Hardware accelerated image processing

    Using hardware to replace certain software parts can make the calculation faster. The methods of acceleration optimization have been done as follows:

    The following code respectively performs edge search, sharpening, and embossing on the image, and uses the convolution calculation to quickly obtain the result.

    import sensor
    import image
    import lcd
    import time
    
    lcd.init(freq=15000000)
    sensor.reset()
    sensor.set_pixformat(sensor.RGB565)
    sensor.set_framesize(sensor.QVGA)
    sensor.run(1)
    origin = (0,0,0, 0,1,0, 0,0,0)
    edge = (-1,-1,-1,-1,8,-1,-1,-1,-1)
    sharp = (-1,-1,-1,-1,9,-1,-1,-1,-1)
    relievo = (2,0,0,0,-1,0,0,0,-1)
    
    tim = time.time()
    while True:
        img=sensor.snapshot()
        img.conv3(edge)
        lcd.display(img)
        if time.time() -tim >10:
            break
    tim = time.time()
    while True:
        img=sensor.snapshot()
        img.conv3(sharp)
        lcd.display(img)
        if time.time() -tim >10:
            break
    tim = time.time()
    while True:
        img=sensor.snapshot()
        img.conv3(relievo)
        lcd.display(img)
        if time.time() -tim >10:
            break
    
    lcd.clear()