def print_points(point1, point2):
if ClassUtils.check_point_integrity(point1, min_score) and \
ClassUtils.check_point_integrity(point2, min_score):
print('Point1: {0} - Point2: {1}'.format(point1, point2))
distance_plumb = ClassUtils.get_euclidean_distance_pt(point1, point2)
print('Distance plumb: {0}'.format(distance_plumb))
def main():
print('Generating angle descriptors')
# Initializing instances
instance_pose = ClassOpenPose()
# Reading pose from dir path
image = '/home/mauricio/Pictures/walk.jpg'
if not os.path.exists(image):
print('The path {0} does not exists'.format(image))
else:
img_cv = cv2.imread(image)
# Forwarding image
arr, output_img = instance_pose.recognize_image_tuple(img_cv)
person_array = arr[0]
# Generating other descriptors
# Assume image is OK
shoulder_dis = ClassUtils.get_euclidean_distance_pt(person_array[1], person_array[2]) + \
ClassUtils.get_euclidean_distance_pt(person_array[1], person_array[5])
torso_dis = ClassUtils.get_euclidean_distance_pt(person_array[1], person_array[8])
# In total, we have a vector with 8 angles
# We need to extract the characteristics of the 8 angles
relation = shoulder_dis / torso_dis
print(relation)
cv2.namedWindow('main_window', cv2.WND_PROP_AUTOSIZE)
cv2.imshow('main_window', output_img)
cv2.waitKey(0)
cv2.destroyAllWindows()
print('Done!')
