在 opencv 中创建一个蒙版并删除内部轮廓 python

Question

这是我的代码的结果： enter image description here

我使用轮廓在脸上制作了这个面具，如下面的代码所示。
该项目的最终结果是删除面部并显示背景我还没有定义它 .
我的问题是： 有没有什么方法可以用这个计数器制作一个蒙版，这样我就可以使用类似这样的东西 cv2.imshow('My Image',cmb(foreground,background,mask)) 只在背景的蒙版下显示前景？（这里的问题是我必须以这种形式将面具作为视频，但我希望它是实时的）
或者可能是另一种方式，我能以某种方式删除我柜台中（或下方）的帧像素吗？
这是我的代码：

from imutils.video import VideoStream
from imutils import face_utils
import datetime
import argparse
import imutils
import time
import dlib
import cv2
import numpy as np

# path to facial landmark predictor
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=True)

print("[INFO] loading facial landmark predictor...")
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(args["shape_predictor"])

# grab the indexes of the facial landmarks
(lebStart, lebEnd) = face_utils.FACIAL_LANDMARKS_IDXS["left_eyebrow"]
(rebStart, rebEnd) = face_utils.FACIAL_LANDMARKS_IDXS["right_eyebrow"]
(jawStart, jawEnd) = face_utils.FACIAL_LANDMARKS_IDXS["jaw"]

# initialize the video stream and allow the cammera sensor to warmup
print("[INFO] camera sensor warming up...")
vs = VideoStream(usePiCamera=args["picamera"] > 0).start()
time.sleep(2.0)

# loop over the frames from the video stream
while True:
    # grab the frame from the threaded video stream, resize it to
    # have a maximum width of 400 pixels, and convert it to
    # grayscale
    frame = vs.read()
    frame = imutils.resize(frame, width=400)
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # detect faces in the grayscale frame
    rects = detector(gray, 0)

    # loop over the face detections
    for rect in rects:
        shape = predictor(gray, rect)
        shape = face_utils.shape_to_np(shape)

        # extract the face coordinates, then use the
        faceline = shape[jawStart:lebEnd]

        # compute the convex hull for face, then
        # visualize each of the face
        facelineHull = cv2.convexHull(faceline)

        mask = np.zeros(frame.shape,dtype='uint8')
        cv2.drawContours(frame, [facelineHull], -1, (0, 0, 0),thickness=cv2.FILLED)
        cv2.drawContours(frame, [facelineHull], -1, (0, 255, 0))

    # show the frame
    cv2.imshow("Frame", frame)
    # cv2.imshow("Frame", mask)
    key = cv2.waitKey(1) & 0xFF

    # if the `q` key was pressed, break from the loop
    if key == ord("q"):
        break


# do a bit of cleanup
cv2.destroyAllWindows()
vs.stop()

Answer 1

假设您的掩码是二进制掩码，您可以执行以下操作：

def cmb(foreground,background,mask):
    result = background.copy()
    result[mask] = foreground[mask]
    return result

我没有测试这段代码，但我希望你能理解这个想法。您反转背景的蒙版，而单独保留前景的蒙版。你将它应用到每一帧，瞧，你有你的蒙版图像。

编辑：根据评论调整代码。当然，这个解决方案比我最初写的要清晰得多。不过，功能保持不变。

Answer 2

这是我从框架中删除人脸的解决方案（速度更快，但再次感谢@meetaig 的帮助）

mask = np.zeros(frame.shape,dtype='uint8')
mask = cv2.drawContours(mask, [facelineHull], -1, (255 , 255 , 255),thickness=cv2.FILLED)
mask = cv2.bitwise_not(mask)
img2gray = cv2.cvtColor(mask,cv2.COLOR_BGR2GRAY)
ret, mask = cv2.threshold(img2gray, 10, 255, cv2.THRESH_BINARY)
result= cv2.bitwise_and(frame,frame,mask=mask)

如果我现在显示结果，它将起作用。

cv2.imshow("Frame", result)

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