Project6

Author: SaharshPandey

Project5-Tkinter-GUI/forehand.py

@@ -9,7 +9,7 @@
 from tkinter import *
 import backend
 root=Tk()
-root.wm_title("BookStor")
+root.wm_title("BookStore")
 
 def get_row_selected(event):
     try:
@@ -118,4 +118,4 @@ def deleteCommand():
 
 b6=Button(root,text="Close",width=12,command=root.destroy)
 b6.grid(row=7,column=3)
-root.mainloop()
+root.mainloop()

Project6-FaceDetection/Times.csv

@@ -0,0 +1,3 @@
+,Start,End,END
+0,2018-07-11 16:15:50.329286,,2018-07-11 16:15:50.343558
+1,2018-07-11 16:15:50.371213,,2018-07-11 16:15:55.901013

Project6-FaceDetection/motion_detector.py

@@ -0,0 +1,71 @@
+import cv2 as cv
+from datetime import datetime
+import pandas
+first_frame=None    #stores the first frame...
+status_list=[None,None]    #stroing the status if objects
+times=[]    #storing the datetime for objects
+df=pandas.DataFrame(columns=["Start","End"])
+video=cv.VideoCapture(0)
+while True:
+    #two attributes check->:boolean that tells video is recording..while frame :-> ndarray
+        check,frame=video.read()
+    #this status=0 means there is no motion right now..
+        status=0
+        #print(check)
+        #print(frame)
+    #converting RGB video into GrayScale
+        gray=cv.cvtColor(frame,cv.COLOR_BGR2GRAY)
+    #blurring the video so that motion is easily measured.
+        gray=cv.GaussianBlur(gray,(21,21),0)
+    #checking and storing the backgound,so the background finds out the difference with other frames of video.
+        if first_frame is None:
+            first_frame=gray
+            continue    #now if we continue then there will be no first frame,because it is pre generated.
+
+        delta_frame=cv.absdiff(first_frame,gray) #this finding the diff between the first frame(background) and other frames of video.
+        thresh_frame=cv.threshold(delta_frame,30,255,cv.THRESH_BINARY)[1] #create threshold frame
+        thresh_frame=cv.dilate(thresh_frame,None,iterations=2) #dilate means making tthe edges smoother
+
+    #finding the contours which helps to find out objects in a frame.
+        (_,cnts,_)=cv.findContours(thresh_frame.copy(),cv.RETR_EXTERNAL,cv.CHAIN_APPROX_SIMPLE)
+        for contour in cnts:
+            #if area of object is less then 1000 then we will continue otherwise there is an object.
+            if cv.contourArea(contour)<1000:
+                continue
+            status=1 #this implies there is an object in a frame
+            (x,y,w,h)=cv.boundingRect(contour) # finding the corners of object in a frame.
+            cv.rectangle(frame,(x,y),(x+w,y+h),(0,255,0),3) # making out rectangle for every objects
+    #appending all the incoming and outgoing of the object in an frame
+        status_list.append(status)
+
+    #checking the datetime of apearing object
+        if status_list[-1]==1 and status_list[-2]==0:
+            times.append(datetime.now())
+    #checking the datetime of disapearing object
+        if status_list[-1]==0 and status_list[-2]==1:
+            times.append(datetime.now())
+
+    #showing the frames/windows
+        cv.imshow("Gray Frame",gray)
+        cv.imshow("Delta Frame",delta_frame)
+        cv.imshow("THRESH_BINARY",thresh_frame)
+        cv.imshow("RectFrame",frame)
+    #1 is refreshing the frame in every 1 milisec:
+        key=cv.waitKey(1)
+    #displaying window until you press q
+        if key ==ord('q'):
+            #if thier is appearing object but that time is window is quited,then it will add the datetime for disappearing object as time of window exited.
+            if status==1:
+                times.append(datetime.now())
+            break
+print(status_list)
+print(times)
+#putting all the datetime of objects in csv file with the help of pandas.
+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") #saving file as "Times.csv"
+
+#releasing window..
+video.release()
+#destroying all windows..
+cv.destroyAllWindows()