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187 lines
6.5 KiB
187 lines
6.5 KiB
# 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 Point, Polygon |
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class QueueManager: |
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"""A class to manage the queue management in real-time video stream based on their tracks.""" |
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def __init__(self): |
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"""Initializes the queue manager 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, 60), (20, 680), (1120, 680), (1120, 60)] |
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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_queue_counts = True |
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self.fontsize = 0.6 |
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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 Queue Manager" |
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# Object counting Information |
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self.counts = 0 |
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self.count_txt_color = (255, 255, 255) |
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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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line_thickness=2, |
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track_thickness=2, |
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view_img=False, |
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region_color=(255, 0, 255), |
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view_queue_counts=True, |
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draw_tracks=False, |
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count_txt_color=(255, 255, 255), |
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track_color=None, |
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region_thickness=5, |
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fontsize=0.7, |
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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_queue_counts (bool): Flag to control whether to display the counts 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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region_color (RGB color): Color of queue region |
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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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track_color (RGB color): color for tracks |
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region_thickness (int): Object counting Region thickness |
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fontsize (float): Text display font size |
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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_queue_counts = view_queue_counts |
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self.track_thickness = track_thickness |
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self.draw_tracks = draw_tracks |
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self.region_color = region_color |
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if len(reg_pts) >= 3: |
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print("Queue region 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...") |
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print("Using default region now....") |
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self.counting_region = Polygon(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.region_thickness = region_thickness |
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self.fontsize = fontsize |
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def extract_and_process_tracks(self, tracks): |
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"""Extracts and processes tracks for queue management in a video stream.""" |
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# Annotator Init and queue region drawing |
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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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# 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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# 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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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: |
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self.counts += 1 |
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label = "Queue Counts : " + str(self.counts) |
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if label is not None: |
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self.annotator.queue_counts_display( |
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label, |
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points=self.reg_pts, |
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region_color=self.region_color, |
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txt_color=self.count_txt_color, |
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fontsize=self.fontsize, |
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) |
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self.counts = 0 |
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self.display_frames() |
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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, thickness=self.region_thickness, color=self.region_color) |
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cv2.namedWindow(self.window_name) |
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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 process_queue(self, im0, tracks): |
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""" |
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Main function to start the queue management 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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QueueManager()
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