VideoDB Documentation

VideoDB Documentation

Visual Search and Indexing

Custom Annotations

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Enhance your understanding of videos by using our simple annotation and tagging pipeline. To enable this, you can create a new Scene object. Then, pass your annotations in the description field and index them using index_scenes() function.

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Screenshot 2024-07-04 at 12.23.02 PM.jpg

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VideoDB allows multiple indexes on video objects. This is advantageous as it allows you to attach additional context to each scene, enhancing the search functionality.

Scene:

A Scene object describes a unique event in the video. From a timeline perspective it’s a timestamp range.

video_id : id of the video object

start : seconds

end : seconds

description : string description

Each scene object has another attribute, frames, which contains a list of

Frame⁠

objects. However, we don't need them here for custom annotation pipelines because we are bringing the description from outside.

Create a new Scene

Create new Scene objects and add your custom annotation as description.

from videodb.scene import Scene

# create scene object and patch your description

scene1 = Scene(

video_id=video.id,

start=0,

end=100,

description="Detective Martin is being interviewed by the police.",)

scene2 = Scene(

video_id=video.id,

start=600,

end=900,

description="A religious gathering. People are praying and singing")

# create a list of scene objects

scenes = [scene1, scene2]

Index and search scenes

Index using the list of scene objects and use the index_id for search

from videodb import IndexType

#create new index and assign it a name

index_id = video.index_scenes(scenes=scenes, name="My Custom Annotations#1")

# search using the index_id

res = video.search(query="religious gathering", index_type=IndexType.scene, index_id=index_id)

res.play()

Custom annotations unlock additional features

Adding application context into the search pipeline.

Generate unique descriptions from your own custom vision model.

Index manual annotations.