def visualize_headpose_result(img,
facebox,
est_headpose,
people,
GTlabel=[]):
#ese_headpose = (phi_head, theta_head)
"""Here, we take the original eye eye_image and overlay the estimated headpose."""
output_image = np.copy(img)
box_point = np.copy(facebox)
center_x = (box_point[2] + box_point[0]) / 2
center_y = (box_point[3] + box_point[1]) / 2
endpoint_x, endpoint_y = gaze_tools.get_endpoint(
est_headpose[1], est_headpose[0], center_x, center_y, 100)
# flip vector
#flip_endpoint_x, flip_endpoint_y = gaze_tools.get_endpoint(est_headpose[1], -est_headpose[0], center_x, center_y, 100)
# cv2.arrowedLine(output_image, (int(center_x), int(center_y)), (int(flip_endpoint_x), int(flip_endpoint_y)), (0, 0, 255),2)
headpose_error = 0
if GTlabel != []:
GT_endpoint_x, GT_endpoint_y = gaze_tools.get_endpoint(
GTlabel[2], GTlabel[1], center_x, center_y, 100)
headpose_error = gaze_tools.get_error(
[GT_endpoint_x, GT_endpoint_y], [endpoint_x, endpoint_y],
[center_x, center_y])
#Smoothing
# endpoint_x ,endpoint_y =people.getEndpointAverage(endpoint_x, endpoint_y, "headpose")
cv2.arrowedLine(output_image, (int(center_x), int(center_y)),
(int(endpoint_x), int(endpoint_y)), (0, 0, 255), 2)
return output_image, headpose_error
def visualize_eye_result(eye_image, est_gaze):
"""Here, we take the original eye eye_image and overlay the estimated gaze."""
output_image = np.copy(eye_image)
center_x = output_image.shape[1] / 2
center_y = output_image.shape[0] / 2
endpoint_x, endpoint_y = get_endpoint(est_gaze[0], est_gaze[1], center_x, center_y, 50)
cv2.line(output_image, (int(center_x), int(center_y)), (int(endpoint_x), int(endpoint_y)), (255, 0, 0))
return output_image
def visualize_headpose_result(face_image, est_headpose):
"""Here, we take the original eye eye_image and overlay the estimated headpose."""
output_image = np.copy(face_image)
center_x = output_image.shape[1] / 2
center_y = output_image.shape[0] / 2
endpoint_x, endpoint_y = gaze_tools.get_endpoint(
est_headpose[1], est_headpose[0], center_x, center_y, 100)
cv2.line(output_image, (int(center_x), int(center_y)),
(int(endpoint_x), int(endpoint_y)), (0, 0, 255), 3)
return output_image
def visualize_eye_result(self, eye_image, est_gaze):
"""Here, we take the original eye eye_image and overlay the estimated gaze."""
output_image = np.copy(eye_image)
center_x = self.image_width / 2
center_y = self.image_height / 2
endpoint_x, endpoint_y = gaze_tools.get_endpoint(
est_gaze[0], est_gaze[1], center_x, center_y, 50)
cv2.line(output_image, (int(center_x), int(center_y)),
(int(endpoint_x), int(endpoint_y)), (255, 0, 0))
return output_image
def visualize_eye_result(color_img,
est_gaze,
center_coor,
facebox,
people,
selection,
GTlabel=[]):
# est_gaze = [theta,phi]
"""Here, we take the original eye eye_image and overlay the estimated gaze."""
output_image = np.copy(color_img)
center_x = facebox[0] + center_coor[0]
center_y = facebox[1] + center_coor[1]
endpoint_x, endpoint_y = get_endpoint(est_gaze[0], est_gaze[1],
center_x, center_y, 150)
#flip vector
# flip_endpoint_x, flip_endpoint_y = get_endpoint(est_gaze[0], -est_gaze[1], center_x, center_y, 150)
# cv2.arrowedLine(output_image, (int(center_x), int(center_y)), (int(flip_endpoint_x), int(flip_endpoint_y)), (255, 0, 0), 2)
# print("gaze_phi:",est_gaze[1])
# print("flip gaze_phi:",-est_gaze[1])
gaze_error = 0
if GTlabel != []:
GT_endpoint_x, GT_endpoint_y = get_endpoint(
GTlabel[4], GTlabel[3], center_x, center_y, 150)
gaze_error = get_error([GT_endpoint_x, GT_endpoint_y],
[endpoint_x, endpoint_y],
[center_x, center_y])
#Smoothing
# endpoint_x, endpoint_y = people.getEndpointAverage(endpoint_x, endpoint_y, selection)
cv2.arrowedLine(output_image, (int(center_x), int(center_y)),
(int(endpoint_x), int(endpoint_y)), (255, 0, 0), 2)
return output_image, gaze_error
def visualize_eye_result(eye_image, est_gaze):
"""Here, we take the original eye eye_image and overlay the estimated gaze."""
output_image = np.copy(eye_image)
center_x = output_image.shape[1] / 2
center_y = output_image.shape[0] / 2
endpoint_x, endpoint_y = get_endpoint(est_gaze[0], est_gaze[1],
center_x, center_y, 50)
# cv2.line(output_image, (int(center_x), int(center_y)), (int(endpoint_x), int(endpoint_y)), (255, 0, 0))
# cv2.arrowedLine(output_image, (int(center_x), int(center_y)), (int(endpoint_x), int(endpoint_y)), (0, 255, 0),
# tipLength=0.2)
cv2.arrowedLine(output_image, (int(center_x), int(center_y)),
(int(endpoint_x * 1.5), int(endpoint_y * 1.5)),
(0, 255, 0),
thickness=2,
tipLength=0.4)
return output_image
