My try at QR code detection (unfinished & broken)

qrdetect.py

import math
import numpy
import cv2

def isPattern(one, two, three, four, five):
	if not one:
		return

	size = float(one + two + three + four + five) / 7

	one /= size
	if one < 0.5 or 1.75 < one:
		return

	two /= size
	if two < 0.5 or 1.75 < two:
		return

	three /= size * 3
	if three < 0.5 or 1.75 < three:
		return

	four /= size
	if four < 0.5 or 1.75 < four:
		return

	five /= size
	if five < 0.5 or 1.75 < five:
		return

	return size

def findPatternsInRow(y, row):
	width = row.shape[0]
	candidates = []
	one = two = three = four = five = 0
	state = False
	for i in range(width):
		if row[i]:
			if state:
				five += 1
			else:
				five = 1
				state = True
		else:
			if not state:
				four += 1
			else:
				size = isPattern(one, two, three, four, five)
				if size:
					candidates.append((i, y, size))
				one = three
				two = four
				three = five
				four = 1
				state = False
	return candidates

def findPatterns(img):
	height, width = img.shape
	candidates = []
	for i in range(0, height, 2):
		candidates.extend(findPatternsInRow(i, img[i]))
	candidates = [(int(round(x-3.5*r)),y,r) for x,y,r in candidates]
	groups = []
	for x,y,r in candidates:
		for matches in groups:
			x2, y2, r2 = matches[-1]
			if math.sqrt((x-x2)**2 + (y-y2)**2) <= r*r2:
				matches.append((x,y,r))
				break
		else:
			groups.append([(x,y,r)])
	patterns = []
	for matches in groups:
		count = float(len(matches))
		if count <= 1:
			continue
		patterns.append((
			sum([x for x,y,r in matches]) / count,
			sum([y for x,y,r in matches]) / count,
			sum([r for x,y,r in matches]) / count))
	return patterns

def handlePattern(edges, img, x, y, r, rgbimg):
	x1 = int(round(x - 4.5 * r))
	x2 = int(round(x + 4.5 * r))
	y1 = int(round(y - 4.5 * r))
	y2 = int(round(y + 4.5 * r))
	cv2.rectangle(rgbimg, (x1,y1), (x2,y2), (255,0,0), 1)
	subimg = edges[y1:y2, x1:x2]
	try:
		lines = cv2.HoughLinesP(subimg, 0.5, math.pi/12, 10)
	except cv2.error:
		return
	if lines == None:
		cv2.line(rgbimg, (x1,y1), (x2,y2), (0,255,0), 1)
		return
	for lx1,ly1,lx2,ly2 in lines[0]:
		cv2.line(rgbimg, (x1+lx1, y1+ly1),
				(x1+lx2, y1+ly2), (0, 0, 255), 1)

v = cv2.VideoCapture(0)
while True:
	res, rgbimg = v.read()
	if not res:
		break

	img = cv2.cvtColor(rgbimg, cv2.COLOR_RGB2GRAY)
#	img = cv2.medianBlur(img, 3)
#	blur = cv2.GaussianBlur(img, (3, 3), 1.5)
#	img = (img - blur) + 127
	img = cv2.adaptiveThreshold(img, 255, cv2.ADAPTIVE_THRESH_MEAN_C,
			cv2.THRESH_BINARY_INV, 15, 5)
	patterns = findPatterns(img)
	edges = cv2.filter2D(img, 0, numpy.array((
			(-1,-1,-1),(-1,8,-1),(-1,-1,-1)
		), dtype=numpy.float))
	for x,y,r in patterns:
		handlePattern(edges, img,x,y,r, rgbimg)
#		cv2.circle(rgbimg, (int(round(x)),int(round(y))),
#				int(round(r*3.5)), (0,0,255), 1)
	cv2.imshow("debug", rgbimg)
#	img = cv2.filter2D(img, 0, numpy.array((
#			(-1,-1,-1),(-1,8,-1),(-1,-1,-1)
#		), dtype=numpy.float))
#	cv2.imshow("debug", img)
	if cv2.waitKey(1) >= 0:
		break