ultralytics_solutions_modified/object_counter.py

# Ultralytics YOLO 🚀, AGPL-3.0 license
from collections import defaultdict
import logging
import cv2
import numpy as np
from ultralytics.utils.checks import check_imshow, check_requirements
from ultralytics.utils.plotting import Annotator, colors
from shapely.geometry import LineString, Point, Polygon


# create logger
logger = logging.getLogger(__name__).addHandler(logging.NullHandler())


# need shapely>=2.0.0
check_requirements("shapely>=2.0.0")


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

        # Object counting Information
        self.in_counts = 0
        self.out_counts = 0
        self.out_counts_prev = self.out_counts
        self.in_counts_prev = self.in_counts
        self.counting_list = []
        self.count_txt_thickness = 0
        self.count_txt_color = (0, 0, 0)
        self.count_color = (255, 255, 255)

        # Tracks info
        self.track_history = defaultdict(list)
        self.track_thickness = 2
        self.draw_tracks = False
        self.draw_boxes = False    # added by steve.yin @ 3/1/2024
        self.track_color = (0, 255, 0)

        # 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),
        line_thickness=2,
        track_thickness=2,
        view_img=False,
        view_in_counts=True,
        view_out_counts=True,
        draw_tracks=False,
        draw_boxes=False,  # added by steve.yin @ 3/1/2024
        draw_reg_pts=True,  # added by steve.yin @ 3/1/2024
        count_txt_thickness=2,
        count_txt_color=(0, 0, 0),
        count_color=(255, 255, 255),
        track_color=(0, 255, 0),
        region_thickness=5,
        line_dist_thresh=15,
    ):
        """
        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 display the video stream.
            view_in_counts (bool): Flag to control display the incounts.
            view_out_counts (bool): Flag to control display the outcounts.
            reg_pts (list): Initial list of points for the counting region.
            classes_names (dict): Classes names
            track_thickness (int): Track thickness
            draw_tracks (Bool): draw tracks
            draw_boxes (Bool): draw boxes
            draw_reg_pts (Bool): draw reg_pts
            count_txt_thickness (int): Text thickness object counting display
            count_txt_color (RGB color): count text color value
            count_color (RGB color): count text background color value
            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 line counter
        """
        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
        self.draw_boxes = draw_boxes   # added by steve.yin @ 3/1/2024
        self.draw_reg_pts = draw_reg_pts   # added by steve.yin @ 3/1/2024        

        # Region and line selection
        if len(reg_pts) == 2:
            logging.info("Line Counter Initiated.")
            self.reg_pts = reg_pts
            self.counting_region = LineString(self.reg_pts)
            u = np.array([self.reg_pts[0][0], self.reg_pts[0][1]])
            v = np.array([self.reg_pts[1][0], self.reg_pts[1][1]])
        elif len(reg_pts) == 4:
            logging.info("Region Counter Initiated.")
            self.reg_pts = reg_pts
            self.counting_region = Polygon(self.reg_pts)
            u = np.array([
                (self.reg_pts[0][0] + self.reg_pts[1][0]) / 2,
                (self.reg_pts[0][1] + self.reg_pts[1][1]) / 2,
            ])
            v = np.array([
                (self.reg_pts[2][0] + self.reg_pts[3][0]) / 2,
                (self.reg_pts[2][1] + self.reg_pts[3][1]) / 2,
            ])
        else:
            logging.warning(
                "Invalid Region points, which can only be 2 or 4. " +
                "Using Line Counter Instead!"
            )
            self.counting_region = LineString(self.reg_pts)
            u = np.array(self.counting_region.coords[0])
            v = np.array(
                self.counting_region.coords[len(self.counting_region.coords)-1]
            )
        # get line orientation, rotate ccw 90degrees, get line normal vector
        n = v - u
        nvec = np.array([-n[1], n[0]])
        # print(f"v: {v}, u: {u}, n: {n}, nvec0: {nvec}")
        self.counting_region_nvec = nvec / (np.linalg.norm(nvec) + 1e-6)
        # print(f"nvec: {self.counting_region_nvec}")

        self.names = classes_names
        self.track_color = track_color
        self.count_txt_thickness = count_txt_thickness
        self.count_txt_color = count_txt_color
        self.count_color = count_color
        self.region_color = count_reg_color
        self.region_thickness = region_thickness
        self.line_dist_thresh = line_dist_thresh

    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 passing 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.
        """
        boxes = tracks[0].boxes.xyxy.cpu()
        clss = tracks[0].boxes.cls.cpu().tolist()
        track_ids = tracks[0].boxes.id.int().cpu().tolist()

        # Annotator Init and region drawing
        self.annotator = Annotator(self.im0, self.tf, self.names)
        # self.annotator.draw_region(
        #     reg_pts=self.reg_pts,
        #     color=self.region_color,
        #     thickness=self.region_thickness
        # )

        # Extract tracks
        for box, track_id, cls in zip(boxes, track_ids, clss):
            # Draw bounding box [modified by steve.yin @ 3/1/2024]
            if self.draw_reg_pts:
                self.annotator.draw_region(
                    reg_pts=self.reg_pts,
                    color=self.region_color,
                    thickness=self.region_thickness
                )
            if self.draw_boxes:
                self.annotator.box_label(
                    box=box,
                    label=f"{track_id}:{self.names[cls]}",
                    color=colors(int(cls), True)
                )

            # 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=track_line,
                    color=self.track_color,
                    track_thickness=self.track_thickness
                )

            prev_position = self.track_history[track_id][0] \
                if len(self.track_history[track_id]) > 1 else None

            # Count objects
            if len(self.reg_pts) == 4:
                if (
                    prev_position is not None
                    and self.counting_region.contains(Point(track_line[-1]))
                    and track_id not in self.counting_list
                ):
                    self.counting_list.append(track_id)
                    obj_track_vec = np.array([
                        track_line[-1][0] - prev_position[0],
                        track_line[-1][1] - prev_position[1]
                    ])
                    if np.sign(
                        np.dot(obj_track_vec, self.counting_region_nvec)
                    ) < 0:
                        self.out_counts += 1
                    else:
                        self.in_counts += 1
            elif len(self.reg_pts) == 2:
                if prev_position is not None:
                    distance = Point(track_line[-1]) \
                        .distance(self.counting_region)
                    if (
                        distance < self.line_dist_thresh and
                        track_id not in self.counting_list
                    ):
                        self.counting_list.append(track_id)
                        obj_track_vec = np.array([
                            track_line[-1][0] - prev_position[0],
                            track_line[-1][1] - prev_position[1]
                        ])
                        logging.info(f"obj_track_vec: {obj_track_vec}")
                        if np.sign(
                            np.dot(obj_track_vec, self.counting_region_nvec)
                        ) < 0:
                            self.out_counts += 1
                        else:
                            self.in_counts += 1

        self.outcounts_updated()
        self.incounts_updated()
        self.out_counts_prev = self.out_counts
        self.in_counts_prev = self.in_counts
        incount_label = f"In: {self.in_counts}"
        outcount_label = f"Out: {self.out_counts}"

        # Display counts based on user choice
        counts_label = None
        if not self.view_in_counts and not self.view_out_counts:
            counts_label = None
        elif not self.view_in_counts:
            counts_label = outcount_label
        elif not self.view_out_counts:
            counts_label = incount_label
        else:
            counts_label = f"{incount_label} | {outcount_label}"

        if counts_label is not None:
            self.annotator.count_labels(
                counts=counts_label,
                count_txt_size=self.count_txt_thickness,
                txt_color=self.count_txt_color,
                color=self.count_color,
            )

    def display_frames(self):
        """Display frame."""
        if self.env_check:
            cv2.namedWindow("Ultralytics YOLOv8 Object Counter")
            # only add mouse event If user drawn region
            if len(self.reg_pts) == 4:
                cv2.setMouseCallback(
                    "Ultralytics YOLOv8 Object Counter",
                    self.mouse_event_for_region,
                    {"region_points": self.reg_pts}
                )
            cv2.imshow("Ultralytics YOLOv8 Object Counter", 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

        if tracks[0].boxes.id is None:
            if self.view_img:
                self.display_frames()
            return im0
        self.extract_and_process_tracks(tracks)

        if self.view_img:
            self.display_frames()
        return self.im0

    def incounts_updated(self):
        if self.in_counts_prev < self.in_counts:
            yield f"{self.in_counts}"

    def outcounts_updated(self):
        if self.out_counts_prev < self.out_counts:
            yield f"{self.out_counts}"


if __name__ == "__main__":
    ObjectCounter()