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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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self.is_drawing = False |
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self.selected_point = None |
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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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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 |
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self.annotator = None |
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self.window_name = "Ultralytics YOLOv8 Object Counter" |
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self.in_counts = 0 |
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self.out_counts = 0 |
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self.counting_dict = {} |
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self.count_txt_thickness = 0 |
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self.count_txt_color = (0, 0, 0) |
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self.count_color = (255, 255, 255) |
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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 = (0, 255, 0) |
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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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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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count_txt_thickness=2, |
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count_txt_color=(0, 0, 0), |
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count_color=(255, 255, 255), |
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track_color=(0, 255, 0), |
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region_thickness=5, |
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line_dist_thresh=15, |
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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_thickness (int): Text thickness for object counting display |
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count_txt_color (RGB color): count text color value |
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count_color (RGB color): count text background color value |
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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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""" |
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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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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("Region 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_thickness = count_txt_thickness |
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self.count_txt_color = count_txt_color |
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self.count_color = count_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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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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self.annotator = Annotator(self.im0, self.tf, self.names) |
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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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for box, track_id, cls in zip(boxes, track_ids, clss): |
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self.annotator.box_label(box, label=f"{track_id}:{self.names[cls]}", color=colors(int(track_id), True)) |
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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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if self.draw_tracks: |
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self.annotator.draw_centroid_and_tracks( |
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track_line, color=self.track_color, 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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centroid = Point((box[:2] + box[2:]) / 2) |
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if len(self.reg_pts) >= 3: |
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is_inside = self.counting_region.contains(centroid) |
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current_position = "in" if is_inside else "out" |
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if prev_position is not None: |
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if self.counting_dict[track_id] != current_position and is_inside: |
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self.in_counts += 1 |
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self.counting_dict[track_id] = "in" |
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elif self.counting_dict[track_id] != current_position and not is_inside: |
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self.out_counts += 1 |
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self.counting_dict[track_id] = "out" |
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else: |
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self.counting_dict[track_id] = current_position |
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else: |
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self.counting_dict[track_id] = current_position |
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elif len(self.reg_pts) == 2: |
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if prev_position is not None: |
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is_inside = (box[0] - prev_position[0]) * ( |
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self.counting_region.centroid.x - prev_position[0] |
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) > 0 |
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current_position = "in" if is_inside else "out" |
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if self.counting_dict[track_id] != current_position and is_inside: |
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self.in_counts += 1 |
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self.counting_dict[track_id] = "in" |
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elif self.counting_dict[track_id] != current_position and not is_inside: |
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self.out_counts += 1 |
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self.counting_dict[track_id] = "out" |
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else: |
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self.counting_dict[track_id] = current_position |
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else: |
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self.counting_dict[track_id] = None |
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incount_label = f"In Count : {self.in_counts}" |
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outcount_label = f"OutCount : {self.out_counts}" |
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counts_label = None |
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if not self.view_in_counts and not self.view_out_counts: |
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counts_label = None |
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elif not self.view_in_counts: |
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counts_label = outcount_label |
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elif not self.view_out_counts: |
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counts_label = incount_label |
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else: |
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counts_label = f"{incount_label} {outcount_label}" |
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if counts_label is not None: |
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self.annotator.count_labels( |
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counts=counts_label, |
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count_txt_size=self.count_txt_thickness, |
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txt_color=self.count_txt_color, |
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color=self.count_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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self.annotator.draw_region(reg_pts=self.reg_pts, color=self.region_color, thickness=self.region_thickness) |
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cv2.namedWindow(self.window_name) |
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if len(self.reg_pts) == 4: |
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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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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 |
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self.extract_and_process_tracks(tracks) |
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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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