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Refactor all Ultralytics Solutions (#12790)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: RizwanMunawar <chr043416@gmail.com>
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Glenn Jocher 2024-05-18 18:14:42 +02:00 • committed by GitHub
parent a2ecb24176
commit 2af71d15a6
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134 changed files with 845 additions and 1020 deletions
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145
ultralytics/solutions/queue_management.py
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@ -13,49 +13,12 @@ from shapely.geometry import Point, Polygon
class QueueManager:
"""A class to manage the queue management in real-time video stream based on their tracks."""
"""A class to manage the queue in a real-time video stream based on object tracks."""
def __init__(self):
"""Initializes the queue manager with default values for various tracking and counting parameters."""
# Mouse events
self.is_drawing = False
self.selected_point = None
# Region & Line Information
self.reg_pts = [(20, 60), (20, 680), (1120, 680), (1120, 60)]
self.counting_region = None
self.region_color = (255, 0, 255)
self.region_thickness = 5
# Image and annotation Information
self.im0 = None
self.tf = None
self.view_img = False
self.view_queue_counts = True
self.fontsize = 0.6
self.names = None # Classes names
self.annotator = None # Annotator
self.window_name = "Ultralytics YOLOv8 Queue Manager"
# Object counting Information
self.counts = 0
self.count_txt_color = (255, 255, 255)
# Tracks info
self.track_history = defaultdict(list)
self.track_thickness = 2
self.draw_tracks = False
self.track_color = None
# Check if environment support imshow
self.env_check = check_imshow(warn=True)
def set_args(
def __init__(
self,
classes_names,
reg_pts,
reg_pts=None,
line_thickness=2,
track_thickness=2,
view_img=False,
@ -68,48 +31,65 @@ class QueueManager:
fontsize=0.7,
):
"""
Configures the Counter's image, bounding box line thickness, and counting region points.
Initializes the QueueManager with specified parameters for tracking and counting objects.
Args:
line_thickness (int): Line thickness for bounding boxes.
view_img (bool): Flag to control whether to display the video stream.
view_queue_counts (bool): Flag to control whether to display the counts on video stream.
reg_pts (list): Initial list of points defining the counting region.
classes_names (dict): Classes names
region_color (RGB color): Color of queue region
track_thickness (int): Track thickness
draw_tracks (Bool): draw tracks
count_txt_color (RGB color): count text color value
track_color (RGB color): color for tracks
region_thickness (int): Object counting Region thickness
fontsize (float): Text display font size
classes_names (dict): A dictionary mapping class IDs to class names.
reg_pts (list of tuples, optional): Points defining the counting region polygon. Defaults to a predefined
rectangle.
line_thickness (int, optional): Thickness of the annotation lines. Defaults to 2.
track_thickness (int, optional): Thickness of the track lines. Defaults to 2.
view_img (bool, optional): Whether to display the image frames. Defaults to False.
region_color (tuple, optional): Color of the counting region lines (BGR). Defaults to (255, 0, 255).
view_queue_counts (bool, optional): Whether to display the queue counts. Defaults to True.
draw_tracks (bool, optional): Whether to draw tracks of the objects. Defaults to False.
count_txt_color (tuple, optional): Color of the count text (BGR). Defaults to (255, 255, 255).
track_color (tuple, optional): Color of the tracks. If None, different colors will be used for different
tracks. Defaults to None.
region_thickness (int, optional): Thickness of the counting region lines. Defaults to 5.
fontsize (float, optional): Font size for the text annotations. Defaults to 0.7.
"""
# Mouse events state
self.is_drawing = False
self.selected_point = None
# Region & Line Information
self.reg_pts = reg_pts if reg_pts is not None else [(20, 60), (20, 680), (1120, 680), (1120, 60)]
self.counting_region = (
Polygon(self.reg_pts) if len(self.reg_pts) >= 3 else Polygon([(20, 60), (20, 680), (1120, 680), (1120, 60)])
)
self.region_color = region_color
self.region_thickness = region_thickness
# Image and annotation Information
self.im0 = None
self.tf = line_thickness
self.view_img = view_img
self.view_queue_counts = view_queue_counts
self.fontsize = fontsize
self.names = classes_names # Class names
self.annotator = None # Annotator
self.window_name = "Ultralytics YOLOv8 Queue Manager"
# Object counting Information
self.counts = 0
self.count_txt_color = count_txt_color
# Tracks info
self.track_history = defaultdict(list)
self.track_thickness = track_thickness
self.draw_tracks = draw_tracks
self.region_color = region_color
if len(reg_pts) >= 3:
print("Queue region initiated...")
self.reg_pts = reg_pts
self.counting_region = Polygon(self.reg_pts)
else:
print("Invalid region points provided...")
print("Using default region now....")
self.counting_region = Polygon(self.reg_pts)
self.names = classes_names
self.track_color = track_color
self.count_txt_color = count_txt_color
self.region_thickness = region_thickness
self.fontsize = fontsize
# Check if environment supports imshow
self.env_check = check_imshow(warn=True)
def extract_and_process_tracks(self, tracks):
"""Extracts and processes tracks for queue management in a video stream."""
# Annotator Init and queue region drawing
# Initialize annotator and draw the queue region
self.annotator = Annotator(self.im0, self.tf, self.names)
if tracks[0].boxes.id is not None:
@ -122,48 +102,48 @@ class QueueManager:
# Draw bounding box
self.annotator.box_label(box, label=f"{self.names[cls]}#{track_id}", color=colors(int(track_id), True))
# Draw Tracks
# Update track history
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
# Draw track trails if enabled
if self.draw_tracks:
self.annotator.draw_centroid_and_tracks(
track_line,
color=self.track_color if self.track_color else colors(int(track_id), True),
color=self.track_color or colors(int(track_id), True),
track_thickness=self.track_thickness,
)
prev_position = self.track_history[track_id][-2] if len(self.track_history[track_id]) > 1 else None
# Check if the object is inside the counting region
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:
self.counts += 1
label = "Queue Counts : " + str(self.counts)
# Display queue counts
label = f"Queue Counts : {str(self.counts)}"
if label is not None:
self.annotator.queue_counts_display(
label,
points=self.reg_pts,
region_color=self.region_color,
txt_color=self.count_txt_color,
fontsize=self.fontsize,
)
self.counts = 0
self.counts = 0 # Reset counts after displaying
self.display_frames()
def display_frames(self):
"""Display frame."""
"""Displays the current frame with annotations."""
if self.env_check:
self.annotator.draw_region(reg_pts=self.reg_pts, thickness=self.region_thickness, color=self.region_color)
cv2.namedWindow(self.window_name)
cv2.imshow(self.window_name, self.im0)
# Break Window
# Close window on 'q' key press
if cv2.waitKey(1) & 0xFF == ord("q"):
return
@ -175,13 +155,14 @@ class QueueManager:
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
self.im0 = im0 # Store the current frame
self.extract_and_process_tracks(tracks) # Extract and process tracks
if self.view_img:
self.display_frames()
self.display_frames() # Display the frame if enabled
return self.im0
if __name__ == "__main__":
QueueManager()
classes_names = {0: "person", 1: "car"} # example class names
queue_manager = QueueManager(classes_names)