Pfthb

Here is the code for the same, have a look at it. In this, below code I am creating a Motion Detector and with this I will be recording the timings of when the various objects appeared and disappeared for which I am using dataframe.

The issue with this is that the program executes but when the output is displayed in the form of a Window, it freezes when I try to terminate.

import cv2, pandas
from datetime import datetime

first_frame = None
status_list = [None,None]
times = 
df = pandas.DataFrame(columns=["Start", "End"]) #Dataframe to store the time values during which object detection and movement appears.


video = cv2.VideoCapture(0)#VideoCapture object is used to record video using web cam

while True:
 #check is a bool data type, returns true if VideoCapture object is read
 check,frame = video.read()
 status = 0
 gray = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY) # For converting the frame color to gray scale
 gray = cv2.GaussianBlur(gray,(21,21),0) # For converting the gray scale frame to GaussianBlur

 if first_frame is None:
 first_frame = gray # used to store the first image/frame of the video
 continue
 delta_frame = cv2.absdiff(first_frame,gray)#calculates the difference between first and other frames
 thresh_delta = cv2.threshold(delta_frame,30,255,cv2.THRESH_BINARY)[1]
 thresh_delta = cv2.dilate(thresh_delta,None,iterations=0) #Provides threshold value, so if the difference is <30 it will turn to black otherwise if >30 pixels will turn to white
 (_,cnts,_) = cv2.findContours(thresh_delta.copy(),cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) #Define the contour area,i.e. adding borders

 #Removing noises and shadows, any part which is greater than 1000 pixels will be converted to white
 for contour in cnts:
 if cv2.contourArea(contour) < 1000:
 continue
 status = 1 #change in status when the object is detected
 #Creating a rectangular box around the object in frame
 (x,y,w,h) = cv2.boundingRect(contour)
 cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),3)

 #list of status for every frame
 status_list.append(status)

 status_list=status_list[-2:]

 #Record datetime in a list when change occurs
 if status_list[-1]==1 and status_list[-2]==0:
 times.append(datetime.now())
 if status_list[-1]==0 and status_list[-2]==1:
 times.append(datetime.now())

 cv2.imshow('frame',frame)
 #cv2.imshow('Capturing',gray)
 #cv2.imshow('delta',delta_frame)
 #cv2.imshow('thresh',thresh_delta)

 key = cv2.waitKey(1) #changing the frame after 1 millisecond

 #Used for terminating the loop once 'q' is pressed
 if key == ord('q'):
 break

print(status_list)
print(times)

for i in range(0,len(times),2):
 df = df.append("Start":times[i],"End":times[i+1],ignore_index=True)

df.to_csv("Times.csv")

video.release()
cv2.destroyAllWindows #will be closing all the windows

Try this:

if cv2.waitKey(1) & 0xFF == ord('q'):
 break

For a brief explanation about what "& 0xFF" is, see: What's 0xFF for in cv2.waitKey(1)?

It is basically a bit mask that takes the portion of 'waitKey' value(32 bit) that can be compared to ASCII (8 bit).