-token: <api-key>' \
  --data '
{
  "scene_type": "shot",
  "callback_url": "https://webhook.example.com/callback"
}
'
{
  "success": true,
  "status": "processing",
  "data": {
    "id": "job-123",
    "output_url": "https://api.videodb.io/async-response/job-123"
  }
}
Extract scenes from a video using shot detection or time-based segmentation, with automatic frame sampling and descriptions. 
import videodb

conn = videodb.connect(api_key="your_api_key")
coll = conn.get_collection()
video = coll.get_videos()[0]

# Extract scenes using shot-based detection (default)
scene_collection = video.extract_scenes()

for scene in scene_collection.scenes:
    print(f"Scene: {scene.id}")
    print(f"Time: {scene.start}s - {scene.end}s")
    print(f"Description: {scene.description}")

# Extract with time-based segmentation (every 10 seconds)
config = {"time": 10, "frame_count": 2}
scenes = video.extract_scenes(
    extraction_type="time_based",
    extraction_config=config
)
  • Two extraction types: shot-based (detects camera cuts) and time-based (fixed intervals)
  • Shot-based default threshold is 20 (lower = more sensitive to changes)
  • Time-based allows specifying interval (in seconds) and frames per segment
  • Returns SceneCollection with Scene objects including frames and metadata
  • Extracted frames can be used for visual search and thumbnail generation

Authorizations

​
x-access-token
string
header
required

API key for authentication (sk-xxx format)

Path Parameters

​
video_id
string
required
Pattern: ^m-
Example:

"m-12345"

Body

application/json
​
scene_type
enum<string>
Available options:
shot,
time_based
Example:

"shot"

​
callback_url
string
Example:

"https://webhook.example.com/callback"

Response

200 - application/json

Scene creation started

​
success
boolean
Example:

true

​
status
enum<string>
Available options:
processing,
done,
failed
Example:

"processing"

​
data
object