284 lines
11 KiB
Python
284 lines
11 KiB
Python
# Ultralytics YOLO 🚀, AGPL-3.0 license
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from collections import defaultdict
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import cv2
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from ultralytics.utils.checks import check_imshow, check_requirements
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from ultralytics.utils.plotting import Annotator, colors
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check_requirements("shapely>=2.0.0")
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from shapely.geometry import LineString, Point, Polygon
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class ObjectCounter:
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"""A class to manage the counting of objects in a real-time video stream based on their tracks."""
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def __init__(self):
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"""Initializes the Counter with default values for various tracking and counting parameters."""
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# Mouse events
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self.is_drawing = False
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self.selected_point = None
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# Region & Line Information
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self.reg_pts = [(20, 400), (1260, 400)]
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self.line_dist_thresh = 15
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self.counting_region = None
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self.region_color = (255, 0, 255)
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self.region_thickness = 5
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# Image and annotation Information
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self.im0 = None
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self.tf = None
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self.view_img = False
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self.view_in_counts = True
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self.view_out_counts = True
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self.names = None # Classes names
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self.annotator = None # Annotator
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self.window_name = "Ultralytics YOLOv8 Object Counter"
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# Object counting Information
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self.in_counts = 0
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self.out_counts = 0
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self.count_ids = []
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self.class_wise_count = {}
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self.count_txt_thickness = 0
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self.count_txt_color = (255, 255, 255)
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self.count_bg_color = (255, 255, 255)
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self.cls_txtdisplay_gap = 50
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self.fontsize = 0.6
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# Tracks info
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self.track_history = defaultdict(list)
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self.track_thickness = 2
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self.draw_tracks = False
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self.track_color = None
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# Check if environment support imshow
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self.env_check = check_imshow(warn=True)
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def set_args(
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self,
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classes_names,
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reg_pts,
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count_reg_color=(255, 0, 255),
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count_txt_color=(0, 0, 0),
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count_bg_color=(255, 255, 255),
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line_thickness=2,
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track_thickness=2,
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view_img=False,
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view_in_counts=True,
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view_out_counts=True,
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draw_tracks=False,
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track_color=None,
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region_thickness=5,
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line_dist_thresh=15,
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cls_txtdisplay_gap=50,
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):
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"""
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Configures the Counter's image, bounding box line thickness, and counting region points.
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Args:
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line_thickness (int): Line thickness for bounding boxes.
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view_img (bool): Flag to control whether to display the video stream.
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view_in_counts (bool): Flag to control whether to display the incounts on video stream.
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view_out_counts (bool): Flag to control whether to display the outcounts on video stream.
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reg_pts (list): Initial list of points defining the counting region.
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classes_names (dict): Classes names
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track_thickness (int): Track thickness
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draw_tracks (Bool): draw tracks
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count_txt_color (RGB color): count text color value
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count_bg_color (RGB color): count highlighter line color
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count_reg_color (RGB color): Color of object counting region
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track_color (RGB color): color for tracks
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region_thickness (int): Object counting Region thickness
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line_dist_thresh (int): Euclidean Distance threshold for line counter
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cls_txtdisplay_gap (int): Display gap between each class count
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"""
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self.tf = line_thickness
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self.view_img = view_img
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self.view_in_counts = view_in_counts
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self.view_out_counts = view_out_counts
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self.track_thickness = track_thickness
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self.draw_tracks = draw_tracks
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# Region and line selection
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if len(reg_pts) == 2:
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print("Line Counter Initiated.")
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self.reg_pts = reg_pts
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self.counting_region = LineString(self.reg_pts)
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elif len(reg_pts) >= 3:
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print("Polygon Counter Initiated.")
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self.reg_pts = reg_pts
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self.counting_region = Polygon(self.reg_pts)
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else:
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print("Invalid Region points provided, region_points must be 2 for lines or >= 3 for polygons.")
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print("Using Line Counter Now")
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self.counting_region = LineString(self.reg_pts)
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self.names = classes_names
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self.track_color = track_color
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self.count_txt_color = count_txt_color
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self.count_bg_color = count_bg_color
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self.region_color = count_reg_color
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self.region_thickness = region_thickness
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self.line_dist_thresh = line_dist_thresh
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self.cls_txtdisplay_gap = cls_txtdisplay_gap
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def mouse_event_for_region(self, event, x, y, flags, params):
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"""
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This function is designed to move region with mouse events in a real-time video stream.
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Args:
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event (int): The type of mouse event (e.g., cv2.EVENT_MOUSEMOVE, cv2.EVENT_LBUTTONDOWN, etc.).
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x (int): The x-coordinate of the mouse pointer.
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y (int): The y-coordinate of the mouse pointer.
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flags (int): Any flags associated with the event (e.g., cv2.EVENT_FLAG_CTRLKEY,
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cv2.EVENT_FLAG_SHIFTKEY, etc.).
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params (dict): Additional parameters you may want to pass to the function.
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"""
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if event == cv2.EVENT_LBUTTONDOWN:
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for i, point in enumerate(self.reg_pts):
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if (
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isinstance(point, (tuple, list))
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and len(point) >= 2
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and (abs(x - point[0]) < 10 and abs(y - point[1]) < 10)
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):
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self.selected_point = i
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self.is_drawing = True
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break
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elif event == cv2.EVENT_MOUSEMOVE:
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if self.is_drawing and self.selected_point is not None:
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self.reg_pts[self.selected_point] = (x, y)
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self.counting_region = Polygon(self.reg_pts)
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elif event == cv2.EVENT_LBUTTONUP:
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self.is_drawing = False
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self.selected_point = None
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def extract_and_process_tracks(self, tracks):
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"""Extracts and processes tracks for object counting in a video stream."""
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# Annotator Init and region drawing
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self.annotator = Annotator(self.im0, self.tf, self.names)
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# Draw region or line
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self.annotator.draw_region(reg_pts=self.reg_pts, color=self.region_color, thickness=self.region_thickness)
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if tracks[0].boxes.id is not None:
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boxes = tracks[0].boxes.xyxy.cpu()
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clss = tracks[0].boxes.cls.cpu().tolist()
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track_ids = tracks[0].boxes.id.int().cpu().tolist()
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# Extract tracks
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for box, track_id, cls in zip(boxes, track_ids, clss):
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# Draw bounding box
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self.annotator.box_label(box, label=f"{self.names[cls]}#{track_id}", color=colors(int(track_id), True))
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# Store class info
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if self.names[cls] not in self.class_wise_count:
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if len(self.names[cls]) > 5:
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self.names[cls] = self.names[cls][:5]
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self.class_wise_count[self.names[cls]] = {"in": 0, "out": 0}
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# Draw Tracks
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track_line = self.track_history[track_id]
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track_line.append((float((box[0] + box[2]) / 2), float((box[1] + box[3]) / 2)))
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if len(track_line) > 30:
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track_line.pop(0)
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# Draw track trails
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if self.draw_tracks:
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self.annotator.draw_centroid_and_tracks(
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track_line,
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color=self.track_color if self.track_color else colors(int(track_id), True),
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track_thickness=self.track_thickness,
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)
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prev_position = self.track_history[track_id][-2] if len(self.track_history[track_id]) > 1 else None
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# Count objects in any polygon
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if len(self.reg_pts) >= 3:
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is_inside = self.counting_region.contains(Point(track_line[-1]))
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if prev_position is not None and is_inside and track_id not in self.count_ids:
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self.count_ids.append(track_id)
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if (box[0] - prev_position[0]) * (self.counting_region.centroid.x - prev_position[0]) > 0:
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self.in_counts += 1
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self.class_wise_count[self.names[cls]]["in"] += 1
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else:
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self.out_counts += 1
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self.class_wise_count[self.names[cls]]["out"] += 1
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# Count objects using line
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elif len(self.reg_pts) == 2:
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if prev_position is not None and track_id not in self.count_ids:
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distance = Point(track_line[-1]).distance(self.counting_region)
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if distance < self.line_dist_thresh and track_id not in self.count_ids:
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self.count_ids.append(track_id)
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if (box[0] - prev_position[0]) * (self.counting_region.centroid.x - prev_position[0]) > 0:
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self.in_counts += 1
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self.class_wise_count[self.names[cls]]["in"] += 1
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else:
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self.out_counts += 1
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self.class_wise_count[self.names[cls]]["out"] += 1
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label = "Ultralytics Analytics \t"
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for key, value in self.class_wise_count.items():
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if value["in"] != 0 or value["out"] != 0:
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if not self.view_in_counts and not self.view_out_counts:
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label = None
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elif not self.view_in_counts:
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label += f"{str.capitalize(key)}: IN {value['in']} \t"
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elif not self.view_out_counts:
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label += f"{str.capitalize(key)}: OUT {value['out']} \t"
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else:
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label += f"{str.capitalize(key)}: IN {value['in']} OUT {value['out']} \t"
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label = label.rstrip()
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label = label.split("\t")
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if label is not None:
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self.annotator.display_counts(
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counts=label,
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count_txt_color=self.count_txt_color,
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count_bg_color=self.count_bg_color,
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)
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def display_frames(self):
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"""Display frame."""
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if self.env_check:
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cv2.namedWindow(self.window_name)
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if len(self.reg_pts) == 4: # only add mouse event If user drawn region
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cv2.setMouseCallback(self.window_name, self.mouse_event_for_region, {"region_points": self.reg_pts})
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cv2.imshow(self.window_name, self.im0)
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# Break Window
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if cv2.waitKey(1) & 0xFF == ord("q"):
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return
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def start_counting(self, im0, tracks):
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"""
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Main function to start the object counting process.
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Args:
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im0 (ndarray): Current frame from the video stream.
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tracks (list): List of tracks obtained from the object tracking process.
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"""
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self.im0 = im0 # store image
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self.extract_and_process_tracks(tracks) # draw region even if no objects
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if self.view_img:
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self.display_frames()
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return self.im0
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if __name__ == "__main__":
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ObjectCounter()
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