supervision/supervision/detection/tools/polygon_zone.py

133 lines
4.9 KiB
Python

from dataclasses import replace
from typing import Optional, Tuple
import cv2
import numpy as np
from supervision import Detections
from supervision.detection.utils import clip_boxes, generate_2d_mask
from supervision.draw.color import Color
from supervision.draw.utils import draw_polygon, draw_text
from supervision.geometry.core import Position
from supervision.geometry.utils import get_polygon_center
class PolygonZone:
"""
A class for defining a polygon-shaped zone within a frame for detecting objects.
Attributes:
polygon (np.ndarray): A numpy array defining the polygon vertices
frame_resolution_wh (Tuple[int, int]): The frame resolution (width, height)
triggering_position (Position): The position within the bounding box that triggers the zone (default: Position.BOTTOM_CENTER)
current_count (int): The current count of detected objects within the zone
mask (np.ndarray): The 2D bool mask for the polygon zone
"""
def __init__(
self,
polygon: np.ndarray,
frame_resolution_wh: Tuple[int, int],
triggering_position: Position = Position.BOTTOM_CENTER,
):
self.polygon = polygon
self.frame_resolution_wh = frame_resolution_wh
self.triggering_position = triggering_position
self.current_count = 0
width, height = frame_resolution_wh
self.mask = generate_2d_mask(
polygon=polygon, resolution_wh=(width + 1, height + 1)
)
def trigger(self, detections: Detections) -> np.ndarray:
"""
Determines if the detections are within the polygon zone.
Parameters:
detections (Detections): The detections to be checked against the polygon zone
Returns:
np.ndarray: A boolean numpy array indicating if each detection is within the polygon zone
"""
clipped_xyxy = clip_boxes(
boxes_xyxy=detections.xyxy, frame_resolution_wh=self.frame_resolution_wh
)
clipped_detections = replace(detections, xyxy=clipped_xyxy)
clipped_anchors = np.ceil(
clipped_detections.get_anchor_coordinates(anchor=self.triggering_position)
).astype(int)
is_in_zone = self.mask[clipped_anchors[:, 1], clipped_anchors[:, 0]]
self.current_count = np.sum(is_in_zone)
return is_in_zone.astype(bool)
class PolygonZoneAnnotator:
"""
A class for annotating a polygon-shaped zone within a frame with a count of detected objects.
Attributes:
zone (PolygonZone): The polygon zone to be annotated
color (Color): The color to draw the polygon lines
thickness (int): The thickness of the polygon lines, default is 2
text_color (Color): The color of the text on the polygon, default is black
text_scale (float): The scale of the text on the polygon, default is 0.5
text_thickness (int): The thickness of the text on the polygon, default is 1
text_padding (int): The padding around the text on the polygon, default is 10
font (int): The font type for the text on the polygon, default is cv2.FONT_HERSHEY_SIMPLEX
center (Tuple[int, int]): The center of the polygon for text placement
"""
def __init__(
self,
zone: PolygonZone,
color: Color,
thickness: int = 2,
text_color: Color = Color.black(),
text_scale: float = 0.5,
text_thickness: int = 1,
text_padding: int = 10,
):
self.zone = zone
self.color = color
self.thickness = thickness
self.text_color = text_color
self.text_scale = text_scale
self.text_thickness = text_thickness
self.text_padding = text_padding
self.font = cv2.FONT_HERSHEY_SIMPLEX
self.center = get_polygon_center(polygon=zone.polygon)
def annotate(self, scene: np.ndarray, label: Optional[str] = None) -> np.ndarray:
"""
Annotates the polygon zone within a frame with a count of detected objects.
Parameters:
scene (np.ndarray): The image on which the polygon zone will be annotated
label (Optional[str]): An optional label for the count of detected objects within the polygon zone (default: None)
Returns:
np.ndarray: The image with the polygon zone and count of detected objects
"""
annotated_frame = draw_polygon(
scene=scene,
polygon=self.zone.polygon,
color=self.color,
thickness=self.thickness,
)
annotated_frame = draw_text(
scene=annotated_frame,
text=str(self.zone.current_count) if label is None else label,
text_anchor=self.center,
background_color=self.color,
text_color=self.text_color,
text_scale=self.text_scale,
text_thickness=self.text_thickness,
text_padding=self.text_padding,
text_font=self.font,
)
return annotated_frame