mosaicsplitter.py

from __future__ import division
import os
import sys
import numpy as np
import cv2

np.set_printoptions(precision=4, suppress=True)

def getseam(image, x0=0, y0=0, blur=False):
	height, width, nch = image.shape

	# de-gamma, normalize
	image = (np.float32(image) * (1/255)) ** (2.2)

	# vertical seams
	xdiff = cv2.filter2D(cv2.blur(image, ksize=(1,blur or 1)), ddepth=cv2.CV_32F, kernel=np.array([[-1, +1]]), borderType=cv2.BORDER_REPLICATE)
	xdiff = np.abs(xdiff).sum(axis=2)

	# horizontal seams
	ydiff = cv2.filter2D(cv2.blur(image, ksize=(blur or 1,1)), ddepth=cv2.CV_32F, kernel=np.array([[-1], [+1]]), borderType=cv2.BORDER_REPLICATE)
	ydiff = np.abs(ydiff).sum(axis=2)

	xseams = xdiff.sum(axis=0) / (nch*height) # vertical seams
	yseams = ydiff.sum(axis=1) / (nch*width) # horizontal seams

	xbest = np.argmax(xseams)
	xscore = xseams[xbest]
	ybest = np.argmax(yseams)
	yscore = yseams[ybest]

	bestaxis = 0 if (xscore >= yscore) else 1
	bestscore = [xscore, yscore][bestaxis]
	bestcoord = [xbest, ybest][bestaxis]

	return bestscore, "xy"[bestaxis], bestcoord+[x0,y0][bestaxis]

def splitroi(rect, axis, coord):
	(x0,y0,x1,y1) = rect

	if axis == 'x': # vertical split
		return (
			(x0, y0, coord, y1),
			(coord, y0, x1, y1)
		)

	elif axis == 'y': # horizontal split
		return (
			(x0, y0, x1, coord),
			(x0, coord, x1, y1)
		)

	else:
		assert False



infile = sys.argv[1]

image = cv2.imread(infile) # de-gamma? normalize to 1.0?
h,w = image.shape[:2]

rois = [ (0, 0, w, h) ]
minsize = 200

i = 0
while i < len(rois):
	x0,y0,x1,y1 = roi = rois[i]
	print roi, ":"

	#import pdb; pdb.set_trace()
	score, axis, coord = getseam(image[y0:y1, x0:x1], x0=x0, y0=y0, blur=5)

	print "seam at {1} = {2}, score {0:.3f}".format(score, axis, coord)
	print

	subrois = splitroi(roi, axis, coord)

	#if (score >= 0.15) and all(min(x1-x0, y1-y0) >= minsize for x0,y0,x1,y1 in subrois):
	if (score >= 0.15) and (min(x1-x0, y1-y0) >= minsize):
		rois[i:i+1] = subrois

	else:
		#print roi
		rois[i] = rois[i] + (score,)
		i += 1

print np.array(rois)

result = image/255 * 0.5
for roi in rois:
	x0,y0,x1,y1,score = roi
	cv2.line(result, (x0,y0), (x1,y1), color=(0,0,1), thickness=3, lineType=cv2.LINE_AA)
	cv2.line(result, (x0,y1), (x1,y0), color=(0,0,1), thickness=3, lineType=cv2.LINE_AA)
	cv2.putText(result, text="{:.3f}".format(score), org=(x0, y1), fontFace=cv2.FONT_HERSHEY_PLAIN, fontScale=2, color=(1,1,1), thickness=2, lineType=cv2.LINE_AA)

cv2.imwrite("{0}-split{1}".format(*os.path.splitext(infile)), (result*255).clip(0, 255))
cv2.namedWindow("result", cv2.WINDOW_NORMAL)
cv2.imshow("result", result)
cv2.waitKey(0)
cv2.destroyWindow("result")