Fix polygon trigger false positives when bounding boxes are clipped

[YoungjaeDev]

Description

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Fixed an issue where objects partially overlapping with polygons were incorrectly detected. Previously, when a polygon was positioned on the left side of the screen and a person on the right, with the person's bounding box slightly overlapping the polygon, the clip_boxes() function would forcefully clip the boxes to fit within the frame. This caused objects outside the frame to be incorrectly identified as being inside the polygon.

Changes

• Modified the trigger() function to use original bounding box coordinates (pre-clipping) for polygon intersection checks
• This reduces false positives and ensures more accurate counting while maintaining logical consistency

The original bounding box is large, and its bottom center point does not overlap with the polygon. However, during the clipping process, since the bottom-left corner intersects with the polygon, the box is forcefully shrunk. This causes the center point to shift inside the polygon, resulting in false detections.

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Type of change

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• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• This change requires a documentation update

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[SkalskiP]

Hi @YoungjaeDev 👋🏻 I'm not sure I understand correctly. Did your bounding boxes have coordinates that extended beyond the video frame?

[JShengP]

Hi, @SkalskiP 👋
Please also check #844 (comment)
PolygonZone trigger error

[YoungjaeDev]

@SkalskiP

Hi,

In the video, the trigger_anchor settings are BOTTOM_LEFT and BOTTOM_CENTER.

However, as shown in the image, the bounding box of the person had only the left corner inside the polygon, yet the count still increased.

Upon inspecting the zone_count code, it seems that clipping the detections to the polygon’s x-max and y-max causes the bounding box width to narrow. Consequently, the BOTTOM_CENTER anchor ends up inside the polygon, triggering a count.

In the PR I submitted, the code is as follows

original_anchors = np.array([
    np.ceil(detections.get_anchors_coordinates(anchor)).astype(int)
    for anchor in self.triggering_anchors
])

original_anchors_clamped = np.clip(
    original_anchors,
    a_min=[0, 0],
    a_max=[self.mask.shape[1] - 1, self.mask.shape[0] - 1]
)

is_in_zone_original = self.mask[
    original_anchors_clamped[:, :, 1],
    original_anchors_clamped[:, :, 0]
].transpose().astype(bool)

This code calculates the anchors based on the original detection coordinates and clamps them to the polygon mask’s dimensions. This approach avoids distorting the bounding box and accurately checks whether the anchor is within the polygon.

[YoungjaeDev]

Please understand that there are many masks on the image to protect privacy.