import random

	print("k-means centers:",centers)

def detectStones(img):

	(bh,bw)=img.shape

	sw=bw//19

	sh=bh//19

	print(img.shape,(sw,sh))

	ell=ellipse(sw,sh)*255

	# print(ell)

	hitMap=np.zeros_like(img,dtype=np.uint8)

	for i in range(sw,bw):

		for j in range(sh,bh):

			region=stones[j-sh:j, i-sw:i]

			hitMap[j,i]=255*score(region,ell)

	show(hitMap)

	return hitMap

def detectGrid(img):

	(bh,bw)=img.shape

	gridMap=np.zeros_like(img,dtype=np.uint8)

	for i in range(5,bw):

		for j in range(5,bh):

			region=img[j-5:j, i-5:i]

			gridMap[j,i]=255*maxOp55(region)

	show(gridMap)

def locateStone(img):

	(bh,bw)=img.shape

	sw=bw//19

	sh=bh//19

	print(img.shape,(sw,sh))

	ell=ellipse(sw,sh)*255

	# print(ell)

	y=random.randrange(sh,bh)

	x=random.randrange(sw,bw)

	region=stones[y-sh:y, x-sw:x]

	sc=score(region,ell)

	print(sc)

	show(region)

	return sc

def locateLocalMaximum(img):

	(bh,bw)=img.shape

	x=random.randrange(0,bw)

	y=random.randrange(0,bh)

	val=img[y,x]

	img_=cv.cvtColor(img,cv.COLOR_GRAY2BGR)

	while True:

		for (dx,dy) in [(0,1),(1,0),(0,-1),(-1,0),(1,1),(-1,1),(1,-1),(-1,-1)]:

			x_=x+dx

			y_=y+dy

			val_=img[y_,x_] if 0<=x_<bw and 0<=y_<bh else 0

			if val_>val:

				x=x_

				y=y_

				val=val_

				img_.itemset((y,x,0),255)

				continue

		break

	print(x,y,val)

	img_.itemset((y,x,2),255)

	show(img_)

	return (x,y,val)

if __name__=="__main__":

	filepath=sys.argv[1]

	annotations=DataFile(sys.argv[2])

	filename=os.path.basename(filepath)

	(x1,y1,x2,y2)=computeBoundingBox(annotations[filename][0])

	(w,h)=(x2-x1,y2-y1)

	img=cv.imread(filepath)

	(x3,x4,y3,y4)=(x1+w//4,x1+3*w//4,y1+h//4,y1+3*h//4)

	print("x3,x4,y3,y4:",x3,x4,y3,y4)

	rect=img[y3:y4,x3:x4,:]

	centers=quantize(rect)

	print("x1,x2,y1,y2:",(x1,x2,y1,y2))

	data=np.reshape(img[y1:y2,x1:x2,:],(-1,3))

	print("data.shape:",data.shape)

	(keys,dists)=scipy.cluster.vq.vq(data,centers)

	print("keys.shape:",keys.shape)

	pixels=np.array([centers[k] for k in keys],dtype=np.uint8).reshape((y2-y1,x2-x1,3))

	img[y1:y2,x1:x2,:]=pixels

	print("image quantized")

	rect=img[y1:y2,x1:x2]

	maskB=cv.inRange(rect,np.array([0,0,0]),np.array([80,80,80]))

	maskB=cv.erode(maskB,np.ones((3,3),np.uint8),iterations=2)

	maskW=cv.inRange(rect,np.array([160,160,160]),np.array([256,256,256]))

	maskW=cv.erode(maskW,np.ones((3,3),np.uint8),iterations=2)

	show(img,filename)

	show(maskB,filename)

	show(maskW,filename)

	stones=cv.bitwise_or(maskB,maskW)

	# houghLines(stones)

	show(stones)

	(contours,hierarchy)=cv.findContours(stones,cv.RETR_LIST,cv.CHAIN_APPROX_SIMPLE)

	contourImg=cv.drawContours(cv.cvtColor(stones,cv.COLOR_GRAY2BGR), contours, -1, (0,255,0), 1)

	for (i,c) in enumerate(contours):

		print(i)

		moments=cv.moments(c)

		center=(moments["m10"]/(moments["m00"] or 1), moments["m01"]/(moments["m00"] or 1))

		print("center:", center)

		cv.circle(contourImg,tuple(map(int,center)),3,(255,255,0))

		area=cv.contourArea(c)

		print("area:",area)

		(x,y,w,h)=cv.boundingRect(c)

		print("bounding box:",(x,y,w,h))

		print("coverage1:",area/(w*h or 1))

		hull=cv.convexHull(c)

		print("coverage2:",area/(cv.contourArea(hull) or 1))

		print()

	show(contourImg)

	# for i in range(10):

	# 	locateStone(stones)

	# distMap=cv.distanceTransform(stones,cv.DIST_L2,5)

	# print("dist map:")

	# show(distMap)

	# print("hit map:")

	# hitMap=detectStones(stones)

	# for i in range(10):

	# 	locateLocalMaximum(hitMap)

# dlib.find_peaks