NotebookHelpers

These are miscellaneous helper methods to render responses from ApertureDB in a jupyter environment.

This module provides helper classes (such as BoundingBox, TemporalBoundingBox) and functions (such as display, draw_bboxes, display_video_mp4, display_annotated_video) to help render visual results from ApertureDB queries directly within a Jupyter Notebook. It makes it easier to visualize bounding boxes, images, and videos without writing boilerplate code.

BoundingBox

BoundingBox(r: Rectangle = None, label: str = None)

A class which combines a box and a label.

TemporalBoundingBox

TemporalBoundingBox(bb: BoundingBox = None, start_frame: int = 0, end_frame=0)

A class that represents a box, but also associated time in the range of frame start and end

display

display(images_array, save=False)

Show images with matplotlib

Note

This method was used by ApertureDB to display images, but it is not recommended anymore. It will not draw annotation.

Instead, when using with JSON queries, make a instance of the Images class and call the display method.

from aperturedb.Images import Images
result, response, blobs = execute_query(client, [{"FindImage":{"uniqueids": True}}], [])
wrapper = Images(client, response=response[0]["FindImage"]["entities"])
wrapper.display()

display_video_mp4

display_video_mp4(blob)

Display a video using IPython.display

Parameters:

Name	Type	Description	Default
blob	bytearray	A blob that is the Video.	required

annotate_video

annotate_video(blob, bboxes: List[TemporalBoundingBox] = [])

Place annotations on a video framewise

Parameters:

Name	Type	Description	Default
blob	bytearray	Video blob returned from the database	required
bboxes	List[TemporalBoundingBox]	List of boxes to be drawn. Defaults to [].	[]

display_annotated_video

display_annotated_video(blob, bboxes: List[TemporalBoundingBox] = [])

Returns a HTML representation with a column filled with video entities.