OneEye Changeset - 275f7307dd32

Changeset - 275f7307dd32

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Laman - 6 years ago 2019-02-20 14:25:16

detecting lines in Hough transform accumulator

2 files changed with 42 insertions and 102 deletions:

exp/board_detect.py

exp/hough.py

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exp/board_detect.py

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@@ @@ -122,7 +122,7 @@ class BoardDetector: @@
 			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,5)
+		hough.update(stonesImg,3)
 		hough.extract()
 		# # detect lines passing through the stones

exp/hough.py

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@@ @@ -7,100 +7,31 @@ import logging as log @@
 import numpy as np
 import scipy.optimize
 import scipy.signal
 import cv2 as cv
 from geometry import Line
 from analyzer.epoint import EPoint
 DEBUG=True
 class BaseHough:
 	def __init__(self,width,height):
 		self._diagLen=int(np.sqrt(height**2+width**2))+1
 		self._center=(width//2,height//2)
 		self._acc=np.zeros((180,self._diagLen),dtype=np.int32)
 	def update(self,x,y,weight=1):
 		""":param x: number, 0 <= x < width
 		:param y: number, 0 <= y < height"""
 		for alphaDeg in range(0,180):
 			d=self._computeDist(x,y,alphaDeg)+self._diagLen//2
 			self._acc[(alphaDeg,d)]+=weight
 	def extract(self,n):
 		shift=self._diagLen//2
 		peaks=sorted(list(findPeaks(self._acc)),key=lambda rc: self._acc[rc],reverse=True)
 		peaks=self._filterClose(peaks)[:n]
 		log.debug("detected peaks: %s",[(alpha,d-shift) for (alpha,d) in peaks])
 class LineBag:
 	def __init__(self):
 		self._lines=[]
 		img=self._createImg()
 		img=self._markPeaks(img,self._filterClose(peaks))
 		self.show(img)
 		res=[]
 		for (alphaDeg,d) in peaks:
 			alphaRad=alphaDeg*math.pi/180
 			baseLine=Line(alphaRad,0)
 			dd=baseLine.distanceTo(EPoint(*self._center)) # to shift d from the center to 0,0
 			res.append(Line(alphaRad, dd+d-shift))
 		log.debug("detected lines: %s",res)
 		return res
 	def _computeDist(self,x,y,alphaDeg):
 		"""Compute the distance of a line with the provided alphaDeg declination and passing the (x,y) point to the image center.
 		The returned distance might be negative (meaning the angle is in fact alpha+180)."""
 		alphaRad=alphaDeg*math.pi/180
 		(x0,y0)=self._center
 		(dx,dy)=(x-x0,y-y0)
 		d=dx*math.cos(alphaRad)+dy*math.sin(alphaRad)
 		return round(d)
 	def put(self,score,alpha,beta):
 		self._lines.append((score,alpha,beta))
 	def _filterClose(self,peaks): # a naive implementation
 		"""Discard points with Euclidean distance on the original image lower than 10.
 		From such pairs keep only the one with a higher value in the accumulator.
 		This can delete a series of points. If a-b and b-c are close and a>b>c, only a is kept."""
 		minDist=13
 		center=EPoint(*self._center)
 	def pull(self,count):
 		self._lines.sort(reverse=True)
 		res=[]
 		for (alphaDeg,d) in peaks:
 			alphaRad=alphaDeg*math.pi/180
 			point=EPoint.fromPolar((alphaRad,d),center)
 			ctrl=True
 			for (betaDeg,e) in peaks:
 				betaRad=betaDeg*math.pi/180
 				point_=EPoint.fromPolar((betaRad,e),center)
 				if point.dist(point_)<minDist and self._acc[(alphaDeg,d)]<self._acc[(betaDeg,e)]:
 					ctrl=False
 			if ctrl: res.append((alphaDeg,d))
 		for (score,alpha,beta) in self._lines:
 			if any(abs(alpha-gamma)<10 and abs(beta-delta)<10 for (_,gamma,delta) in res): continue
 			if any((beta-delta)!=0 and (alpha-gamma)/(beta-delta)<0 for (_,gamma,delta) in res): continue
 			res.append((score,alpha,beta))
 			if len(res)>=count: break
 		return res
 	def show(self,img=None):
 		if not DEBUG: return
 		if img is None: img=self._createImg()
 		show(img,"Hough transform accumulator")
 	def _createImg(self):
 		maxVal=self._acc.max()
 		arr=np.expand_dims(np.uint8(255*self._acc//maxVal),axis=2)
 		img=np.concatenate((arr,arr,arr),axis=2)
 		(h,w)=img.shape[:2]
 		for x in range(0,w,4): # y axis
 			img[h//2,x]=[255,255,255]
 		for y in range(0,h,4):
 			img[y,w//2]=[255,255,255]
 		return img
 	def _markPeaks(self,img,peaks):
 		colors=[[255,0,0],[255,255,0],[0,255,0],[0,255,255],[0,0,255]]
 		for (i,(alpha,d)) in enumerate(peaks[:38]):
 			cv.drawMarker(img,(d,alpha),colors[i//9],cv.MARKER_TILTED_CROSS)
 		return img
 class HoughTransform:
 	def __init__(self,img):
@@ @@ -114,26 +45,13 @@ class HoughTransform: @@
 		self.update(img)
 	def extract(self):
 		shift=self._diagLen//2
 		allPeaks=sorted(list(findPeaks(self._acc)),key=lambda rc: self._acc[rc],reverse=True)
 		peaks=allPeaks[:38]
 		peaks=[(alpha,d-shift) for (alpha,d) in peaks]
 		peaks=self._filterClose(peaks)
 		peaks.sort(key=lambda rc: rc[0])
 		log.debug("detected peaks: %s",peaks)
 		img=self._createImg()
 		(ab,cd)=self._detectLines()
 		for (score,alpha,beta) in (ab,cd):
 			log.debug("score: %s",score)
 			log.debug("alpha, beta: %s, %s",alpha,beta)
 			cv.line(img,(0,alpha),(self._diagLen-1,beta),(0,255,255))
 		h2=BaseHough(self._diagLen,180+90)
 		for (alpha,d) in peaks:
 			h2.update(d+shift,alpha)
 			if alpha<90:
 				h2.update(shift-d,alpha+180)
 		lines=h2.extract(3)
 		img=self._createImg()
 		img=self._markPeaks(img,self._filterClose(allPeaks[:38]))
 		for (i,line) in enumerate(lines):
 			self.drawLine(img,line,i)
 		self.show(img)
 	def update(self,img,weight=1):
@@ @@ -192,6 +110,28 @@ class HoughTransform: @@
 		log.debug("dominant angles: %s, %s",alpha,beta)
 		return (alpha[0],beta[0])
 	def _detectLines(self):
 		bag=LineBag()
 		for alpha in range(0,180,2):
 			for beta in range(alpha-45,alpha+45,2):
 				accLine=self._readLine(alpha,beta)
 				(peaks,props)=scipy.signal.find_peaks(accLine,prominence=0)
 				prominences=sorted(props["prominences"],reverse=True)[:19]
 				bag.put(sum(prominences),alpha,beta)
 		return bag.pull(2)
 	def _readLine(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:
 				if k<-180 or k>360: print(alpha,beta,i,k)
 				k=k%180
 				i=n+1-i
 			res.append(self._acc[k][i])
 		return res
 	def _computeGridParams(self,lines):
 		log.debug("computing grid parameters for: %s",lines)
 		angles=[alpha for (alpha,d) in lines]

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