Add line counting and circular heatmaps in Ultralytics Solutions (#7113)
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Muhammad Rizwan Munawar
GitHub
parent
a5735724c5
commit
38eaf5e29f
5 changed files with 526 additions and 247 deletions
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@ -10,8 +10,7 @@ from ultralytics.utils.plotting import Annotator
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check_requirements('shapely>=2.0.0')
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from shapely.geometry import Polygon
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from shapely.geometry.point import Point
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from shapely.geometry import LineString, Point, Polygon
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class Heatmap:
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@ -23,6 +22,7 @@ class Heatmap:
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# Visual information
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self.annotator = None
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self.view_img = False
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self.shape = 'circle'
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# Image information
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self.imw = None
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@ -38,17 +38,22 @@ class Heatmap:
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self.boxes = None
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self.track_ids = None
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self.clss = None
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self.track_history = None
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self.track_history = defaultdict(list)
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# Counting info
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# Region & Line Information
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self.count_reg_pts = None
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self.count_region = None
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self.counting_region = None
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self.line_dist_thresh = 15
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self.region_thickness = 5
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self.region_color = (255, 0, 255)
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# Object Counting Information
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self.in_counts = 0
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self.out_counts = 0
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self.count_list = []
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self.counting_list = []
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self.count_txt_thickness = 0
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self.count_reg_color = (0, 255, 0)
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self.region_thickness = 5
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self.count_txt_color = (0, 0, 0)
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self.count_color = (255, 255, 255)
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# Decay factor
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self.decay_factor = 0.99
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@ -64,9 +69,13 @@ class Heatmap:
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view_img=False,
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count_reg_pts=None,
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count_txt_thickness=2,
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count_txt_color=(0, 0, 0),
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count_color=(255, 255, 255),
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count_reg_color=(255, 0, 255),
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region_thickness=5,
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decay_factor=0.99):
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line_dist_thresh=15,
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decay_factor=0.99,
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shape='circle'):
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"""
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Configures the heatmap colormap, width, height and display parameters.
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@ -78,27 +87,55 @@ class Heatmap:
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view_img (bool): Flag indicating frame display
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count_reg_pts (list): Object counting region points
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count_txt_thickness (int): Text thickness for object counting display
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count_txt_color (RGB color): count text color value
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count_color (RGB color): count text background color value
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count_reg_color (RGB color): Color of object counting region
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region_thickness (int): Object counting Region thickness
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line_dist_thresh (int): Euclidean Distance threshold for line counter
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decay_factor (float): value for removing heatmap area after object passed
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shape (str): Heatmap shape, rect or circle shape supported
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"""
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self.imw = imw
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self.imh = imh
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self.colormap = colormap
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self.heatmap_alpha = heatmap_alpha
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self.view_img = view_img
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self.colormap = colormap
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self.heatmap = np.zeros((int(self.imw), int(self.imh)), dtype=np.float32) # Heatmap new frame
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# Region and line selection
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if count_reg_pts is not None:
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self.track_history = defaultdict(list)
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self.count_reg_pts = count_reg_pts
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self.count_region = Polygon(self.count_reg_pts)
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self.count_txt_thickness = count_txt_thickness # Counting text thickness
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self.count_reg_color = count_reg_color
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if len(count_reg_pts) == 2:
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print('Line Counter Initiated.')
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self.count_reg_pts = count_reg_pts
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self.counting_region = LineString(count_reg_pts)
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elif len(count_reg_pts) == 4:
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print('Region Counter Initiated.')
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self.count_reg_pts = count_reg_pts
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self.counting_region = Polygon(self.count_reg_pts)
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else:
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print('Region or line points Invalid, 2 or 4 points supported')
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print('Using Line Counter Now')
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self.counting_region = Polygon([(20, 400), (1260, 400)]) # dummy points
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# Heatmap new frame
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self.heatmap = np.zeros((int(self.imw), int(self.imh)), dtype=np.float32)
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self.count_txt_thickness = count_txt_thickness
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self.count_txt_color = count_txt_color
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self.count_color = count_color
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self.region_color = count_reg_color
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self.region_thickness = region_thickness
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self.decay_factor = decay_factor
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self.line_dist_thresh = line_dist_thresh
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self.shape = shape
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# shape of heatmap, if not selected
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if self.shape not in ['circle', 'rect']:
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print("Unknown shape value provided, 'circle' & 'rect' supported")
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print('Using Circular shape now')
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self.shape = 'circle'
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def extract_results(self, tracks):
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"""
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@ -128,13 +165,26 @@ class Heatmap:
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self.annotator = Annotator(self.im0, self.count_txt_thickness, None)
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if self.count_reg_pts is not None:
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# Draw counting region
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self.annotator.draw_region(reg_pts=self.count_reg_pts,
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color=self.count_reg_color,
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color=self.region_color,
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thickness=self.region_thickness)
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for box, cls, track_id in zip(self.boxes, self.clss, self.track_ids):
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self.heatmap[int(box[1]):int(box[3]), int(box[0]):int(box[2])] += 1
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if self.shape == 'circle':
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center = (int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2))
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radius = min(int(box[2]) - int(box[0]), int(box[3]) - int(box[1])) // 2
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y, x = np.ogrid[0:self.heatmap.shape[0], 0:self.heatmap.shape[1]]
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mask = (x - center[0]) ** 2 + (y - center[1]) ** 2 <= radius ** 2
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self.heatmap[int(box[1]):int(box[3]), int(box[0]):int(box[2])] += \
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(2 * mask[int(box[1]):int(box[3]), int(box[0]):int(box[2])])
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else:
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self.heatmap[int(box[1]):int(box[3]), int(box[0]):int(box[2])] += 2
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# Store tracking hist
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track_line = self.track_history[track_id]
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@ -143,16 +193,39 @@ class Heatmap:
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track_line.pop(0)
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# Count objects
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if self.count_region.contains(Point(track_line[-1])):
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if track_id not in self.count_list:
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self.count_list.append(track_id)
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if box[0] < self.count_region.centroid.x:
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self.out_counts += 1
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else:
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self.in_counts += 1
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if len(self.count_reg_pts) == 4:
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if self.counting_region.contains(Point(track_line[-1])):
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if track_id not in self.counting_list:
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self.counting_list.append(track_id)
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if box[0] < self.counting_region.centroid.x:
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self.out_counts += 1
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else:
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self.in_counts += 1
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elif len(self.count_reg_pts) == 2:
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distance = Point(track_line[-1]).distance(self.counting_region)
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if distance < self.line_dist_thresh:
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if track_id not in self.counting_list:
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self.counting_list.append(track_id)
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if box[0] < self.counting_region.centroid.x:
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self.out_counts += 1
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else:
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self.in_counts += 1
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else:
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for box, cls in zip(self.boxes, self.clss):
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self.heatmap[int(box[1]):int(box[3]), int(box[0]):int(box[2])] += 1
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if self.shape == 'circle':
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center = (int((box[0] + box[2]) // 2), int((box[1] + box[3]) // 2))
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radius = min(int(box[2]) - int(box[0]), int(box[3]) - int(box[1])) // 2
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y, x = np.ogrid[0:self.heatmap.shape[0], 0:self.heatmap.shape[1]]
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mask = (x - center[0]) ** 2 + (y - center[1]) ** 2 <= radius ** 2
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self.heatmap[int(box[1]):int(box[3]), int(box[0]):int(box[2])] += \
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(2 * mask[int(box[1]):int(box[3]), int(box[0]):int(box[2])])
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else:
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self.heatmap[int(box[1]):int(box[3]), int(box[0]):int(box[2])] += 2
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# Normalize, apply colormap to heatmap and combine with original image
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heatmap_normalized = cv2.normalize(self.heatmap, None, 0, 255, cv2.NORM_MINMAX)
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@ -161,7 +234,11 @@ class Heatmap:
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if self.count_reg_pts is not None:
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incount_label = 'InCount : ' + f'{self.in_counts}'
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outcount_label = 'OutCount : ' + f'{self.out_counts}'
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self.annotator.count_labels(in_count=incount_label, out_count=outcount_label)
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self.annotator.count_labels(in_count=incount_label,
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out_count=outcount_label,
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count_txt_size=self.count_txt_thickness,
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txt_color=self.count_txt_color,
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color=self.count_color)
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im0_with_heatmap = cv2.addWeighted(self.im0, 1 - self.heatmap_alpha, heatmap_colored, self.heatmap_alpha, 0)
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@ -9,8 +9,7 @@ from ultralytics.utils.plotting import Annotator, colors
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check_requirements('shapely>=2.0.0')
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from shapely.geometry import Polygon
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from shapely.geometry.point import Point
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from shapely.geometry import LineString, Point, Polygon
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class ObjectCounter:
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@ -23,10 +22,12 @@ class ObjectCounter:
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self.is_drawing = False
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self.selected_point = None
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# Region Information
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self.reg_pts = None
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# Region & Line Information
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self.reg_pts = [(20, 400), (1260, 400)]
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self.line_dist_thresh = 15
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self.counting_region = None
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self.region_color = (255, 255, 255)
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self.region_color = (255, 0, 255)
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self.region_thickness = 5
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# Image and annotation Information
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self.im0 = None
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@ -40,11 +41,15 @@ class ObjectCounter:
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self.in_counts = 0
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self.out_counts = 0
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self.counting_list = []
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self.count_txt_thickness = 0
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self.count_txt_color = (0, 0, 0)
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self.count_color = (255, 255, 255)
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# Tracks info
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self.track_history = defaultdict(list)
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self.track_thickness = 2
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self.draw_tracks = False
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self.track_color = (0, 255, 0)
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# Check if environment support imshow
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self.env_check = check_imshow(warn=True)
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@ -52,11 +57,17 @@ class ObjectCounter:
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def set_args(self,
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classes_names,
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reg_pts,
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region_color=None,
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count_reg_color=(255, 0, 255),
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line_thickness=2,
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track_thickness=2,
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view_img=False,
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draw_tracks=False):
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draw_tracks=False,
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count_txt_thickness=2,
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count_txt_color=(0, 0, 0),
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count_color=(255, 255, 255),
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track_color=(0, 255, 0),
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region_thickness=5,
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line_dist_thresh=15):
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"""
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Configures the Counter's image, bounding box line thickness, and counting region points.
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@ -65,18 +76,43 @@ class ObjectCounter:
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view_img (bool): Flag to control whether to display the video stream.
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reg_pts (list): Initial list of points defining the counting region.
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classes_names (dict): Classes names
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region_color (tuple): color for region line
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track_thickness (int): Track thickness
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draw_tracks (Bool): draw tracks
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count_txt_thickness (int): Text thickness for object counting display
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count_txt_color (RGB color): count text color value
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count_color (RGB color): count text background color value
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count_reg_color (RGB color): Color of object counting region
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track_color (RGB color): color for tracks
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region_thickness (int): Object counting Region thickness
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line_dist_thresh (int): Euclidean Distance threshold for line counter
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"""
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self.tf = line_thickness
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self.view_img = view_img
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self.track_thickness = track_thickness
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self.draw_tracks = draw_tracks
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self.reg_pts = reg_pts
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self.counting_region = Polygon(self.reg_pts)
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# Region and line selection
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if len(reg_pts) == 2:
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print('Line Counter Initiated.')
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self.reg_pts = reg_pts
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self.counting_region = LineString(self.reg_pts)
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elif len(reg_pts) == 4:
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print('Region Counter Initiated.')
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self.reg_pts = reg_pts
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self.counting_region = Polygon(self.reg_pts)
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else:
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print('Invalid Region points provided, region_points can be 2 or 4')
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print('Using Line Counter Now')
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self.counting_region = LineString(self.reg_pts)
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self.names = classes_names
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self.region_color = region_color if region_color else self.region_color
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self.track_color = track_color
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self.count_txt_thickness = count_txt_thickness
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self.count_txt_color = count_txt_color
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self.count_color = count_color
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self.region_color = count_reg_color
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self.region_thickness = region_thickness
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self.line_dist_thresh = line_dist_thresh
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def mouse_event_for_region(self, event, x, y, flags, params):
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"""
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@ -113,11 +149,14 @@ class ObjectCounter:
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clss = tracks[0].boxes.cls.cpu().tolist()
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track_ids = tracks[0].boxes.id.int().cpu().tolist()
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# Annotator Init and region drawing
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self.annotator = Annotator(self.im0, self.tf, self.names)
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self.annotator.draw_region(reg_pts=self.reg_pts, color=(0, 255, 0))
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self.annotator.draw_region(reg_pts=self.reg_pts, color=self.region_color, thickness=self.region_thickness)
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# Extract tracks
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for box, track_id, cls in zip(boxes, track_ids, clss):
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self.annotator.box_label(box, label=self.names[cls], color=colors(int(cls), True)) # Draw bounding box
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self.annotator.box_label(box, label=str(track_id) + ':' + self.names[cls],
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color=colors(int(cls), True)) # Draw bounding box
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# Draw Tracks
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track_line = self.track_history[track_id]
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@ -125,28 +164,45 @@ class ObjectCounter:
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if len(track_line) > 30:
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track_line.pop(0)
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# Draw track trails
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if self.draw_tracks:
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self.annotator.draw_centroid_and_tracks(track_line,
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color=(0, 255, 0),
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color=self.track_color,
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track_thickness=self.track_thickness)
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# Count objects
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if self.counting_region.contains(Point(track_line[-1])):
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if track_id not in self.counting_list:
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self.counting_list.append(track_id)
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if box[0] < self.counting_region.centroid.x:
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self.out_counts += 1
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else:
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self.in_counts += 1
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if len(self.reg_pts) == 4:
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if self.counting_region.contains(Point(track_line[-1])):
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if track_id not in self.counting_list:
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self.counting_list.append(track_id)
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if box[0] < self.counting_region.centroid.x:
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self.out_counts += 1
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else:
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self.in_counts += 1
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incount_label = 'InCount : ' + f'{self.in_counts}'
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elif len(self.reg_pts) == 2:
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distance = Point(track_line[-1]).distance(self.counting_region)
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if distance < self.line_dist_thresh:
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if track_id not in self.counting_list:
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self.counting_list.append(track_id)
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if box[0] < self.counting_region.centroid.x:
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self.out_counts += 1
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else:
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self.in_counts += 1
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incount_label = 'In Count : ' + f'{self.in_counts}'
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outcount_label = 'OutCount : ' + f'{self.out_counts}'
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self.annotator.count_labels(in_count=incount_label, out_count=outcount_label)
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self.annotator.count_labels(in_count=incount_label,
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out_count=outcount_label,
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count_txt_size=self.count_txt_thickness,
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txt_color=self.count_txt_color,
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color=self.count_color)
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if self.env_check and self.view_img:
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cv2.namedWindow('Ultralytics YOLOv8 Object Counter')
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cv2.setMouseCallback('Ultralytics YOLOv8 Object Counter', self.mouse_event_for_region,
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{'region_points': self.reg_pts})
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if len(self.reg_pts) == 4: # only add mouse event If user drawn region
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cv2.setMouseCallback('Ultralytics YOLOv8 Object Counter', self.mouse_event_for_region,
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{'region_points': self.reg_pts})
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cv2.imshow('Ultralytics YOLOv8 Object Counter', self.im0)
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# Break Window
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if cv2.waitKey(1) & 0xFF == ord('q'):
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@ -161,6 +217,7 @@ class ObjectCounter:
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tracks (list): List of tracks obtained from the object tracking process.
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"""
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self.im0 = im0 # store image
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if tracks[0].boxes.id is None:
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return
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self.extract_and_process_tracks(tracks)
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@ -260,19 +260,41 @@ class Annotator:
|
|||
|
||||
# Object Counting Annotator
|
||||
def draw_region(self, reg_pts=None, color=(0, 255, 0), thickness=5):
|
||||
# Draw region line
|
||||
"""
|
||||
Draw region line
|
||||
Args:
|
||||
reg_pts (list): Region Points (for line 2 points, for region 4 points)
|
||||
color (tuple): Region Color value
|
||||
thickness (int): Region area thickness value
|
||||
"""
|
||||
cv2.polylines(self.im, [np.array(reg_pts, dtype=np.int32)], isClosed=True, color=color, thickness=thickness)
|
||||
|
||||
def draw_centroid_and_tracks(self, track, color=(255, 0, 255), track_thickness=2):
|
||||
# Draw region line
|
||||
"""
|
||||
Draw centroid point and track trails
|
||||
Args:
|
||||
track (list): object tracking points for trails display
|
||||
color (tuple): tracks line color
|
||||
track_thickness (int): track line thickness value
|
||||
"""
|
||||
points = np.hstack(track).astype(np.int32).reshape((-1, 1, 2))
|
||||
cv2.polylines(self.im, [points], isClosed=False, color=color, thickness=track_thickness)
|
||||
cv2.circle(self.im, (int(track[-1][0]), int(track[-1][1])), track_thickness * 2, color, -1)
|
||||
|
||||
def count_labels(self, in_count=0, out_count=0, color=(255, 255, 255), txt_color=(0, 0, 0)):
|
||||
def count_labels(self, in_count=0, out_count=0, count_txt_size=2, color=(255, 255, 255), txt_color=(0, 0, 0)):
|
||||
"""
|
||||
Plot counts for object counter
|
||||
Args:
|
||||
in_count (int): in count value
|
||||
out_count (int): out count value
|
||||
count_txt_size (int): text size for counts display
|
||||
color (tuple): background color of counts display
|
||||
txt_color (tuple): text color of counts display
|
||||
"""
|
||||
self.tf = count_txt_size
|
||||
tl = self.tf or round(0.002 * (self.im.shape[0] + self.im.shape[1]) / 2) + 1
|
||||
tf = max(tl - 1, 1)
|
||||
gap = int(24 * tl) # Calculate the gap between in_count and out_count based on line_thickness
|
||||
gap = int(24 * tl) # gap between in_count and out_count based on line_thickness
|
||||
|
||||
# Get text size for in_count and out_count
|
||||
t_size_in = cv2.getTextSize(str(in_count), 0, fontScale=tl / 2, thickness=tf)[0]
|
||||
|
|
@ -306,14 +328,13 @@ class Annotator:
|
|||
thickness=self.tf,
|
||||
lineType=cv2.LINE_AA)
|
||||
|
||||
# AI GYM Annotator
|
||||
def estimate_pose_angle(self, a, b, c):
|
||||
@staticmethod
|
||||
def estimate_pose_angle(a, b, c):
|
||||
"""Calculate the pose angle for object
|
||||
Args:
|
||||
a (float) : The value of pose point a
|
||||
b (float): The value of pose point b
|
||||
c (float): The value o pose point c
|
||||
|
||||
Returns:
|
||||
angle (degree): Degree value of angle between three points
|
||||
"""
|
||||
|
|
@ -325,7 +346,15 @@ class Annotator:
|
|||
return angle
|
||||
|
||||
def draw_specific_points(self, keypoints, indices=[2, 5, 7], shape=(640, 640), radius=2):
|
||||
"""Draw specific keypoints for gym steps counting."""
|
||||
"""
|
||||
Draw specific keypoints for gym steps counting.
|
||||
|
||||
Args:
|
||||
keypoints (list): list of keypoints data to be plotted
|
||||
indices (list): keypoints ids list to be plotted
|
||||
shape (tuple): imgsz for model inference
|
||||
radius (int): Keypoint radius value
|
||||
"""
|
||||
nkpts, ndim = keypoints.shape
|
||||
nkpts == 17 and ndim == 3
|
||||
for i, k in enumerate(keypoints):
|
||||
|
|
@ -340,8 +369,17 @@ class Annotator:
|
|||
return self.im
|
||||
|
||||
def plot_angle_and_count_and_stage(self, angle_text, count_text, stage_text, center_kpt, line_thickness=2):
|
||||
"""Plot the pose angle, count value and step stage."""
|
||||
angle_text, count_text, stage_text = f' {angle_text:.2f}', 'Steps : ' + f'{count_text}', f' {stage_text}'
|
||||
"""
|
||||
Plot the pose angle, count value and step stage.
|
||||
|
||||
Args:
|
||||
angle_text (str): angle value for workout monitoring
|
||||
count_text (str): counts value for workout monitoring
|
||||
stage_text (str): stage decision for workout monitoring
|
||||
center_kpt (int): centroid pose index for workout monitoring
|
||||
line_thickness (int): thickness for text display
|
||||
"""
|
||||
angle_text, count_text, stage_text = (f' {angle_text:.2f}', 'Steps : ' + f'{count_text}', f' {stage_text}')
|
||||
font_scale = 0.6 + (line_thickness / 10.0)
|
||||
|
||||
# Draw angle
|
||||
|
|
@ -378,18 +416,38 @@ class Annotator:
|
|||
cv2.putText(self.im, stage_text, stage_text_position, 0, font_scale, (0, 0, 0), line_thickness)
|
||||
|
||||
def seg_bbox(self, mask, mask_color=(255, 0, 255), det_label=None, track_label=None):
|
||||
"""Function for drawing segmented object in bounding box shape."""
|
||||
"""
|
||||
Function for drawing segmented object in bounding box shape.
|
||||
|
||||
Args:
|
||||
mask (list): masks data list for instance segmentation area plotting
|
||||
mask_color (tuple): mask foreground color
|
||||
det_label (str): Detection label text
|
||||
track_label (str): Tracking label text
|
||||
"""
|
||||
cv2.polylines(self.im, [np.int32([mask])], isClosed=True, color=mask_color, thickness=2)
|
||||
|
||||
label = f'Track ID: {track_label}' if track_label else det_label
|
||||
text_size, _ = cv2.getTextSize(label, 0, 0.7, 1)
|
||||
|
||||
cv2.rectangle(self.im, (int(mask[0][0]) - text_size[0] // 2 - 10, int(mask[0][1]) - text_size[1] - 10),
|
||||
(int(mask[0][0]) + text_size[0] // 2 + 5, int(mask[0][1] + 5)), mask_color, -1)
|
||||
|
||||
cv2.putText(self.im, label, (int(mask[0][0]) - text_size[0] // 2, int(mask[0][1]) - 5), 0, 0.7, (255, 255, 255),
|
||||
2)
|
||||
|
||||
def visioneye(self, box, center_point, color=(235, 219, 11), pin_color=(255, 0, 255), thickness=2, pins_radius=10):
|
||||
"""Function for pinpoint human-vision eye mapping and plotting."""
|
||||
"""
|
||||
Function for pinpoint human-vision eye mapping and plotting.
|
||||
|
||||
Args:
|
||||
box (list): Bounding box coordinates
|
||||
center_point (tuple): center point for vision eye view
|
||||
color (tuple): object centroid and line color value
|
||||
pin_color (tuple): visioneye point color value
|
||||
thickness (int): int value for line thickness
|
||||
pins_radius (int): visioneye point radius value
|
||||
"""
|
||||
center_bbox = int((box[0] + box[2]) / 2), int((box[1] + box[3]) / 2)
|
||||
cv2.circle(self.im, center_point, pins_radius, pin_color, -1)
|
||||
cv2.circle(self.im, center_bbox, pins_radius, color, -1)
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue