return ear
def mouth_aspect_ratio(mouth):
A = dist.euclidean(mouth[1], mouth[7])
B = dist.euclidean(mouth[2], mouth[6])
C = dist.euclidean(mouth[3], mouth[5])
D = dist.euclidean(mouth[0], mouth[4])
mar = (A + B + C) / (3.0 * D)
return mar
def head_angle(landmark,image)
refImgPts = world.ref2dImagePoints(landmark)
height, width, channels = image.shape
focalLength = args["focal"] * width
cameraMatrix = world.cameraMatrix(focalLength, (height / 2, width / 2))
mdists = np.zeros((4, 1), dtype=np.float64)
# calculate rotation and translation vector using solvePnP
success, rotationVector, translationVector = cv2.solvePnP(face3Dmodel, refImgPts, cameraMatrix, mdists)
noseEndPoints3D = np.array([[0, 0, 1000.0]], dtype=np.float64)
noseEndPoint2D, jacobian = cv2.projectPoints(noseEndPoints3D, rotationVector, translationVector, cameraMatrix, mdists)
# draw nose line
p1 = (int(refImgPts[0, 0]), int(refImgPts[0, 1]))
p2 = (int(noseEndPoint2D[0, 0, 0]), int(noseEndPoint2D[0, 0, 1]))
cv2.line(frame, p1, p2, (110, 220, 0),thickness=2, lineType=cv2.LINE_AA)
def main(image):
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(PREDICTOR_PATH)
while True:
im = cv2.imread(image)
faces = detector(cv2.cvtColor(im, cv2.COLOR_BGR2RGB), 0)
face3Dmodel = world.ref3DModel()
for face in faces:
shape = predictor(cv2.cvtColor(im, cv2.COLOR_BGR2RGB), face)
draw(im, shape)
refImgPts = world.ref2dImagePoints(shape)
height, width, channel = im.shape
focalLength = args.focal * width
cameraMatrix = world.cameraMatrix(focalLength, (height / 2, width / 2))
mdists = np.zeros((4, 1), dtype=np.float64)
# calculate rotation and translation vector using solvePnP
success, rotationVector, translationVector = cv2.solvePnP(
face3Dmodel, refImgPts, cameraMatrix, mdists)
noseEndPoints3D = np.array([[0, 0, 1000.0]], dtype=np.float64)
noseEndPoint2D, jacobian = cv2.projectPoints(
noseEndPoints3D, rotationVector, translationVector, cameraMatrix, mdists)
# draw nose line
p1 = (int(refImgPts[0, 0]), int(refImgPts[0, 1]))
p2 = (int(noseEndPoint2D[0, 0, 0]), int(noseEndPoint2D[0, 0, 1]))
cv2.line(im, p1, p2, (110, 220, 0),
thickness=2, lineType=cv2.LINE_AA)
# calculating angle
rmat, jac = cv2.Rodrigues(rotationVector)
angles, mtxR, mtxQ, Qx, Qy, Qz = cv2.RQDecomp3x3(rmat)
print('*' * 80)
print("Angle: ", angles)
# print(f"Qx:{Qx}\tQy:{Qy}\tQz:{Qz}\t")
x = np.arctan2(Qx[2][1], Qx[2][2])
y = np.arctan2(-Qy[2][0], np.sqrt((Qy[2][1] * Qy[2][1] ) + (Qy[2][2] * Qy[2][2])))
z = np.arctan2(Qz[0][0], Qz[1][0])
print("AxisX: ", x)
print("AxisY: ", y)
print("AxisZ: ", z)
print('*' * 80)
gaze = "Looking: "
if angles[1] < -15:
gaze += "Left"
elif angles[1] > 15:
gaze += "Right"
else:
gaze += "Forward"
cv2.putText(im, gaze, (20, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 80), 2)
cv2.imshow("Head Pose", im)
key = cv2.waitKey(10) & 0xFF
if key == 27:
cv2.imwrite(f"joye-{gaze}.jpg", im)
break
cv2.destroyAllWindows()
def main(source=0):
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(PREDICTOR_PATH)
cap = cv2.VideoCapture(source)
while True:
GAZE = "Face Not Found"
ret, img = cap.read()
if not ret:
print(f"[ERROR - System]Cannot read from source: {source}")
break
faces = detector(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), 0)
face3Dmodel = world.ref3DModel()
for face in faces:
shape = predictor(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), face)
draw(img, shape)
refImgPts = world.ref2dImagePoints(shape)
height, width, channels = img.shape
focalLength = args.focal * width
cameraMatrix = world.cameraMatrix(focalLength, (height / 2, width / 2))
mdists = np.zeros((4, 1), dtype=np.float64)
# calculate rotation and translation vector using solvePnP
success, rotationVector, translationVector = cv2.solvePnP(
face3Dmodel, refImgPts, cameraMatrix, mdists)
noseEndPoints3D = np.array([[0, 0, 1000.0]], dtype=np.float64)
noseEndPoint2D, jacobian = cv2.projectPoints(
noseEndPoints3D, rotationVector, translationVector, cameraMatrix, mdists)
# draw nose line
p1 = (int(refImgPts[0, 0]), int(refImgPts[0, 1]))
p2 = (int(noseEndPoint2D[0, 0, 0]), int(noseEndPoint2D[0, 0, 1]))
cv2.line(img, p1, p2, (110, 220, 0),
thickness=2, lineType=cv2.LINE_AA)
# calculating euler angles
rmat, jac = cv2.Rodrigues(rotationVector)
angles, mtxR, mtxQ, Qx, Qy, Qz = cv2.RQDecomp3x3(rmat)
if angles[1] < -15:
GAZE = "Looking: Left"
elif angles[1] > 15:
GAZE = "Looking: Right"
else:
GAZE = "Forward"
cv2.putText(img, GAZE, (20, 20), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 80), 2)
cv2.imshow("Head Pose", img)
key = cv2.waitKey(10) & 0xFF
if key == 27:
break
cap.release()
cv2.destroyAllWindows()
def main():
predictor = dlib.shape_predictor(PREDICTOR_PATH)
cap = cv2.VideoCapture(args["camsource"])
while True:
GAZE = "Face Not Found"
ret, img = cap.read()
image = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
h, w, c = image.shape
# To improve performance, optionally mark the image as not writeable to
# pass by reference.
image.flags.writeable = False
results = face_detection.process(image)
# Draw the face detection annotations on the image.
image.flags.writeable = True
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
if not ret:
print(
f'[ERROR - System]Cannot read from source: {args["camsource"]}'
)
break
if results.detections:
for detection in results.detections:
location = detection.location_data
relative_bounding_box = location.relative_bounding_box
x_min = relative_bounding_box.xmin
y_min = relative_bounding_box.ymin
widthh = relative_bounding_box.width
heightt = relative_bounding_box.height
absx, absy = mp_drawing._normalized_to_pixel_coordinates(
x_min, y_min, w, h)
abswidth, absheight = mp_drawing._normalized_to_pixel_coordinates(
x_min + widthh, y_min + heightt, w, h)
newrect = dlib.rectangle(absx, absy, abswidth, absheight)
cv2.rectangle(image, (absx, absy), (abswidth, absheight),
(0, 255, 0), 2)
shape = predictor(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), newrect)
draw(image, shape)
refImgPts = world.ref2dImagePoints(shape)
height, width, channels = img.shape
focalLength = args["focal"] * width
cameraMatrix = world.cameraMatrix(focalLength,
(height / 2, width / 2))
mdists = np.zeros((4, 1), dtype=np.float64)
# calculate rotation and translation vector using solvePnP
success, rotationVector, translationVector = cv2.solvePnP(
face3Dmodel, refImgPts, cameraMatrix, mdists)
noseEndPoints3D = np.array([[0, 0, 1000.0]], dtype=np.float64)
noseEndPoint2D, jacobian = cv2.projectPoints(
noseEndPoints3D, rotationVector, translationVector,
cameraMatrix, mdists)
# draw nose line
p1 = (int(refImgPts[0, 0]), int(refImgPts[0, 1]))
p2 = (int(noseEndPoint2D[0, 0, 0]), int(noseEndPoint2D[0, 0, 1]))
cv2.line(image,
p1,
p2, (110, 220, 0),
thickness=2,
lineType=cv2.LINE_AA)
# calculating euler angles
rmat, jac = cv2.Rodrigues(rotationVector)
angles, mtxR, mtxQ, Qx, Qy, Qz = cv2.RQDecomp3x3(rmat)
print('*' * 80)
# print(f"Qx:{Qx}\tQy:{Qy}\tQz:{Qz}\t")
x = np.arctan2(Qx[2][1], Qx[2][2])
y = np.arctan2(
-Qy[2][0],
np.sqrt((Qy[2][1] * Qy[2][1]) + (Qy[2][2] * Qy[2][2])))
z = np.arctan2(Qz[0][0], Qz[1][0])
# print("ThetaX: ", x)
print("ThetaY: ", y)
# print("ThetaZ: ", z)
print('*' * 80)
if angles[1] < -15:
GAZE = "Looking: Left"
elif angles[1] > 15:
GAZE = "Looking: Right"
else:
GAZE = "Forward"
cv2.putText(image, GAZE, (20, 20), cv2.FONT_HERSHEY_SIMPLEX, 1,
(0, 255, 80), 2)
cv2.imshow("Head Pose", image)
key = cv2.waitKey(10) & 0xFF
if key == 27:
break
cap.release()
cv2.destroyAllWindows()
def main():
predictor = dlib.shape_predictor(PREDICTOR_PATH)
cap = cv2.VideoCapture(args["camsource"])
while True:
GAZE = "Face Not Found"
ret, img = cap.read()
if not ret:
print(
f'[ERROR - System]Cannot read from source: {args["camsource"]}'
)
break
#faces = detector(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), 0)
faces = face_recognition.face_locations(img, model="cnn")
for face in faces:
#Extracting the co cordinates to convert them into dlib rectangle object
x = int(face[3])
y = int(face[0])
w = int(abs(face[1] - x))
h = int(abs(face[2] - y))
u = int(face[1])
v = int(face[2])
newrect = dlib.rectangle(x, y, u, v)
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
shape = predictor(cv2.cvtColor(img, cv2.COLOR_BGR2RGB), newrect)
draw(img, shape)
refImgPts = world.ref2dImagePoints(shape)
height, width, channels = img.shape
focalLength = args["focal"] * width
cameraMatrix = world.cameraMatrix(focalLength,
(height / 2, width / 2))
mdists = np.zeros((4, 1), dtype=np.float64)
# calculate rotation and translation vector using solvePnP
success, rotationVector, translationVector = cv2.solvePnP(
face3Dmodel, refImgPts, cameraMatrix, mdists)
noseEndPoints3D = np.array([[0, 0, 1000.0]], dtype=np.float64)
noseEndPoint2D, jacobian = cv2.projectPoints(
noseEndPoints3D, rotationVector, translationVector,
cameraMatrix, mdists)
# draw nose line
p1 = (int(refImgPts[0, 0]), int(refImgPts[0, 1]))
p2 = (int(noseEndPoint2D[0, 0, 0]), int(noseEndPoint2D[0, 0, 1]))
cv2.line(img,
p1,
p2, (110, 220, 0),
thickness=2,
lineType=cv2.LINE_AA)
# calculating euler angles
rmat, jac = cv2.Rodrigues(rotationVector)
angles, mtxR, mtxQ, Qx, Qy, Qz = cv2.RQDecomp3x3(rmat)
print('*' * 80)
# print(f"Qx:{Qx}\tQy:{Qy}\tQz:{Qz}\t")
x = np.arctan2(Qx[2][1], Qx[2][2])
y = np.arctan2(
-Qy[2][0],
np.sqrt((Qy[2][1] * Qy[2][1]) + (Qy[2][2] * Qy[2][2])))
z = np.arctan2(Qz[0][0], Qz[1][0])
# print("ThetaX: ", x)
print("ThetaY: ", y)
# print("ThetaZ: ", z)
print('*' * 80)
if angles[1] < -15:
GAZE = "Looking: Left"
elif angles[1] > 15:
GAZE = "Looking: Right"
else:
GAZE = "Forward"
cv2.putText(img, GAZE, (20, 20), cv2.FONT_HERSHEY_SIMPLEX, 1,
(0, 255, 80), 2)
cv2.imshow("Head Pose", img)
key = cv2.waitKey(10) & 0xFF
if key == 27:
break
cap.release()
cv2.destroyAllWindows()