main.py

# importing OpenCV, time and Pandas library
import pandas
# importing datetime class from datetime library
from datetime import datetime
import cv2
import ssl
import smtplib
from email.mime.image import MIMEImage
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText

saveNum = 0
frames = []
whoTo = input("Enter email address of recipient: ")


def sendEmail(msg):
    context = ssl.create_default_context()

    s = smtplib.SMTP('smtp.outlook.com', 587)
    s.ehlo()
    s.starttls()
    s.ehlo()
    s.login('murrayg0216@outlook.com', 'Gmurr216')
    s.sendmail('murrayg0216@outlook.com', 'murrayg0216@outlook.com', msg.as_string())
    s.quit()


def prepEmail():

    msg = MIMEMultipart()
    msg["Subject"] = "An Email Alert"
    msg["From"] = "murrayg0216@outlook.com"
    msg["To"] = whoTo

    text = MIMEText("Test")
    msg.attach(text)

    i = 0

    for i in range(0, saveNum):
        fileName = 'motionStart' + str(i) + '.jpg'
        img_data = open(fileName, 'rb').read()
        image = MIMEImage(img_data, name=fileName)
        msg.attach(image)

        fileName = 'motionMid' + str(i) + '.jpg'
        img_data = open(fileName, 'rb').read()
        image = MIMEImage(img_data, name=fileName)
        msg.attach(image)

        fileName = 'motionEnd' + str(i) + '.jpg'
        img_data = open(fileName, 'rb').read()
        image = MIMEImage(img_data, name=fileName)
        msg.attach(image)

    sendEmail(msg)


def saveImage(start, mid, end):
    fileName = 'motionStart' + str(saveNum) + '.jpg'
    cv2.imwrite(fileName, img=start)

    fileName = 'motionMid' + str(saveNum) + '.jpg'
    cv2.imwrite(fileName, img=mid)

    fileName = 'motionEnd' + str(saveNum) + '.jpg'
    cv2.imwrite(fileName, img=end)


def getImage(frames):
    if (len(frames) % 2) is 0:
        saveImage(frames[0], frames[int(len(frames)/2)], frames[len(frames)-1])
    else:
        saveImage(frames[0], frames[int((len(frames)-1)/2)], frames[len(frames)-1])


# Assigning our static_back to None
static_back = None

# List when any moving object appear
motion_list = [None, None]

# Time of movement
time = []

# Initializing DataFrame, one column is start
# time and other column is end time
df = pandas.DataFrame(columns=["Start", "End"])

# Capturing video
video = cv2.VideoCapture(0)

# Infinite while loop to treat stack of image as video
while True:
    # Reading frame(image) from video
    check, frame = video.read()

    # Initializing motion = 0(no motion)
    motion = 0

    # Converting color image to gray_scale image
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)

    # Converting gray scale image to GaussianBlur
    # so that change can be find easily
    gray = cv2.GaussianBlur(gray, (21, 21), 0)

    # In first iteration we assign the value
    # of static_back to our first frame
    if static_back is None:
        static_back = gray
        continue

    # Difference between static background
    # and current frame(which is GaussianBlur)
    diff_frame = cv2.absdiff(static_back, gray)

    # If change in between static background and
    # current frame is greater than 30 it will show white color(255)
    thresh_frame = cv2.threshold(diff_frame, 30, 255, cv2.THRESH_BINARY)[1]
    thresh_frame = cv2.dilate(thresh_frame, None, iterations=2)

    # Finding contour of moving object
    (cnts, _) = cv2.findContours(thresh_frame.copy(),
                                    cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)

    for contour in cnts:
        if cv2.contourArea(contour) < 10000:
            continue
        motion = 1
        frames.append(frame)

        (x, y, w, h) = cv2.boundingRect(contour)
        # making green rectangle around the moving object
        cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 255), 3)

        # Appending status of motion
    motion_list.append(motion)

    motion_list = motion_list[-2:]

    # Appending Start time of motion
    if motion_list[-1] == 1 and motion_list[-2] == 0:
        time.append(datetime.now())

        # Appending End time of motion
    if motion_list[-1] == 0 and motion_list[-2] == 1:
        time.append(datetime.now())
        getImage(frames)
        saveNum = saveNum + 1

    # Displaying color frame with contour of motion of object
    cv2.imshow("Color Frame", frame)

    key = cv2.waitKey(1)
    # if q entered whole process will stop
    if key == ord('q'):
        # if something is moving then it append the end time of movement
        if motion == 1:
            time.append(datetime.now())
        break

    if saveNum >= 30:
        prepEmail()
        saveNum = 0

# Appending time of motion in DataFrame
for i in range(0, len(time), 2):
    df = df.append({"Start": time[i], "End": time[i + 1]}, ignore_index=True)

# Creating a csv file in which time of movements will be saved
df.to_csv("Time_of_movements.csv")

print("Done")

video.release()

# Destroying all the windows
cv2.destroyAllWindows()

prepEmail()