util.py

import cv2
import random

import numpy as np
import set_solver as s


def show(img, window_name='main'):
	# destroy existing window
	destroy(window_name)
	# show it
	cv2.imshow(window_name, s.resize_image(img, 600))

	# wait for key, then destroy it
	cv2.waitKey(0)
	destroy(window_name)

	return window_name


def destroy(window_name):
	cv2.destroyWindow(window_name)


# (Stolen) utility code from
# http://git.io/vGi60A
def rectify(h):
	try:
		h = h.reshape((4, 2))
	except ValueError:
		return np.array([None])
	hnew = np.zeros((4, 2), dtype=np.float32)

	add = h.sum(1)
	hnew[0] = h[np.argmin(add)]
	hnew[2] = h[np.argmax(add)]

	diff = np.diff(h, axis=1)
	hnew[1] = h[np.argmin(diff)]
	hnew[3] = h[np.argmax(diff)]

	return hnew


# draw contour on empty image
def draw_contour(c, i, h=500, w=300):
	dest = np.zeros((h, w), np.float32)
	cv2.drawContours(dest, c, i, 255, cv2.FILLED)
	return dest


def resize(src, shape):
	dest = cv2.resize(src, (shape[1], shape[0]))
	return dest


# get grayscale and slightly blurred image to remove noise
def preprocess(img):
	# grayscale
	gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

	# gaussian blur to remove noise
	blur = cv2.GaussianBlur(gray, ksize=(5, 5), sigmaX=0)

	return blur


# inspired by
# http://martin.ankerl.com/2009/12/09/how-to-create-random-colors-programmatically/


def random_color_palette(n, bgr=True):
	"""Generates a random, aesthetically pleasing set of n colors
	(list of BGR tuples - because opencv is silly - if BGR; else HSV) """
	random.seed(4242)
	SATURATION = 0.6
	VALUE = 0.95
	GOLDEN_RATIO_INVERSE = 0.618033988749895

	# see: https://en.wikipedia.org/wiki/HSL_and_HSV#Converting_to_RGB
	def hsv2bgr(hsv):
		h, s, v = hsv
		# compute chroma
		c = v * s
		h_prime = h * 6.0
		x = c * (1 - abs(h_prime % 2 - 1))
		if h_prime >= 5:
			rgb = (c, 0, x)
		elif h_prime >= 4:
			rgb = (x, 0, c)
		elif h_prime >= 3:
			rgb = (0, x, c)
		elif h_prime >= 2:
			rgb = (0, c, x)
		elif h_prime >= 1:
			rgb = (x, c, 0)
		else:
			rgb = (c, x, 0)
		m = v - c
		rgb = tuple(255.0 * (val + m) for val in rgb)
		# flip tuple to return (B,G,R)
		return rgb[::-1]

	# random float in [0.0, 1.0)
	hue = random.random()
	l_hues = [hue]

	for i in xrange(n - 1):
		# generate evenly distributed hues by random walk using the golden ratio!
		# (mod 1, to stay within hue space)
		hue += GOLDEN_RATIO_INVERSE
		hue %= 1
		l_hues.append(hue)

	if not bgr:
		return [(h, SATURATION, VALUE) for h in l_hues]

	return [hsv2bgr((h, SATURATION, VALUE)) for h in l_hues]