diff --git a/scripts/WebCam Motion Detector/Graph.html b/scripts/WebCam Motion Detector/Graph.html
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+ Bokeh Plot
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diff --git a/scripts/WebCam Motion Detector/MotionDetector.py b/scripts/WebCam Motion Detector/MotionDetector.py
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+++ b/scripts/WebCam Motion Detector/MotionDetector.py
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+import cv2,time,pandas
+from datetime import datetime
+
+first_frame = None
+status_list = [None, None]
+time = []
+df = pandas.DataFrame(columns=["Start", "End"])
+
+video = cv2.VideoCapture(0)
+
+while True:
+ check, frame = video.read()
+ status = 0
+ grey = cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
+ grey = cv2.GaussianBlur(grey, (21, 21), 0) #blurring for accuracy
+
+ if first_frame is None: #capturing the background or the initial frame
+ first_frame = grey
+ continue
+
+ delta_frame = cv2.absdiff(first_frame, grey) #to
+
+ thresh_frame = cv2.threshold(delta_frame, 30, 255, cv2.THRESH_BINARY)[1]
+ #returns a tuple and converts the moving pixels to white
+
+ thresh_frame = cv2.dilate(thresh_frame, None, iterations=2)
+
+ (cnts,_) = cv2.findContours(thresh_frame.copy(), cv2.RETR_EXTERNAL,
+ cv2.CHAIN_APPROX_SIMPLE)
+
+ for cont in cnts:
+ if cv2.contourArea(cont) < 10000: #excluding negligble objects
+ continue
+ status = 1
+ (x, y, w, h) = cv2.boundingRect(cont)
+ cv2.rectangle(frame, (x, y), (x+w, y+h), (0,255,0), 3,)
+ status_list.append(status)
+
+ status_list = status_list[-2:]
+
+ if status_list[-1] == 1 and status_list[-2] == 0:
+ time.append(datetime.now())
+ if status_list[-1] == 0 and status_list[-2] == 1:
+ time.append(datetime.now())
+ cv2.imshow("captured", grey)
+ cv2.imshow("delta", delta_frame)
+ cv2.imshow("Threshold", thresh_frame)
+ cv2.imshow("color frame", frame)
+
+ key = cv2.waitKey(1)
+
+ if key == ord('q'):
+ if status == 1:
+ time.append(datetime.now())
+ break
+ print(status)
+
+print(status_list)
+print(time)
+
+for i in range(0, len(time), 2):
+ df = df.append({"Start" : time[i], "End": time[i+1]}, ignore_index=True)
+
+df.to_csv("Times.csv")
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+video.release()
+cv2.destroyAllWindows()
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