def windowExplore(image, winSize = 40):
"""
def windowExplore(image, win)->None
Divides an image into grids of size win*win
"""
WAIT_TIME = 50
WIN = winSize
image = Image.border(image, WIN)
image = cv2.GaussianBlur(image, (5,5), 5)
oilPaint = np.zeros_like(image, np.uint8)
avgPaint = oilPaint.copy()
# cv2.imshow("OIL PAINT", oilPaint)
row, col = image.shape[:2]
startH = 0
for i in xrange(0, row/WIN):
startW = 0
for j in xrange(0, col/WIN):
roiQ = image[startH: startH + WIN, startW : startW + WIN]
startK = 0
# startK = startW
colors = []
colorsRed = []
colorsBlue = []
colorsGreen = []
# for k in xrange(0, col/WIN):
roi = image[startH : startH + WIN, startW : startW + WIN]
# colors = [roi[i][j] for i in WIN for j in WIN]
for i in xrange(0,WIN):
for j in xrange(0,WIN):
colors.append(roi[i][j])
center = group(colors)
avg = np.average(roi)
# print center, avg
oilWindow = np.ones(roi.shape, np.uint8)*center
avgWindow = np.ones(roi.shape, np.uint8)*avg
oilPaint[startH : startH + WIN, startW : startW + WIN] = oilWindow
avgPaint[startH : startH + WIN, startW : startW + WIN] = avgWindow
# cv2.imshow("OIL", oilPaint)
# cv2.imshow("AVERAGE", avgPaint)
# cv2.imshow("INPUT", image)
# cv2.waitKey(WAIT_TIME)
startW = startW + WIN
startH = startH + WIN
# cv2.imshow("OIL", oilPaint)
# cv2.imshow("AVERAGE", avgPaint)
# cv2.imshow("INPUT", image)
# cv2.imshow("BLURRED", cv2.GaussianBlur(oilPaint, (5,5), 5))
# cv2.waitKey(WAIT_TIME*0)
blurred = cv2.GaussianBlur(oilPaint, (5,5), 5)
print oilPaint.shape
return oilPaint, blurred
