import cv2

# open a video
cap = cv2.VideoCapture('example.mp4')

# get frame width, height, and fps
frame_width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
frame_height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
fps = int(cap.get(cv2.CAP_PROP_FPS))

fourcc = cv2.VideoWriter_fourcc('X', 'V', 'I', 'D')
output = cv2.VideoWriter("squid.mp4", fourcc, fps, (frame_width, frame_height))

# open 2 frame, so we can detect the diff
ret, frame1 = cap.read()
ret, frame2 = cap.read()

while cap.isOpened():
    diff = cv2.absdiff(frame1, frame2)
    frame_gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
    frame_blur = cv2.GaussianBlur(frame_gray, (5, 5), 0)
    _, thresh = cv2.threshold(frame_blur, 20, 255, cv2.THRESH_BINARY)
    dilated = cv2.dilate(thresh, None, iterations=3)
    contours, _ = cv2.findContours(dilated, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)

    for contour in contours:
        (x, y, w, h) = cv2.boundingRect(contour)

        if cv2.contourArea(contour) < 900:
            continue
        cv2.rectangle(frame1, (x, y), (x+w, y+h), (0, 255, 0), 2)

    image = cv2.resize(frame1, (frame_width, frame_height))
    output.write(image)
    cv2.imshow("feed", frame1)
    frame1 = frame2
    ret, frame2 = cap.read()

    if cv2.waitKey(40) == 27:
        break

cv2.destroyAllWindows()
cap.release()
out.release()