if cap.get(cv2.CAP_PROP_POS_FRAMES) == cap.get(cv2.CAP_PROP_FRAME_COUNT):
cap.set(cv2.CAP_PROP_POS_FRAMES, 0)
success, img = cap.read()
img, faces = detector.findFaceMesh(img, draw=False)
if faces:
face = faces[0]
for id in idList:
cv2.circle(img, face[id], 5, color, cv2.FILLED)
leftUp = face[159]
leftDown = face[23]
leftLeft = face[130]
leftRight = face[243]
lenghtVer, _ = detector.findDistance(leftUp, leftDown)
lenghtHor, _ = detector.findDistance(leftLeft, leftRight)
cv2.line(img, leftUp, leftDown, (0, 200, 0), 3)
cv2.line(img, leftLeft, leftRight, (0, 200, 0), 3)
ratio = int((lenghtVer / lenghtHor) * 100)
ratioList.append(ratio)
if len(ratioList) > 3:
ratioList.pop(0)
ratioAvg = sum(ratioList) / len(ratioList)
if ratioAvg < 35 and counter == 0:
blinkCounter += 1
color = (0, 200, 0)
counter = 1
"Thank you."
]
sen = 25
while True:
success, img = cap.read()
imgText = np.zeros_like(img)
img, faces = detector.findFaceMesh(img, draw=False)
if faces:
face = faces[0]
pointLeft = face[145]
pointRight = face[374]
w, _ = detector.findDistance(pointLeft, pointRight)
W = 6.3
# Finding distance
f = 840
d = (W * f) / w
print(d)
cvzone.putTextRect(img,
f'Depth: {int(d)}cm',
(face[10][0] - 100, face[10][1] - 50),
scale=2)
for i, text in enumerate(textList):
singleHeight = 20 + int((int(d / sen) * sen) / 4)
scale = 0.4 + (int(d / sen) * sen) / 100
while True:
success, img = cap.read()
img = cv2.flip(img, 1)
img, faces = detector.findFaceMesh(img, draw=False)
if faces:
face = faces[0]
eyeLeft = [27, 23, 130, 243] # up, down, left, right
eyeRight = [257, 253, 463, 359] # up, down, left, right
mouth = [11, 16, 57, 287] # up, down, left, right
faceId = [27, 23, 130, 243, 257, 253, 463, 359, 11, 16, 57, 287]
#calculate eye left distance ratio
eyeLeft_ver, _ = detector.findDistance(face[eyeLeft[0]],
face[eyeLeft[1]])
eyeLeft_hor, _ = detector.findDistance(face[eyeLeft[2]],
face[eyeLeft[3]])
eyeLeft_ratio = int((eyeLeft_ver / eyeLeft_hor) * 100)
# calculate eye right distance ratio
eyeRight_ver, _ = detector.findDistance(face[eyeRight[0]],
face[eyeRight[1]])
eyeRight_hor, _ = detector.findDistance(face[eyeRight[2]],
face[eyeRight[3]])
eyeRight_ratio = int((eyeRight_ver / eyeRight_hor) * 100)
# calculate mouth distance ratio
mouth_ver, _ = detector.findDistance(face[mouth[0]], face[mouth[1]])
mouth_hor, _ = detector.findDistance(face[mouth[2]], face[mouth[3]])
mouth_ratio = int((mouth_ver / mouth_hor) * 100)
#display text on image