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| # Ultralytics 🚀 AGPL-3.0 License - https://ultralytics.com/license | |
| from time import time | |
| import numpy as np | |
| from ultralytics.solutions.solutions import BaseSolution | |
| from ultralytics.utils.plotting import Annotator, colors | |
| class SpeedEstimator(BaseSolution): | |
| """ | |
| A class to estimate the speed of objects in a real-time video stream based on their tracks. | |
| This class extends the BaseSolution class and provides functionality for estimating object speeds using | |
| tracking data in video streams. | |
| Attributes: | |
| spd (Dict[int, float]): Dictionary storing speed data for tracked objects. | |
| trkd_ids (List[int]): List of tracked object IDs that have already been speed-estimated. | |
| trk_pt (Dict[int, float]): Dictionary storing previous timestamps for tracked objects. | |
| trk_pp (Dict[int, Tuple[float, float]]): Dictionary storing previous positions for tracked objects. | |
| annotator (Annotator): Annotator object for drawing on images. | |
| region (List[Tuple[int, int]]): List of points defining the speed estimation region. | |
| track_line (List[Tuple[float, float]]): List of points representing the object's track. | |
| r_s (LineString): LineString object representing the speed estimation region. | |
| Methods: | |
| initialize_region: Initializes the speed estimation region. | |
| estimate_speed: Estimates the speed of objects based on tracking data. | |
| store_tracking_history: Stores the tracking history for an object. | |
| extract_tracks: Extracts tracks from the current frame. | |
| display_output: Displays the output with annotations. | |
| Examples: | |
| >>> estimator = SpeedEstimator() | |
| >>> frame = cv2.imread("frame.jpg") | |
| >>> processed_frame = estimator.estimate_speed(frame) | |
| >>> cv2.imshow("Speed Estimation", processed_frame) | |
| """ | |
| def __init__(self, **kwargs): | |
| """Initializes the SpeedEstimator object with speed estimation parameters and data structures.""" | |
| super().__init__(**kwargs) | |
| self.initialize_region() # Initialize speed region | |
| self.spd = {} # set for speed data | |
| self.trkd_ids = [] # list for already speed_estimated and tracked ID's | |
| self.trk_pt = {} # set for tracks previous time | |
| self.trk_pp = {} # set for tracks previous point | |
| def estimate_speed(self, im0): | |
| """ | |
| Estimates the speed of objects based on tracking data. | |
| Args: | |
| im0 (np.ndarray): Input image for processing. Shape is typically (H, W, C) for RGB images. | |
| Returns: | |
| (np.ndarray): Processed image with speed estimations and annotations. | |
| Examples: | |
| >>> estimator = SpeedEstimator() | |
| >>> image = np.random.randint(0, 255, (480, 640, 3), dtype=np.uint8) | |
| >>> processed_image = estimator.estimate_speed(image) | |
| """ | |
| self.annotator = Annotator(im0, line_width=self.line_width) # Initialize annotator | |
| self.extract_tracks(im0) # Extract tracks | |
| self.annotator.draw_region( | |
| reg_pts=self.region, color=(104, 0, 123), thickness=self.line_width * 2 | |
| ) # Draw region | |
| for box, track_id, cls in zip(self.boxes, self.track_ids, self.clss): | |
| self.store_tracking_history(track_id, box) # Store track history | |
| # Check if track_id is already in self.trk_pp or trk_pt initialize if not | |
| if track_id not in self.trk_pt: | |
| self.trk_pt[track_id] = 0 | |
| if track_id not in self.trk_pp: | |
| self.trk_pp[track_id] = self.track_line[-1] | |
| speed_label = f"{int(self.spd[track_id])} km/h" if track_id in self.spd else self.names[int(cls)] | |
| self.annotator.box_label(box, label=speed_label, color=colors(track_id, True)) # Draw bounding box | |
| # Draw tracks of objects | |
| self.annotator.draw_centroid_and_tracks( | |
| self.track_line, color=colors(int(track_id), True), track_thickness=self.line_width | |
| ) | |
| # Calculate object speed and direction based on region intersection | |
| if self.LineString([self.trk_pp[track_id], self.track_line[-1]]).intersects(self.r_s): | |
| direction = "known" | |
| else: | |
| direction = "unknown" | |
| # Perform speed calculation and tracking updates if direction is valid | |
| if direction == "known" and track_id not in self.trkd_ids: | |
| self.trkd_ids.append(track_id) | |
| time_difference = time() - self.trk_pt[track_id] | |
| if time_difference > 0: | |
| self.spd[track_id] = np.abs(self.track_line[-1][1] - self.trk_pp[track_id][1]) / time_difference | |
| self.trk_pt[track_id] = time() | |
| self.trk_pp[track_id] = self.track_line[-1] | |
| self.display_output(im0) # display output with base class function | |
| return im0 # return output image for more usage | |