OneEye Changeset - c3345c5afb6d

Changeset - c3345c5afb6d

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Laman - 6 years ago 2019-02-22 13:01:54

more robust color handling

2 files changed with 24 insertions and 15 deletions:

exp/board_detect.py

exp/hough.py

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exp/board_detect.py

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@@ @@ -17,29 +17,34 @@ from geometry import Line @@
 from polar_hough import PolarHough
 from annotations import DataFile,computeBoundingBox
 from hough import show,prepareEdgeImg,HoughTransform
 from analyzer.epoint import EPoint
 from analyzer.corners import Corners
 random.seed(361)
 log.basicConfig(level=log.DEBUG,format="%(message)s")
 def kmeans(img):
 	arr=np.reshape(img,(-1,3)).astype(np.float)
 	colors=np.array([[0,0,0],[255,255,255],[193,165,116]],np.float)
 	log.debug(colors)
 	(centers,distortion)=scipy.cluster.vq.kmeans(arr,colors)
 	wood=[193,165,116]
 	(centers,distortion)=scipy.cluster.vq.kmeans(arr,3)
 	log.debug("k-means centers: %s",centers)
 	return centers
 	(black,empty,white)=sorted(centers,key=sum)
 	if np.linalg.norm(black)>np.linalg.norm(black-wood):
 		black=None
 	if np.linalg.norm(white-[255,255,255])>np.linalg.norm(white-wood):
 		white=None
 	log.debug("black, white: %s, %s",black,white)
 	return (black,white,centers)
 def quantize(img,centers):
 	origShape=img.shape
 	data=np.reshape(img,(-1,3))
 	(keys,dists)=scipy.cluster.vq.vq(data,centers)
 	pixels=np.array([centers[k] for k in keys],dtype=np.uint8).reshape(origShape)
 	return pixels
 def filterStones(contours,bwImg,stoneDims):
 	contourImg=cv.cvtColor(bwImg,cv.COLOR_GRAY2BGR)
@@ @@ -94,44 +99,44 @@ class BoardDetector: @@
 	def __call__(self,img,filename):
 		# approximately detect the board
 		(h,w)=img.shape[:2]
 		log.debug("image dimensions: %s x %s",w,h)
 		show(img,filename)
 		(x1,y1,x2,y2)=self._detectRough(img,filename)
 		rect=img[y1:y2,x1:x2]
 		self._rectW=x2-x1
 		self._rectH=y2-y1
 		self._rect=rect
 		# quantize colors
 		colors=self._sampleColors(rect)
+		(black,white,colors)=self._sampleColors(rect)
 		quantized=quantize(rect,colors)
 		gray=cv.cvtColor(rect,cv.COLOR_BGR2GRAY)
 		edges=cv.Canny(gray,70,130)
 		show(edges,"edges")
 		quantized=quantized & (255-cv.cvtColor(edges,cv.COLOR_GRAY2BGR))
 		show(quantized,"quantized, edges separated")
 		# detect black and white stones
-		stones=self._detectStones(quantized,colors)
+		stones=self._detectStones(quantized,black,white)
 		# detect lines from edges and stones
 		edgeImg=prepareEdgeImg(rect)
 		hough=HoughTransform(edgeImg)
 		stonesImg=np.zeros((self._rectH,self._rectW),np.uint8)
 		for (point,c) in stones:
 			cv.circle(stonesImg,(int(point.x),int(point.y)),2,255,-1)
 		# cv.drawContours(stonesImg,[c for (point,c) in stones],-1,255,-1)
 		show(stonesImg,"detected stones")
-		hough.update(stonesImg,3)
+		hough.update(stonesImg,5)
 		hough.extract()
 		# # detect lines passing through the stones
 		# lines=self._constructLines(stones)
+		#
 		# # detect vanishing points of the lines
 		# imgCenter=EPoint(w//2-x1, h//2-y1)
 		# (a,b,c,d)=(p-EPoint(x1,y1) for p in self._annotations[filename][0])
 		# (p,q,r,s)=(Line(a,b),Line(b,c),Line(c,d),Line(d,a))
 		# v1=p.intersect(r)
 		# v2=q.intersect(s)
 		# log.debug("true vanishing points: %s ~ %s, %s ~ %s",v1,v1.toPolar(imgCenter),v2,v2.toPolar(imgCenter))
@@ @@ -145,48 +150,52 @@ class BoardDetector: @@
 	def _detectRough(self,img,filename):
 		corners=self._annotations[filename][0]
 		(x1,y1,x2,y2)=computeBoundingBox(corners)
 		log.debug("bounding box: (%s,%s) - (%s,%s)",x1,y1,x2,y2)
 		return (x1,y1,x2,y2)
 	def _sampleColors(self,rect):
 		(h,w)=rect.shape[:2]
 		minirect=rect[h//4:3*h//4, w//4:3*w//4]
 		return kmeans(minirect)
-	def _detectStones(self,quantized,colors):
+	def _detectStones(self,quantized,black,white):
 		(h,w)=quantized.shape[:2]
-		mask=self._maskStones(quantized,colors)
+		mask=self._maskStones(quantized,black,white)
 		stoneDims=(w/19,h/19)
 		log.debug("stone dims: %s - %s",tuple(x/2 for x in stoneDims),stoneDims)
 		(contours,hierarchy)=cv.findContours(mask,cv.RETR_LIST,cv.CHAIN_APPROX_SIMPLE)
 		stoneLocs=filterStones(contours,mask,stoneDims)
 		return stoneLocs
-	def _maskStones(self,quantized,colors):
+	def _maskStones(self,quantized,black,white):
 		unit=np.array([1,1,1],dtype=np.uint8)
 		maskB=cv.inRange(quantized,colors[0]-unit,colors[0]+unit)
 		if black is not None:
 			maskB=cv.inRange(quantized,black-unit,black+unit)
 		distTransform=cv.distanceTransform(maskB,cv.DIST_L2,5)
 		maskB=cv.inRange(distTransform,6,20)
 		show(maskB,"black areas")
 		else: maskB=np.zeros(quantized.shape[:2],dtype=np.uint8)
 		maskW=cv.inRange(quantized,colors[1]-unit,colors[1]+unit)
 		if white is not None:
 			maskW=cv.inRange(quantized,white-unit,white+unit)
 		distTransform=cv.distanceTransform(maskW,cv.DIST_L2,5)
 		maskW=cv.inRange(distTransform,6,20)
 			show(maskW,"white areas")
 		else: maskW=np.zeros(quantized.shape[:2],dtype=np.uint8)
 		show(maskW,"white areas")
 		stones=cv.bitwise_or(maskB,maskW)
 		show(stones,"black and white areas")
 		return stones
 	def _constructLines(self,stoneLocs):
 		lineDict=dict()
 		# minCount=min(max(math.sqrt(len(stoneLocs))-4,3),7)
 		minCount=6
 		log.debug("min count: %s",minCount)
 		points=[point for (point,contour) in stoneLocs]
 		for line in groupLines(points,minCount,2):
 			key=line.getSortedPoints()

exp/hough.py

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@@ @@ -106,26 +106,26 @@ class HoughTransform: @@
 			histogram.append((angles[k1],k2-k1))
 			k1+=1
 		log.debug("angles histogram: %s",histogram)
 		dominantAngles=sorted(histogram,key=lambda xy: xy[1],reverse=True)
 		alpha=dominantAngles[0]
 		dominantAngles=[beta for beta in dominantAngles if 180-bandwidth>abs(alpha[0]-beta[0])>bandwidth]
 		beta=dominantAngles[0]
 		log.debug("dominant angles: %s, %s",alpha,beta)
 		return (alpha[0],beta[0])
 	def _detectLines(self):
 		bag=LineBag()
 		for alpha in range(0,180,3):
 			for beta in range(min(alpha-60,0),alpha+60,3):
 		for alpha in range(0,180,2):
 			for beta in range(max(alpha-60,0),alpha+60,2):
 				accLine=[self._acc[key] for key in self._readLineKeys(alpha,beta)]
 				(peaks,props)=scipy.signal.find_peaks(accLine,prominence=0)
 				(prominences,peaks)=zip(*sorted(zip(props["prominences"],peaks),reverse=True)[:19])
 				bag.put(sum(prominences),alpha,beta,peaks)
 		return bag.pull(2)
 	def _readLineKeys(self,alpha,beta):
 		n=self._diagLen-1
 		res=[]
 		for i in range(n+1):
 			k=round((alpha*(n-i)+beta*i)/n)
 			if k<0 or k>=180:

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