bokeh detection

Face Detection/Motion Detection App/capture.1.py

-"""
-MOTION DETECTION APPLICATION
-"""
-
-import cv2, time, pandas
-from datetime import datetime
-
-first_frame = None
-
-status_list = [None, None]
-times = []
-df = pandas.DataFrame(columns=["Start", "End"])
-video = cv2.VideoCapture(0)
-
-while True:
- 
-    check, frame = video.read()
-    status = 0
-
-    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-    gray = cv2.GaussianBlur(gray, (21, 21), 0)
-    
-    if first_frame is None:
-        first_frame = gray
-        continue
-    
-    delta_frame = cv2.absdiff(first_frame, gray)
-    thresh_frame = cv2.threshold(delta_frame, 30, 255, cv2.THRESH_BINARY)[1]
-    thresh_frame = cv2.dilate(thresh_frame, None, iterations=2)
-    
-    (cnts,__) = cv2.findContours(thresh_frame.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
-    
-    for contour in cnts:
-        # checking the area of the objects in camera
-        if cv2.contourArea(contour) < 10000:
-            continue
-        status = 1
-        
-        (x, y, w, h) = cv2.boundingRect(contour)
-        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)
-    
-    status_list.append(status)
-    
-    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("Gray Frame", gray)
-    # cv2.imshow("Delta Frame",delta_frame)
-    # cv2.imshow("Threshold Frame",thresh_frame)
-    cv2.imshow("Color Frame", frame)
-    key = cv2.waitKey(1)
-    
-    if key == ord('q'):
-        if status == 1:
-            times.append(datetime.now())
-        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
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