#!/usr/bin/env python
# -*- coding: utf-8 -*-
import cv2
import time
def conv():
#Threshold setting
threshold = 100
#Binarization(The number of pixels exceeding the threshold value of 100 is set to 255.)
ret, img_thresh = cv2.threshold(img, threshold, 255, cv2.THRESH_BINARY)
#Display of binarized image
cv2.imshow("img_th", img_thresh)
cv2.waitKey()
cv2.destroyAllWindows()
def fps(video):
fps = video.get(cv2.CAP_PROP_FPS)
print("FPS settings, video.get(cv2.CAP_PROP_FPS) : {0}".format(fps))
#Number of frames to get
num_frames = 120
print("Acquiring{0} frames".format(num_frames))
#Start time
start = time.time()
#Get the frame
#for i in range(0, num_frames):
# ret, frame = video.read()
#ending time
end = time.time()
# Time elapsed
seconds = end - start
print("elapsed time: {0} seconds".format(seconds))
# Calculate frames per second
fps = num_frames / seconds
print("Calculated FPS: {0}".format(fps))
class FPS:
def __init__(self):
self.flag = False
self.start = 0
self.end = 0
self.fps = 0
self.framecnt = 0
def calc_fps(self):
if self.flag == False:
self.start = time.time()
self.flag = True
else:
diff = time.time() - self.start
if diff > 1.0:
self.fps = self.framecnt / diff
self.framecnt = 0
self.start = time.time()
self.framecnt += 1
return self.fps
def test1(mode):
URL = "http://172.23.64.38:8081/?action=stream"
winname ="winname"
cv2.namedWindow(winname, cv2.WINDOW_NORMAL)
try :
if mode == 0:
s_video = cv2.VideoCapture(0)
else:
s_video = cv2.VideoCapture(URL)
#Threshold setting
threshold = 200
fpsobj = FPS()
while True:
start = time.time()
end = time.time()
seconds = end - start
ret, srcimg = s_video.read()
#cv2.imshow(winname,img)
key = cv2.waitKey(1) & 0xff
if key == ord('q'): break
#Binarization(The number of pixels exceeding the threshold value of 100 is set to 255.)
#cv2.threshold(image,Threshold,Thresholdを超えた場合に変更する値,Binarization method)
ret, img = cv2.threshold(srcimg, threshold, 255, cv2.THRESH_BINARY)
ksize=7 #Aperture size 3, 5,An odd number greater than 1 such as or 7. The larger the number, the more blurred.
img = cv2.medianBlur(img,ksize)
img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) #Specify BGR2 ~ instead of RGB2 ~
ret, img = cv2.threshold(img, 20, 255, cv2.THRESH_BINARY)
#print("{}".format( fpsobj.calc_fps()))
if ret:
#Display of binarized image
cv2.imshow(winname, img)
except:
pass
cv2.destroyAllWindows()
if __name__ == "__main__":
test1(1)
C++
#include <opencv2/core.hpp>
#include <opencv2/videoio.hpp>
#include <opencv2/highgui.hpp>
#include <iostream>
#include <stdio.h>
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/photo.hpp"
// http://labs.eecs.tottori-u.ac.jp/sd/Member/oyamada/OpenCV/html/py_tutorials/py_imgproc/py_thresholding/py_thresholding.html
Mat dst;
int criteria = 100;
int max = 255;
for ( ;;) {
cap.read( frame );
cv::threshold( frame, dst, criteria, max, THRESH_BINARY ); // binalized
int ksize = 7;// #Aperture size 3, 5,An odd number greater than 1 such as or 7. The larger the number, the more blurred.
cv::medianBlur( dst, dst, ksize );
cv::cvtColor( dst, dst, COLOR_BGR2GRAY );// #Specify BGR2 ~ instead of RGB2 ~
cv::threshold( dst, dst, 20, max, THRESH_BINARY );
imshow( "Live", dst );
if ( waitKey( 5 ) >= 0 ) {
break;
}
}
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