06_picam_video.py

# -*- coding: utf-8 -*-
# This program illustrates how to capture frames in a video stream and how to do further processing on them
# It uses numpy to do the calculations and OpenCV to display the frames

import picamera
import picamera.array                           # This needs to be imported explicitly
import time
import cv2
import numpy as np                              



# Initialize the camera
camera = picamera.PiCamera()
camera.resolution = (640, 480)
camera.framerate = 32
camera.vflip = False                            # Flip upside down or not
camera.hflip = True                             # Flip left-right or not


# Create a data structure to store a frame
rawframe = picamera.array.PiRGBArray(camera, size=(640, 480))


# Allow the camera to warm up
time.sleep(0.1)


if __name__ == '__main__':
    try:
        
        # Continuously capture frames from the camera
        # Each rawframe is accessible as ´frame´ inside the for-loop
        # Note that the format is BGR instead of RGB because we want to use openCV later on and it only supports BGR
        for frame in camera.capture_continuous(rawframe, format = 'bgr', use_video_port = True):

            # Clear the rawframe in preparation for the next frame
            # Do not modify this line of code
            rawframe.truncate(0)


            # Create a numpy array representing the image
            # Do not modify this line of code
            image = frame.array


            #-----------------------------------------------------
            # We will use numpy to do our image manipulations
            #-----------------------------------------------------

            # Make a copy of the image
            image2 = image.copy()
            image2.setflags(write=1)                                   # Making the array mutable                                                                                                      

            # Modify the copy of the image
            # This is where you would write your code to manipulate the image (invert it, make it grayscale, etc.)
            # Remember: images are stored as BGR
            w,h,d = image2.shape
            image2[w//4:3*w//4 , h//4:3*h//4 , :] = 255 - image2[w//4:3*w//4 , h//4:3*h//4 , :]


            # Show the frames
            cv2.imshow("Orignal frame", image)
            cv2.imshow("Modified frame", image2)
            
            # The waitKey command is needed to force openCV to show the image
            cv2.waitKey(1)




    # Reset by pressing CTRL + C
    except KeyboardInterrupt:
        print("Program stopped by User")
        cv2.destroyAllWindows()
        # Clean up the camera resources
        camera.close()