# Ultralytics YOLO 🚀, AGPL-3.0 license from collections import defaultdict import cv2 from ultralytics.utils.checks import check_imshow, check_requirements from ultralytics.utils.plotting import Annotator, colors check_requirements("shapely>=2.0.0") from shapely.geometry import LineString, Point, Polygon class ObjectCounter: """A class to manage the counting of objects in a real-time video stream based on their tracks.""" def __init__( self, names, reg_pts=None, line_thickness=2, view_img=False, view_in_counts=True, view_out_counts=True, draw_tracks=False, ): """ Initializes the ObjectCounter with various tracking and counting parameters. Args: names (dict): Dictionary of class names. reg_pts (list): List of points defining the counting region. line_thickness (int): Line thickness for bounding boxes. view_img (bool): Flag to control whether to display the video stream. view_in_counts (bool): Flag to control whether to display the in counts on the video stream. view_out_counts (bool): Flag to control whether to display the out counts on the video stream. draw_tracks (bool): Flag to control whether to draw the object tracks. """ # Mouse events self.is_drawing = False self.selected_point = None # Region & Line Information self.reg_pts = [(20, 400), (1260, 400)] if reg_pts is None else reg_pts self.counting_region = None # Image and annotation Information self.im0 = None self.tf = line_thickness self.view_img = view_img self.view_in_counts = view_in_counts self.view_out_counts = view_out_counts self.names = names # Classes names self.window_name = "Ultralytics YOLOv8 Object Counter" # Object counting Information self.in_counts = 0 self.out_counts = 0 self.count_ids = [] self.class_wise_count = {} # Tracks info self.track_history = defaultdict(list) self.draw_tracks = draw_tracks # Check if environment supports imshow self.env_check = check_imshow(warn=True) # Initialize counting region if len(self.reg_pts) == 2: print("Line Counter Initiated.") self.counting_region = LineString(self.reg_pts) elif len(self.reg_pts) >= 3: print("Polygon Counter Initiated.") self.counting_region = Polygon(self.reg_pts) else: print("Invalid Region points provided, region_points must be 2 for lines or >= 3 for polygons.") print("Using Line Counter Now") self.counting_region = LineString(self.reg_pts) # Define the counting line segment self.counting_line_segment = LineString( [ (self.reg_pts[0][0], self.reg_pts[0][1]), (self.reg_pts[1][0], self.reg_pts[1][1]), ] ) def mouse_event_for_region(self, event, x, y, flags, params): """ Handles mouse events for defining and moving the counting region in a real-time video stream. Args: event (int): The type of mouse event (e.g., cv2.EVENT_MOUSEMOVE, cv2.EVENT_LBUTTONDOWN, etc.). x (int): The x-coordinate of the mouse pointer. y (int): The y-coordinate of the mouse pointer. flags (int): Any associated event flags (e.g., cv2.EVENT_FLAG_CTRLKEY, cv2.EVENT_FLAG_SHIFTKEY, etc.). params (dict): Additional parameters for the function. """ if event == cv2.EVENT_LBUTTONDOWN: for i, point in enumerate(self.reg_pts): if ( isinstance(point, (tuple, list)) and len(point) >= 2 and (abs(x - point[0]) < 10 and abs(y - point[1]) < 10) ): self.selected_point = i self.is_drawing = True break elif event == cv2.EVENT_MOUSEMOVE: if self.is_drawing and self.selected_point is not None: self.reg_pts[self.selected_point] = (x, y) self.counting_region = Polygon(self.reg_pts) elif event == cv2.EVENT_LBUTTONUP: self.is_drawing = False self.selected_point = None def extract_and_process_tracks(self, tracks): """Extracts and processes tracks for object counting in a video stream.""" # Annotator Init and region drawing annotator = Annotator(self.im0, self.tf, self.names) # Draw region or line annotator.draw_region(reg_pts=self.reg_pts, color=(104, 0, 123), thickness=self.tf * 2) # Extract tracks for OBB or object detection track_data = tracks[0].obb or tracks[0].boxes if track_data and track_data.id is not None: boxes = track_data.xyxy.cpu() clss = track_data.cls.cpu().tolist() track_ids = track_data.id.int().cpu().tolist() # Extract tracks for box, track_id, cls in zip(boxes, track_ids, clss): # Draw bounding box annotator.box_label(box, label=self.names[cls], color=colors(int(track_id), True)) # Store class info if self.names[cls] not in self.class_wise_count: self.class_wise_count[self.names[cls]] = {"IN": 0, "OUT": 0} # Draw Tracks track_line = self.track_history[track_id] track_line.append((float((box[0] + box[2]) / 2), float((box[1] + box[3]) / 2))) if len(track_line) > 30: track_line.pop(0) # Draw track trails if self.draw_tracks: annotator.draw_centroid_and_tracks( track_line, color=colors(int(track_id), True), track_thickness=self.tf, ) prev_position = self.track_history[track_id][-2] if len(self.track_history[track_id]) > 1 else None # Count objects in any polygon if len(self.reg_pts) >= 3: is_inside = self.counting_region.contains(Point(track_line[-1])) if prev_position is not None and is_inside and track_id not in self.count_ids: self.count_ids.append(track_id) if (box[0] - prev_position[0]) * (self.counting_region.centroid.x - prev_position[0]) > 0: self.in_counts += 1 self.class_wise_count[self.names[cls]]["IN"] += 1 else: self.out_counts += 1 self.class_wise_count[self.names[cls]]["OUT"] += 1 # Count objects using line elif len(self.reg_pts) == 2: if ( prev_position is not None and track_id not in self.count_ids and LineString([(prev_position[0], prev_position[1]), (box[0], box[1])]).intersects( self.counting_line_segment ) ): self.count_ids.append(track_id) # Determine the direction of movement (IN or OUT) dx = (box[0] - prev_position[0]) * (self.counting_region.centroid.x - prev_position[0]) dy = (box[1] - prev_position[1]) * (self.counting_region.centroid.y - prev_position[1]) if dx > 0 and dy > 0: self.in_counts += 1 self.class_wise_count[self.names[cls]]["IN"] += 1 else: self.out_counts += 1 self.class_wise_count[self.names[cls]]["OUT"] += 1 labels_dict = {} for key, value in self.class_wise_count.items(): if value["IN"] != 0 or value["OUT"] != 0: if not self.view_in_counts and not self.view_out_counts: continue elif not self.view_in_counts: labels_dict[str.capitalize(key)] = f"OUT {value['OUT']}" elif not self.view_out_counts: labels_dict[str.capitalize(key)] = f"IN {value['IN']}" else: labels_dict[str.capitalize(key)] = f"IN {value['IN']} OUT {value['OUT']}" if labels_dict: annotator.display_analytics(self.im0, labels_dict, (104, 31, 17), (255, 255, 255), 10) def display_frames(self): """Displays the current frame with annotations and regions in a window.""" if self.env_check: cv2.namedWindow(self.window_name) if len(self.reg_pts) == 4: # only add mouse event If user drawn region cv2.setMouseCallback(self.window_name, self.mouse_event_for_region, {"region_points": self.reg_pts}) cv2.imshow(self.window_name, self.im0) # Break Window if cv2.waitKey(1) & 0xFF == ord("q"): return def start_counting(self, im0, tracks): """ Main function to start the object counting process. Args: im0 (ndarray): Current frame from the video stream. tracks (list): List of tracks obtained from the object tracking process. """ self.im0 = im0 # store image self.extract_and_process_tracks(tracks) # draw region even if no objects if self.view_img: self.display_frames() return self.im0 if __name__ == "__main__": classes_names = {0: "person", 1: "car"} # example class names ObjectCounter(classes_names)