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| # Ultralytics YOLO 🚀, AGPL-3.0 license | |
| from collections import defaultdict | |
| import cv2 | |
| import numpy as np | |
| from ultralytics.utils.checks import check_imshow, check_requirements | |
| from ultralytics.utils.plotting import Annotator | |
| check_requirements("shapely>=2.0.0") | |
| from shapely.geometry import LineString, Point, Polygon | |
| class Heatmap: | |
| """A class to draw heatmaps in real-time video stream based on their tracks.""" | |
| def __init__(self): | |
| """Initializes the heatmap class with default values for Visual, Image, track, count and heatmap parameters.""" | |
| # Visual information | |
| self.annotator = None | |
| self.view_img = False | |
| self.shape = "circle" | |
| # Image information | |
| self.imw = None | |
| self.imh = None | |
| self.im0 = None | |
| self.view_in_counts = True | |
| self.view_out_counts = True | |
| # Heatmap colormap and heatmap np array | |
| self.colormap = None | |
| self.heatmap = None | |
| self.heatmap_alpha = 0.5 | |
| # Predict/track information | |
| self.boxes = None | |
| self.track_ids = None | |
| self.clss = None | |
| self.track_history = defaultdict(list) | |
| # Region & Line Information | |
| self.count_reg_pts = None | |
| self.counting_region = None | |
| self.line_dist_thresh = 15 | |
| self.region_thickness = 5 | |
| self.region_color = (255, 0, 255) | |
| # Object Counting Information | |
| self.in_counts = 0 | |
| self.out_counts = 0 | |
| self.counting_list = [] | |
| self.count_txt_thickness = 0 | |
| self.count_txt_color = (0, 0, 0) | |
| self.count_color = (255, 255, 255) | |
| # Decay factor | |
| self.decay_factor = 0.99 | |
| # Check if environment support imshow | |
| self.env_check = check_imshow(warn=True) | |
| def set_args( | |
| self, | |
| imw, | |
| imh, | |
| colormap=cv2.COLORMAP_JET, | |
| heatmap_alpha=0.5, | |
| view_img=False, | |
| view_in_counts=True, | |
| view_out_counts=True, | |
| count_reg_pts=None, | |
| count_txt_thickness=2, | |
| count_txt_color=(0, 0, 0), | |
| count_color=(255, 255, 255), | |
| count_reg_color=(255, 0, 255), | |
| region_thickness=5, | |
| line_dist_thresh=15, | |
| decay_factor=0.99, | |
| shape="circle", | |
| ): | |
| """ | |
| Configures the heatmap colormap, width, height and display parameters. | |
| Args: | |
| colormap (cv2.COLORMAP): The colormap to be set. | |
| imw (int): The width of the frame. | |
| imh (int): The height of the frame. | |
| heatmap_alpha (float): alpha value for heatmap display | |
| view_img (bool): Flag indicating frame display | |
| 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. | |
| count_reg_pts (list): Object counting region points | |
| count_txt_thickness (int): Text thickness for 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 | |
| region_thickness (int): Object counting Region thickness | |
| line_dist_thresh (int): Euclidean Distance threshold for line counter | |
| decay_factor (float): value for removing heatmap area after object passed | |
| shape (str): Heatmap shape, rect or circle shape supported | |
| """ | |
| self.imw = imw | |
| self.imh = imh | |
| self.heatmap_alpha = heatmap_alpha | |
| self.view_img = view_img | |
| self.view_in_counts = view_in_counts | |
| self.view_out_counts = view_out_counts | |
| self.colormap = colormap | |
| # Region and line selection | |
| if count_reg_pts is not None: | |
| if len(count_reg_pts) == 2: | |
| print("Line Counter Initiated.") | |
| self.count_reg_pts = count_reg_pts | |
| self.counting_region = LineString(count_reg_pts) | |
| elif len(count_reg_pts) == 4: | |
| print("Region Counter Initiated.") | |
| self.count_reg_pts = count_reg_pts | |
| self.counting_region = Polygon(self.count_reg_pts) | |
| else: | |
| print("Region or line points Invalid, 2 or 4 points supported") | |
| print("Using Line Counter Now") | |
| self.counting_region = Polygon([(20, 400), (1260, 400)]) # dummy points | |
| # Heatmap new frame | |
| self.heatmap = np.zeros((int(self.imh), int(self.imw)), dtype=np.float32) | |
| 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.decay_factor = decay_factor | |
| self.line_dist_thresh = line_dist_thresh | |
| self.shape = shape | |
| # shape of heatmap, if not selected | |
| if self.shape not in ["circle", "rect"]: | |
| print("Unknown shape value provided, 'circle' & 'rect' supported") | |
| print("Using Circular shape now") | |
| self.shape = "circle" | |
| def extract_results(self, tracks): | |
| """ | |
| Extracts results from the provided data. | |
| Args: | |
| tracks (list): List of tracks obtained from the object tracking process. | |
| """ | |
| self.boxes = tracks[0].boxes.xyxy.cpu() | |
| self.clss = tracks[0].boxes.cls.cpu().tolist() | |
| self.track_ids = tracks[0].boxes.id.int().cpu().tolist() | |
| def generate_heatmap(self, im0, tracks): | |
| """ | |
| Generate heatmap based on tracking data. | |
| Args: | |
| im0 (nd array): Image | |
| tracks (list): List of tracks obtained from the object tracking process. | |
| """ | |
| self.im0 = im0 | |
| if tracks[0].boxes.id is None: | |
| self.heatmap = np.zeros((int(self.imh), int(self.imw)), dtype=np.float32) | |
| if self.view_img and self.env_check: | |
| self.display_frames() | |
| return im0 | |
| self.heatmap *= self.decay_factor # decay factor | |
| self.extract_results(tracks) | |
| self.annotator = Annotator(self.im0, self.count_txt_thickness, None) | |
| if self.count_reg_pts is not None: | |
| # Draw counting region | |
| if self.view_in_counts or self.view_out_counts: | |
| self.annotator.draw_region( | |
| reg_pts=self.count_reg_pts, color=self.region_color, thickness=self.region_thickness | |
| ) | |
| for box, cls, track_id in zip(self.boxes, self.clss, self.track_ids): | |
| if self.shape == "circle": | |
| center = (int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2)) | |
| radius = min(int(box[2]) - int(box[0]), int(box[3]) - int(box[1])) // 2 | |
| y, x = np.ogrid[0 : self.heatmap.shape[0], 0 : self.heatmap.shape[1]] | |
| mask = (x - center[0]) ** 2 + (y - center[1]) ** 2 <= radius**2 | |
| self.heatmap[int(box[1]) : int(box[3]), int(box[0]) : int(box[2])] += ( | |
| 2 * mask[int(box[1]) : int(box[3]), int(box[0]) : int(box[2])] | |
| ) | |
| else: | |
| self.heatmap[int(box[1]) : int(box[3]), int(box[0]) : int(box[2])] += 2 | |
| # Store tracking hist | |
| 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) | |
| # Count objects | |
| if len(self.count_reg_pts) == 4: | |
| if self.counting_region.contains(Point(track_line[-1])) and track_id not in self.counting_list: | |
| self.counting_list.append(track_id) | |
| if box[0] < self.counting_region.centroid.x: | |
| self.out_counts += 1 | |
| else: | |
| self.in_counts += 1 | |
| elif len(self.count_reg_pts) == 2: | |
| 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) | |
| if box[0] < self.counting_region.centroid.x: | |
| self.out_counts += 1 | |
| else: | |
| self.in_counts += 1 | |
| else: | |
| for box, cls in zip(self.boxes, self.clss): | |
| if self.shape == "circle": | |
| center = (int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2)) | |
| radius = min(int(box[2]) - int(box[0]), int(box[3]) - int(box[1])) // 2 | |
| y, x = np.ogrid[0 : self.heatmap.shape[0], 0 : self.heatmap.shape[1]] | |
| mask = (x - center[0]) ** 2 + (y - center[1]) ** 2 <= radius**2 | |
| self.heatmap[int(box[1]) : int(box[3]), int(box[0]) : int(box[2])] += ( | |
| 2 * mask[int(box[1]) : int(box[3]), int(box[0]) : int(box[2])] | |
| ) | |
| else: | |
| self.heatmap[int(box[1]) : int(box[3]), int(box[0]) : int(box[2])] += 2 | |
| # Normalize, apply colormap to heatmap and combine with original image | |
| heatmap_normalized = cv2.normalize(self.heatmap, None, 0, 255, cv2.NORM_MINMAX) | |
| heatmap_colored = cv2.applyColorMap(heatmap_normalized.astype(np.uint8), self.colormap) | |
| incount_label = f"In Count : {self.in_counts}" | |
| outcount_label = f"OutCount : {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 self.count_reg_pts is not None and 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, | |
| ) | |
| self.im0 = cv2.addWeighted(self.im0, 1 - self.heatmap_alpha, heatmap_colored, self.heatmap_alpha, 0) | |
| if self.env_check and self.view_img: | |
| self.display_frames() | |
| return self.im0 | |
| def display_frames(self): | |
| """Display frame.""" | |
| cv2.imshow("Ultralytics Heatmap", self.im0) | |
| if cv2.waitKey(1) & 0xFF == ord("q"): | |
| return | |
| if __name__ == "__main__": | |
| Heatmap() | |