bev-project/RMT-PPAD-main/ultralytics/solutions/object_counter.py

239 lines
9.7 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,
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)
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
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:
# Check if the object's movement segment intersects the counting line
if 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)