Zones

class Zone(name, points, image_width, image_height, description='', **kwargs)

A region of interest in a static view.

Parameters:

name (str) – The name for the zone.
points (List[Tuple[int, int]]) – The coordinates of the zone.
image_width (int) – The width of the image that was used to generate the zone.
image_height (int) – The height of the image that was used to generate the zone.
description (str) – A short description of the zone.

classmethod from_bounding_box(name, box, image_width, image_height, description='')

Create a Zone from a BoundingBox.

Parameters:

name (str) – The name for the zone.
box (BoundingBox) – A bounding box to be used to generate a zone.
image_width (int) – The width of the image that was used to generate the zone.
image_height (int) – The height of the image that was used to generate the zone.
description (str) – A short description of the zone.

Return type:

Zone

property image_width: int: The width of the image that was used to generate the zone.

property image_height: int: The height of the image that was used to generate the zone.

property mask: ndarray

The binary mask representing the zone.

This is a numpy array of 0 and 1 with data type np.uint8. It’s dimensions match the width and height of the image it was generated with.

property name: str: The zone name.

property points: List[Tuple[int, int]]: The zone coordinates.

property description: str: A short description of the zone.

property type: ZoneType: The type for the zone.

to_bounding_box()

Get a BoundingBox representing the zone.

A box that fits the outermost edges of the Zone will be generated.

Return type:: BoundingBox
Returns:: A BoundingBox representing the Zone

update_image_dimensions(image_width=None, image_height=None)

Update the dimensions of the ZoneList and all included Zone objects.

Parameters:

image_width (Optional[int]) – The new width to update dimensions to
image_height (Optional[int]) – The new height to update dimensions to

check_prediction_within_zone(prediction, **kwargs)

Check whether a prediction is inside the Zone.

Parameters:: prediction (ObjectDetectionPrediction) – The prediction to check for zone affiliation.
Return type:: bool
Returns:: True if the prediction is in the Zone, and False otherwise.

get_predictions_in_zone(results, **kwargs)

Get the predictions that are within this zone.

Parameters:: results (ObjectDetectionResults) – The ObjectDetectionResults to check against the given zone.
Return type:: ObjectDetectionResults
Returns:: A :class:ObjectDetectionResults containing predictions that are within this zone

get_tracked_objects_in_zone(objects)

Get the tracked objects that are within this zone.

Parameters:: results – The TrackingResults to check against the given zone.
Return type:: TrackingResults
Returns:: A TrackingResults containing predictions that are within this zone.

compute_prediction_overlap_with_zone(prediction)

Compute the fraction of prediction box which is overlapped by the Zone.

Parameters:: prediction (ObjectDetectionPrediction) – The prediction to compute overlap.
Return type:: float
Returns:: A value [0.0, 1.0] indicating the fraction of prediction box which is overlapped by the Zone.

class ZoneType(value)

Supported Zone types.

BOX = 'BOX'

POLYGON = 'POLYGON'

class ZoneList(zones, image_width, image_height)

A managed list of Zone objects.

Work with regions of interest in your applications. Each Zone must have a unique name and they all must have matching image dimensions.

Typical usage:

my_zones = edgeiq.ZoneList.from_config_file("zone_config.json")

<get image>
results = obj_detect.detect_objects(image, confidence_level=.5)
image = edgeiq.markup_image(
        image, results.predictions, colors=obj_detect.colors)

obj_detect.publish_analytics(zone_detect_results)

image = my_zones.markup_image_with_zones(
        image,
        fill_zones=True,
        color=(255, 0, 0))

Parameters:

zones (List[Zone]) – A list of Zone to organize as a ZoneList.
image_width (int) – The width of the image the zones were based on.
image_height (int) – The height of the image the zones were based on.

Raises:

ValueError if zones are invalid (duplicate name or mismatching image dimensions)

classmethod from_config_file(filepath)

Create ZoneList from a Zone Creator configuration file.

The Zone Creator tools is available with the alwaysAI CLI.

Parameters:: filepath (str) – The path to the JSON file to configure Zone objects.
Return type:: ZoneList

property zones: List[Zone]: The zones in this Zone List

property zone_names: List[str]

property image_width: int | None: The width of the image the Zone objects were based on.

property image_height: int | None: The height of the image the Zone objects were based on.

property colors: List[Tuple[int, int, int]]: The colors to draw the Zone boundaries in.

property alpha: float

Transparency of the filled Zone objects, if the fill_zones option is selected.

The closer alpha is to 1.0, the more opaque the overlay will be. Similarly, the closer alpha is to 0.0, the more transparent the overlay will appear.

update_image_dimensions(image_width=None, image_height=None)

Update the dimensions of the ZoneList and all included Zone objects.

Parameters:

image_width (Optional[int]) – The new width to update dimensions to
image_height (Optional[int]) – The new height to update dimensions to

get_zone_by_name(zone_name)

Get the Zone that corresponds to the given name.

Parameters:: zone_name (str) – The name of the Zone to retrieve.
Return type:: Zone
Returns:: A Zone that corresponds to the input name.
Raises:: ValueError if zone of zone_name doesn’t exist in list

get_zones_for_prediction(prediction, **kwargs)

Get the Zone objects that this prediction is currently within.

Parameters:: prediction (ObjectDetectionPrediction) – The prediction to check for associated Zone objects.
Return type:: ZoneList
Returns:: A ZoneList containing Zone objects that this prediction is currently within.

get_zone_for_prediction(prediction, **kwargs)

Get the Zone object that this prediction is currently within. If there are intersecting zones the zone with the higher index is returned. Returns None if no zone is present

Parameters:: prediction (ObjectDetectionPrediction) – The prediction to check for associated Zone object.
Return type:: Optional[Zone]
Returns:: A Zone object that this prediction is currently within.

get_predictions_in_zone(results, zone_name, **kwargs)

Get the predictions that are within the given zone.

Parameters:

results (ObjectDetectionResults) – The ObjectDetectionResults to check against the given zone.
zone_name (str) – The name of zone to check results against.

Return type:

ObjectDetectionResults

Returns:

A :class:ObjectDetectionResults containing predictions that are within the given zone.

Raises:

ValueError if the given zone name doesn’t match a zone.

get_tracked_objects_in_zone(results, zone_name)

Get the tracked objects that are within the given zone.

Parameters:

results (TrackingResults) – The TrackingResults to check against the given zone.
zone_name (str) – The name of zone to check results against.

Return type:

TrackingResults

Returns:

A TrackingResults containing predictions that are within the given zone.

Raises:

ValueError if the given zone name doesn’t match a zone.

create_sub_zone_list(zone_names)

Create a new ZoneList containing a subset of Zone objects.

Parameters:: name_list – The list of names that correspond to Zone objects that should be in the new ZoneList
Returns:: A new ZoneList containing the subset of Zone objects.
Raises:: ValueError if any of the names do not match a zone

markup_image_with_zones(image, show_labels=True, show_boundaries=True, fill_zones=False, line_thickness=2, font_size=0.5, font_thickness=2, text_box_padding=10, text_box_corner_radius=0, text_alignment=('left', 'top'), text_box_position=('left', 'top'))

Mark all zones on the given input image.

Parameters:

frame – The image to mark up.
show_labels (bool) – True if Zone names should be drawn.
show_boundaries (bool) – True if Zone boundaries should be drawn.
fill_zones (bool) – True if Zone objects should have a transparent overlay.
color – The color to draw the Zone boundaries in.
line_thickness (int) – The boundary thickness.
font_size (float) – The font size to use in marking up the labels.
font_thickness (int) – The font thickness to use in marking up the labels. size.
text_box_padding (int) – The padding around the text in each text box.
text_box_corner_radius (int) – The corner radius for the text boxes.
text_alignment (Tuple[Literal['left', 'center', 'right'], Literal['top', 'middle', 'bottom']]) – Specifies the alignment of the text in reference to the origin point (x, y). Accepts a tuple of horizontal (‘left’, ‘center’, ‘right’) and vertical (‘top’, ‘middle’, ‘bottom’) alignment literals.
text_box_position (Union[Tuple[Literal['left', 'center', 'right'], Literal['top', 'middle', 'bottom']], Tuple[int, int]]) – Defines the position of the text box’s reference point relative to the zone box. Can either be a tuple of alignment literals (horizontal, vertical) for automatic positioning, or a tuple of integers (offset_x, offset_y) specifying a custom offset from the center of the bounding box.

Return type:

ndarray

Returns:

The marked-up image.

Note: fill_zones is time-intensive. fill_zones = True will generate the zone mask upon first call.