问题描述
我有一个使用 cv2 的小型 python 脚本来捕获检测到的第一张人脸并仅在 cv2 窗口中显示该区域。一切正常。
目前,视频源在最小化时会冻结。 如果我将 cv2 窗口最小化到托盘,如何让我的脚本继续捕获视频?
编辑
我还想知道是否有更好的方法来减少 cpu 的负载。当前运行此脚本将使用 14 - 20% 的 cpu。
from __future__ import division
from imutils.video import VideoStream
import face_recognition
import imutils
import cv2
POINTS = []
def landmarkTrackSmoothing(Box,factor,maxPoints=30):
top = Box[0][0]
bottom = Box[0][1]
left = Box[0][2]
right = Box[0][3]
if len(POINTS) < maxPoints:
maxPoints = len(POINTS)
else:
del POINTS[0]
POINTS.append([top,bottom,left,right])
mean = [int((sum(col)/len(col))/factor) for col in zip(*POINTS)]
return mean
def cartoonFilter(roi):
# 1) Edges
gray = cv2.cvtColor(roi,cv2.COLOR_RGB2GRAY)
gray = cv2.medianBlur(gray,5)
edges = cv2.adaptiveThreshold(
gray,255,cv2.ADAPTIVE_THRESH_MEAN_C,cv2.THRESH_BINARY,9,9)
# 2) Color
color = cv2.bilateralFilter(roi,300,300)
# 3) Cartoon
return cv2.bitwise_and(color,color,mask=edges)
def OpenCamera():
vs = VideoStream(0 + cv2.CAP_DSHOW,framerate=120).start()
vs.stream.set(cv2.CAP_PROP_FRAME_WIDTH,1280)
vs.stream.set(cv2.CAP_PROP_FRAME_HEIGHT,1024)
roi = [0,0]
prev = [0,0]
# Add filter flags
cartoonEffect = False
# loop over frames from the video file stream
while True:
# grab the frame from the threaded video stream
frame = vs.read()
# downscale and convert to grayscale for fast processing
# of landmark locations
gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
gray = imutils.resize(frame,width=240)
# calculate upscale factor for landmark locations
factor = float(gray.shape[1]) / frame.shape[1]
# detect the (x,y)-coordinates of the bounding Boxes
# corresponding to each face in the input frame,then
# the facial embeddings for each face
Boxes = face_recognition.face_locations(gray)
Box = list(map(list,Boxes))
# t,b,l,r = 0,0
# upscale landmark locations
for i in range(len(Box)):
Box = [landmarkTrackSmoothing(Box,factor)]
# loop over the recognized faces
if (len(Box) > 0):
i = 0
for (top,right,left) in Box:
# grab frames from face coordinates
if (i == 0):
roi = frame[top:bottom,left:right]
prev = top,right
if cartoonEffect:
roi = cartoonFilter(roi)
i += 1
# check to see if we are supposed to display the output frame to
# the screen
if (len(Box) == 0):
if (prev[0] > 0):
roi = frame[prev[0]:prev[1],prev[2]:prev[3]]
else:
roi = frame
cv2.namedWindow("Frame",cv2.WINDOW_norMAL)
if (roi.any()):
cv2.imshow("Frame",roi)
cv2.resizeWindow("Frame",512,512)
# continue looping until quit: expandable to add dynamic key commands for filters
key = cv2.waitKey(1) & 0xFF
if key == ord("q"):
break
if key == ord('c'):
if cartoonEffect:
cartoonEffect = False
else:
cartoonEffect = True
# do a bit of cleanup on quit
cv2.destroyAllWindows()
vs.stop()
# Begin capturing
OpenCamera()
解决方法
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