wjs/yolo_safehat_num_v8/ultralytics/solutions/object_counter.py

284 lines
11 KiB
Python

# 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):
"""Initializes the Counter 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, 400), (1260, 400)]
self.line_dist_thresh = 15
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_in_counts = True
self.view_out_counts = True
self.names = None # Classes names
self.annotator = None # Annotator
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 = {}
self.count_txt_thickness = 0
self.count_txt_color = (255, 255, 255)
self.count_bg_color = (255, 255, 255)
self.cls_txtdisplay_gap = 50
self.fontsize = 0.6
# 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(
self,
classes_names,
reg_pts,
count_reg_color=(255, 0, 255),
count_txt_color=(0, 0, 0),
count_bg_color=(255, 255, 255),
line_thickness=2,
track_thickness=2,
view_img=False,
view_in_counts=True,
view_out_counts=True,
draw_tracks=False,
track_color=None,
region_thickness=5,
line_dist_thresh=15,
cls_txtdisplay_gap=50,
):
"""
Configures the Counter's image, bounding box line thickness, and counting region points.
Args:
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 incounts on video stream.
view_out_counts (bool): Flag to control whether to display the outcounts on video stream.
reg_pts (list): Initial list of points defining the counting region.
classes_names (dict): Classes names
track_thickness (int): Track thickness
draw_tracks (Bool): draw tracks
count_txt_color (RGB color): count text color value
count_bg_color (RGB color): count highlighter line color
count_reg_color (RGB color): Color of object counting region
track_color (RGB color): color for tracks
region_thickness (int): Object counting Region thickness
line_dist_thresh (int): Euclidean Distance threshold for line counter
cls_txtdisplay_gap (int): Display gap between each class count
"""
self.tf = line_thickness
self.view_img = view_img
self.view_in_counts = view_in_counts
self.view_out_counts = view_out_counts
self.track_thickness = track_thickness
self.draw_tracks = draw_tracks
# Region and line selection
if len(reg_pts) == 2:
print("Line Counter Initiated.")
self.reg_pts = reg_pts
self.counting_region = LineString(self.reg_pts)
elif len(reg_pts) >= 3:
print("Polygon Counter Initiated.")
self.reg_pts = reg_pts
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)
self.names = classes_names
self.track_color = track_color
self.count_txt_color = count_txt_color
self.count_bg_color = count_bg_color
self.region_color = count_reg_color
self.region_thickness = region_thickness
self.line_dist_thresh = line_dist_thresh
self.cls_txtdisplay_gap = cls_txtdisplay_gap
def mouse_event_for_region(self, event, x, y, flags, params):
"""
This function is designed to move region with mouse events 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 flags associated with the event (e.g., cv2.EVENT_FLAG_CTRLKEY,
cv2.EVENT_FLAG_SHIFTKEY, etc.).
params (dict): Additional parameters you may want to pass to 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
self.annotator = Annotator(self.im0, self.tf, self.names)
# Draw region or line
self.annotator.draw_region(reg_pts=self.reg_pts, color=self.region_color, thickness=self.region_thickness)
if tracks[0].boxes.id is not None:
boxes = tracks[0].boxes.xyxy.cpu()
clss = tracks[0].boxes.cls.cpu().tolist()
track_ids = tracks[0].boxes.id.int().cpu().tolist()
# Extract tracks
for box, track_id, cls in zip(boxes, track_ids, clss):
# Draw bounding box
self.annotator.box_label(box, label=f"{self.names[cls]}#{track_id}", color=colors(int(track_id), True))
# Store class info
if self.names[cls] not in self.class_wise_count:
if len(self.names[cls]) > 5:
self.names[cls] = self.names[cls][:5]
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:
self.annotator.draw_centroid_and_tracks(
track_line,
color=self.track_color if self.track_color else 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
# 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:
distance = Point(track_line[-1]).distance(self.counting_region)
if distance < self.line_dist_thresh 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
label = "Ultralytics Analytics \t"
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:
label = None
elif not self.view_in_counts:
label += f"{str.capitalize(key)}: IN {value['in']} \t"
elif not self.view_out_counts:
label += f"{str.capitalize(key)}: OUT {value['out']} \t"
else:
label += f"{str.capitalize(key)}: IN {value['in']} OUT {value['out']} \t"
label = label.rstrip()
label = label.split("\t")
if label is not None:
self.annotator.display_counts(
counts=label,
count_txt_color=self.count_txt_color,
count_bg_color=self.count_bg_color,
)
def display_frames(self):
"""Display frame."""
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__":
ObjectCounter()