def _process_frame(self, frame, frame_index, pixel_diff_threshold,
pixel_count_threshold, beta):
# HACK naive implementation of background subtraction
foreground = get_foreground(frame, self.background,
pixel_diff_threshold)
display_foreground = get_foreground(frame, self.display_background,
pixel_diff_threshold)
# update background with running average
self.display_background = self.display_background * beta + frame * (
1. - beta)
# get the two opposite vertices of real bounding box
xx, yy = np.nonzero(foreground)
upper, lower, left, right = find_bounding_box(
xx, yy, pix_count_thres=pixel_count_threshold)
vertices = ((left, upper), (right, lower))
# check whether the foreground is located in mute areas
for rect in self.mute_rects:
fill_zero(foreground, rect)
# get the basic stats of foreground with muted areas (points_count, value, area, ratio, obliqueness)
value = np.sum(foreground)
xx, yy = np.nonzero(foreground)
u_l_l_r = find_bounding_box(xx,
yy,
pix_count_thres=pixel_count_threshold
) # returns upper, lower, left, right
bounding_rectangle = Rectangle(*u_l_l_r)
area = bounding_rectangle.get_area()
ratio = bounding_rectangle.get_ratio()
try:
coords = coords_within_boundary(xx, yy, *u_l_l_r, zero_mean=True)
self.pca_solver.fit(coords)
obliqueness = self.pca_solver.explained_variance_ratio_
except:
obliqueness = 0.5
# check whether the shape of foreground should trigger the alarm
self.parameter_list.append((len(xx), value, area, ratio, obliqueness))
if self.threshold.check(len(xx), value, area, ratio, obliqueness):
cv2.rectangle(frame, *vertices, color=(0, 0, 255))
cv2.putText(frame, "WARNING", (left, upper),
cv2.FONT_HERSHEY_DUPLEX, 1, (0, 0, 255))
self._trigger_alarm(frame_index, frame)
else:
cv2.rectangle(frame, *vertices, color=(255, 0, 0))
cv2.putText(frame, "Object", (left, upper),
cv2.FONT_HERSHEY_DUPLEX, 1, (255, 0, 0))
return frame, display_foreground
