def main():
vs = cv2.VideoCapture(0)
width = 640
vs.set(3, width)
height = 480
vs.set(4, height)
face_detector = cv2.CascadeClassifier(
'haarcascade_frontalface_default.xml')
while True:
ret, pic = vs.read()
pic_gray = cv2.split(pic)[2]
face_boxs = face_detector.detectMultiScale(
pic_gray,
scaleFactor=1.1,
minNeighbors=5,
minSize=(100, 100),
flags=cv2.CASCADE_SCALE_IMAGE)
if len(face_boxs):
for x, y, w, h in face_boxs:
e_right, e_left = find_eye_region(pic[y:y + h, x:x + w])
e_right_gray = cv2.split(e_right)[2]
e_left_gray = cv2.split(e_left)[2]
e_right_gray = cv2.GaussianBlur(e_right_gray, (15, 15), 1)
e_left_gray = cv2.GaussianBlur(e_left_gray, (15, 15), 1)
eye_radius = int(0.1 * (e_right.shape)[1])
eye_radius = eye_radius if eye_radius % 2 == 1 else eye_radius + 1
for i in range(e_left_gray.shape[0]):
for j in range(e_left_gray.shape[1]):
if e_left_gray[i][j] < gray_threshold:
e_left_gray[i][j] = 255 - e_left_gray[i][j]
else:
e_left_gray[i][j] = 0
for i in range(e_right_gray.shape[0]):
for j in range(e_right_gray.shape[1]):
if e_right_gray[i][j] < gray_threshold:
e_right_gray[i][j] = 255 - e_right_gray[i][j]
else:
e_right_gray[i][j] = 0
loc, mags = frst.frst(e_left_gray, eye_radius, 0.8)
cv2.circle(e_left, loc, 1, (0, 255, 0))
loc1, mags = frst.frst(e_right_gray, eye_radius, 0.8)
cv2.circle(e_right, loc1, 1, (0, 255, 0))
cv2.imshow('left eye', e_left)
cv2.imshow('left1 eye', e_left_gray)
cv2.imshow('right eye', e_right)
cv2.imshow('right1 eye', e_right_gray)
cv2.imshow('frame', pic)
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
vs.release()
cv2.destroyAllWindows()
break
def process(window, radii, alpha, beta, tbIter, tra):
frame = cv2.imread(iname)
w0, h0 = frame.shape[:2]
frame = cv2.resize(frame, (int(400 * h0 / w0), 400))
frame = cv2.GaussianBlur(frame, (15, 15), 0)
grayImg = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
grayImg = cv2.adaptiveThreshold(grayImg, 255,
cv2.ADAPTIVE_THRESH_GAUSSIAN_C,
cv2.THRESH_BINARY_INV, 11, 1)
kernel = np.ones((3, 3), np.uint8)
if tbIter > 0:
grayImg = cv2.morphologyEx(grayImg,
cv2.MORPH_CLOSE,
kernel,
iterations=int(tbIter))
grayImg = frst(grayImg, radii, alpha, beta, 0)
print(np.min(grayImg), np.max(grayImg))
hi = np.max(grayImg)
lo = np.min(grayImg)
grayImg = np.uint8(np.around((grayImg - lo) * 255 / (hi - lo)))
grayImg = cv2.cvtColor(grayImg, cv2.COLOR_GRAY2BGR)
# frame = frame[:grayImg.shape[0], :grayImg.shape[1], :]
grayImg = grayImg[:frame.shape[0], :frame.shape[1]]
print(frame.shape, grayImg.shape)
frame = cv2.addWeighted(frame, tra, grayImg, 1 - tra, 0)
window.show(frame)
def find_radial_symmetry(img):
# find regions of interest
firstImg = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
firstImg = frst(firstImg, 200, 1, 0.5, 0.1, 'BRIGHT')
# show_img(firstImg)
firstImg = cv2.normalize(firstImg, None, 0.0, 1.0, cv2.NORM_MINMAX)
# frstImage.convertTo(frstImage, CV_8U, 255.0);
firstImg = cv2.convertScaleAbs(firstImg, None, 255.0, 0)
show_img(firstImg)
ret, thresh = cv2.threshold(firstImg, 0, 255,
cv2.THRESH_BINARY | cv2.THRESH_OTSU)
# show_img(ret)
# cv::morphologyEx(inputImage, inputImage, operation, element, cv::Point(-1, -1), iterations);
# bwMorph(frstImage, markers, cv::MORPH_CLOSE, cv::MORPH_ELLIPSE, 5);
kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (3, 3))
markers = cv2.morphologyEx(firstImg, cv2.MORPH_CLOSE, kernel, iterations=5)
print(len(markers))
im2, contours, hierarchy = cv2.findContours(markers, cv2.RETR_TREE,
cv2.CHAIN_APPROX_SIMPLE)
# print(len(contours))
#
# img = cv2.drawContours(img, contours, -1, (0,0,255), 8)
# show_img(img)
moments = []
for cnt in contours:
moment = cv2.moments(cnt)
moments.append(moment)
print(moment)
#get the mass centers
mass_centers = []
for moment in moments:
x, y = moment.get('m10') / moment.get('m00'), moment.get(
'm01') / moment.get('m00')
mass_centers.append((int(x), int(y)))
for center in mass_centers:
print(center)
cv2.circle(img, center, 20, (0, 255, 0), 2)
show_img(img)
return None
def loop(socket_link):
magsum = 0
magavg = 0
locxsum = 0
locysum = 0
locxavg = 0
locyavg = 0
eye_state = False
eye_left = False
eye_right = False
sumcount = 30
# 眨眼次数
blink_count = 2
loctestx = []
loctesty = []
vs = VideoStream(src=camera_flag).start()
while True:
frame = vs.read()
frame = cv2.flip(frame, 0) # 水平镜像
# 获取眼部区域
eye_region = frame[left_eye_y:left_eye_y + eye_region_height,
left_eye_x:left_eye_x + eye_region_width]
eye_region = cv2.resize(eye_region, (resizex, resizey))
# 眼部转换成灰度图
gray = cv2.cvtColor(eye_region, cv2.COLOR_BGR2GRAY)
gray = cv2.GaussianBlur(gray, (15, 15), 1)
# 对眼图区域灰度图阈值取反
for i in range(resizex):
for j in range(resizey):
if gray[j][i] < gray_threshold:
gray[j][i] = 255 - gray[j][i]
else:
gray[j][i] = 0
loc, mags = frst.frst(gray, eye_radius, frst_threshold)
if sumcount > 0:
locxsum += loc[0]
locysum += loc[1]
magsum += mags
sumcount -= 1
if sumcount == 0:
magsum /= 30
locxsum /= 30
locysum /= 30
try:
socket_link.send(('4').encode('utf-8'))
recvdata = socket_link.recv(1)
except Exception:
print('client disconnected!')
break
print("Mag average:", magsum, "X average:", locxsum,
"Y average:", locysum)
else:
continue
# 0 center、 1 right 、2 left 、3 ensure
if mags < 0.3 * magsum and eye_state:
blink_count = blink_count - 1
if blink_count == 0:
blink_count = 2
try:
socket_link.send(('3').encode('utf-8'))
recvdata = socket_link.recv(1)
except Exception:
print('client disconnected!')
break
eye_state = False
continue
elif mags > 0.5 * magsum:
eye_state = True
cv2.circle(eye_region, loc, 2, (0, 255, 0))
loctestx.append(loc[0])
loctesty.append(loc[1])
if (not eye_left) and (not eye_right):
if loc[0] - locxsum > 5:
try:
socket_link.send(('1').encode('utf-8'))
recvdata = socket_link.recv(1)
except Exception:
print('client disconnected!')
break
blink_count = 2
eye_left = True
continue
elif loc[0] - locxsum < -5:
try:
socket_link.send(('2').encode('utf-8'))
recvdata = socket_link.recv(1)
except Exception:
print('client disconnected!')
break
blink_count = 2
eye_right = True
continue
elif (loc[0] - locxsum < 3) and (loc[0] - locxsum > -2):
try:
socket_link.send(('0').encode('utf-8'))
recvdata = socket_link.recv(1)
except Exception:
print('client disconnected!')
break
eye_left = False
eye_right = False
# cv2.imshow("tracking eye", eye_region)
ret, data = cv2.imencode('.jpg', eye_region)
data = data.tostring()
try:
socket_link.send(('5').encode('utf-8') + data)
# key = cv2.waitKey(1) & 0xFF
# if key == ord('q'):
# break
recvdata = socket_link.recv(1)
except Exception:
print('client disconnected!')
break
socket_link.close()
# cv2.destroyAllWindows()
vs.stop()
time.sleep(1)
return