Adaptive Histogram Equalization

# This work is licensed under the MIT license.
# Copyright (c) 2013-2023 OpenMV LLC. All rights reserved.
# https://github.com/openmv/openmv/blob/master/LICENSE
#
# Adaptive Histogram Equalization
#
# This example shows off how to use adaptive histogram equalization to improve
# the contrast in the image. Adaptive histogram equalization splits the image
# into regions and then equalizes the histogram in those regions to improve
# the image contrast versus a global histogram equalization. Additionally,
# you may specify a clip limit to prevent the contrast from going wild.

import csi
import time

csi0 = csi.CSI()
csi0.reset()
csi0.pixformat(csi.RGB565)
csi0.framesize(csi.QQVGA)
csi0.snapshot(time=2000)

clock = time.clock()

while True:
    clock.tick()

    # A clip_limit of < 0 gives you normal adaptive histogram equalization
    # which may result in huge amounts of contrast noise...

    # A clip_limit of 1 does nothing. For best results go slightly higher
    # than 1 like below. The higher you go the closer you get back to
    # standard adaptive histogram equalization with huge contrast swings.

    img = csi0.snapshot().histeq(adaptive=True, clip_limit=3)

    print(clock.fps())