有没有一种方法可以通过使用opencv/dlib和直播视频来获取前额(边界框)的区域 [英] Is there a way to get the area of the forehead (bounding box) by using opencv/dlib and for a live stream video
问题描述
我一直在进行一个项目,以从实时流式视频中获取前额区域,而不仅仅是像本例中那样使用和成像并裁剪前额,例如本例中的
当我很远的时候:
代码:
import cv2导入dlib上限= cv2.VideoCapture(0)检测器= dlib.get_frontal_face_detector()预测变量= dlib.shape_predictor("shape_predictor_81_face_landmarks.dat")而True:_,框架= cap.read()灰色= cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)人脸=检测器(灰色)#检测存在的人脸数量面对面:x1 = face.left()y1 = face.top()x2 = face.right()y2 = face.bottom()地标=预测变量(灰色,面部)x_pts = []y_pts = []对于范围n中的n(68,81):x =地标.part(n).xy =地标.part(n).yx_pts.append(x)y_pts.append(y)cv2.circle(frame,(x,y),4,(0,255,0),-1)x1 =最小值(x_pts)x2 =最大值(x_pts)y1 =最小值(y_pts)y2 =最大值(y_pts)cv2.rectangle(frame,(x1,y1),(x2,y2),(0,0,255),3)cv2.imshow("out",框架)键= cv2.waitKey(1)&0xFF#如果按了q键,则从循环中中断如果键== ord("q"):休息
I've been working on a project to get the forehead area from a live streaming video and not just use and image and crop the forehead like from this example How can i detect the forehead region using opencv and dlib?.
cap = cv2.VideoCapture(0)
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(predict_path)
while True:
_, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = detector(gray) #detects number of faces present
for face in faces:
x1 = face.left()
y1 = face.top()
x2 = face.right()
y2 = face.bottom()
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 3)
landmarks = predictor(gray, face)
for n in range(68, 81):
x = landmarks.part(n).x
y = landmarks.part(n).y
cv2.circle(frame, (x, y), 4, (0, 255, 0), -1)
I managed to get the forehead region using the landmarks of using https://github.com/codeniko/shape_predictor_81_face_landmarks/blob/master/shape_predictor_81_face_landmarks.dat
But what I need is the rectangle bounding box onto where the landmark is at detecting the forehead region. Is this possible to get? If not, what should I do to get the forehead region. Thanks in advance.
you already find the desired coordinates by:
for face in faces:
x1 = face.left()
y1 = face.top()
x2 = face.right()
y2 = face.bottom()
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 3)
But what I need is the rectangle bounding box onto where the landmark is at detecting the forehead region.
Then change the y-coordinates:
cv2.rectangle(frame, (x1, y1-100), (x2, y2-100), (0, 0, 255), 3)
Update
To stick to the forehead points, we need to get minimum and maximum landmark
coordinates, then we need to draw rectangle.
Step1: Getting coordinates:
-
- Initialize
x_pts
andy_pts
- Initialize
-
- Store
landmark(n)
points into the arrays.
- Store
for n in range(68, 81):
x = landmarks.part(n).x
y = landmarks.part(n).y
x_pts.append(x)
y_pts.append(y)
cv2.circle(frame, (x, y), 4, (0, 255, 0), -1)
Step 2: Drawing the rectangle around detected points
-
- Get Minimum and Maximum points
x1 = min(x_pts)
x2 = max(x_pts)
y1 = min(y_pts)
y2 = max(y_pts)
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 3)
Result:
When I zoom to the webcam:
When I'm far away:
Code:
import cv2
import dlib
cap = cv2.VideoCapture(0)
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor("shape_predictor_81_face_landmarks.dat")
while True:
_, frame = cap.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = detector(gray) # detects number of faces present
for face in faces:
x1 = face.left()
y1 = face.top()
x2 = face.right()
y2 = face.bottom()
landmarks = predictor(gray, face)
x_pts = []
y_pts = []
for n in range(68, 81):
x = landmarks.part(n).x
y = landmarks.part(n).y
x_pts.append(x)
y_pts.append(y)
cv2.circle(frame, (x, y), 4, (0, 255, 0), -1)
x1 = min(x_pts)
x2 = max(x_pts)
y1 = min(y_pts)
y2 = max(y_pts)
cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 0, 255), 3)
cv2.imshow("out", frame)
key = cv2.waitKey(1) & 0xFF
# if the `q` key was pressed, break from the loop
if key == ord("q"):
break
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