def test_color_bars():

    sensor.reset()
    # Set sensor settings
    sensor.set_brightness(0)
    sensor.set_saturation(0)
    sensor.set_gainceiling(8)
    sensor.set_contrast(2)

    # Set sensor pixel format
    sensor.set_framesize(sensor.QVGA)
    sensor.set_pixformat(sensor.RGB565)

    # Enable colorbar test mode
    sensor.set_colorbar(True)

    # Skip a few frames to allow the sensor settle down
    # Note: This takes more time when exec from the IDE.
    for i in range(0, 100):
        image = sensor.snapshot()

    # Color bars thresholds
    t = [lambda r, g, b: r < 50  and g < 50  and b < 50,   # Black
         lambda r, g, b: r < 50  and g < 50  and b > 200,  # Blue
         lambda r, g, b: r > 200 and g < 50  and b < 50,   # Red
         lambda r, g, b: r > 200 and g < 50  and b > 200,  # Purple
         lambda r, g, b: r < 50  and g > 200 and b < 50,   # Green
         lambda r, g, b: r < 50  and g > 200 and b > 200,  # Aqua
         lambda r, g, b: r > 200 and g > 200 and b < 50,   # Yellow
         lambda r, g, b: r > 200 and g > 200 and b > 200]  # White

    # 320x240 image with 8 color bars each one is approx 40 pixels.
    # we start from the center of the frame buffer, and average the
    # values of 10 sample pixels from the center of each color bar.
    for i in range(0, 8):
        avg = (0, 0, 0)
        idx = 40*i+20 # center of colorbars
        for off in range(0, 10): # avg 10 pixels
            rgb = image.get_pixel(idx+off, 120)
            avg = tuple(map(sum, zip(avg, rgb)))

        if not t[i](avg[0]/10, avg[1]/10, avg[2]/10):
            raise Exception("COLOR BARS TEST FAILED. "
            "BAR#(%d): RGB(%d,%d,%d)"%(i+1, avg[0]/10, avg[1]/10, avg[2]/10))

    print("COLOR BARS TEST PASSED...")

import sensor, time

sensor.reset()
# Set sensor settings 
sensor.set_brightness(0)
sensor.set_saturation(0)
sensor.set_gainceiling(8)
sensor.set_contrast(2)

# Set sensor pixel format
sensor.set_framesize(sensor.QVGA)
sensor.set_pixformat(sensor.RGB565)

# Enable colorbar test mode
sensor.set_colorbar(True)

# Skip a few frames to allow the sensor settle down 
for i in range(0, 30):
    image = sensor.snapshot()

#color bars thresholds
t = [lambda r, g, b: r < 50  and g < 50  and b < 50,   # Black
     lambda r, g, b: r < 50  and g < 50  and b > 200,  # Blue
     lambda r, g, b: r > 200 and g < 50  and b < 50,   # Red
     lambda r, g, b: r > 200 and g < 50  and b > 200,  # Purple
     lambda r, g, b: r < 50  and g > 200 and b < 50,   # Green
     lambda r, g, b: r < 50  and g > 200 and b > 200,  # Aqua
     lambda r, g, b: r > 200 and g > 200 and b < 50,   # Yellow
     lambda r, g, b: r > 200 and g > 200 and b > 200]  # White

#320x240 image with 8 color bars each one is approx 40 pixels.

import sensor

sensor.set_contrast(1)
sensor.set_gainceiling(8)
sensor.set_framesize(sensor.QQVGA)
sensor.set_pixformat(sensor.RGB565)

image = sensor.snapshot()
image.save("/test.ppm")

# Iris Detection 2 Example
#
# This example shows how to find the eye gaze (pupil detection) after finding
# the eyes in an image. This script uses the find_eyes function which determines
# the center point of roi that should contain a pupil. It does this by basically
# finding the center of the darkest area in the eye roi which is the pupil center.
#
# Note: This script does not detect a face first, use it with the telephoto lens.

import sensor, time, image

# Reset sensor
sensor.reset()

# Sensor settings
sensor.set_contrast(3)
sensor.set_gainceiling(16)

# Set resolution to VGA.
sensor.set_framesize(sensor.VGA)

# Bin/Crop image to 200x100, which gives more details with less data to process
sensor.set_windowing((220, 190, 200, 100))

sensor.set_pixformat(sensor.GRAYSCALE)

# Load Haar Cascade
# By default this will use all stages, lower stages is faster but less accurate.
eyes_cascade = image.HaarCascade("eye", stages=24)
print(eyes_cascade)