def main():
    global frames_per_second

    K.set_learning_phase(0)

    model = load_model("./tfmodel/model.json", "./tfmodel/model_weights/model.36-0.9417.hdf5")

    frame_count = 0
    start_time = time.time()

    cap = cv2.VideoCapture('drivingNYCdowntown.mp4')
    ret, frame = cap.read()

    # Define the codec and create VideoWriter object
    fourcc = cv2.VideoWriter_fourcc(*'DIVX')
    print('shape:', frame.shape[:2])
    out = cv2.VideoWriter('output.avi',cv2.VideoWriter_fourcc(*'DIVX'), 5.0, (1280, 720), True)

    counter=0

    while(True):
            # Capture frame-by-frame
            ret, frame = cap.read()

            pred = run_inference(frame, model)

            display_image = overlay_on_image(frame, pred)

            #cv2.imshow('frame',display_image)
            if counter%3==0:
                out.write(display_image)
                print(counter)
            counter = counter + 1

            if counter>9000:
                break

            if cv2.waitKey(1) & 0xFF == ord('q'):
                break

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