OneEye Changeset - 5e5a8c4642c5

Changeset - 5e5a8c4642c5

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Laman - 6 years ago 2019-02-21 17:31:58

presenting detected peaks

1 file changed with 31 insertions and 17 deletions:

exp/hough.py

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exp/hough.py

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@@ @@ -10,56 +10,59 @@ import scipy.optimize @@
 import scipy.signal
 import cv2 as cv
 from analyzer.epoint import EPoint
 DEBUG=True
 class LineBag:
 	def __init__(self):
 		self._lines=[]
 	def put(self,score,alpha,beta):
 		self._lines.append((score,alpha,beta))
 	def put(self,score,alpha,beta,peaks):
 		self._lines.append((score,alpha,beta,peaks))
 	def pull(self,count):
 		self._lines.sort(reverse=True)
 		res=[]
 		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))
 		for (score,alpha,beta,peaks) 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,peaks))
 			if len(res)>=count: break
 		return res
 class HoughTransform:
 	def __init__(self,img):
 		self._angleBandwidth=30 # degrees
 		(h,w)=img.shape[:2]
 		self._diagLen=int(np.sqrt(h**2+w**2))+1
 		self._center=(w//2,h//2)
 		self._acc=np.zeros((180,self._diagLen),dtype=np.int32)
 		self.update(img)
 	def extract(self):
 		img=self._createImg()
 		self.show(img)
 		(ab,cd)=self._detectLines()
 		for (score,alpha,beta) in (ab,cd):
 		i=0
 		for (score,alpha,beta,peaks) 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))
 			self._drawLine(img,alpha,beta,peaks,i)
 			i+=1
 		self.show(img)
 	def update(self,img,weight=1):
 		start=datetime.now().timestamp()
 		for (r,row) in enumerate(img):
 			for (c,pix) in enumerate(row):
 				if pix==0: continue
 				for alphaDeg in range(0,180):
 					d=self._computeDist(c,r,alphaDeg)+self._diagLen//2
 					self._acc[(alphaDeg,d)]+=weight
 		log.debug("Hough updated in %s s",round(datetime.now().timestamp()-start,3))
@@ @@ -103,42 +106,41 @@ 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(0,180,2):
 			for beta in range(alpha-45,alpha+45,2):
 				accLine=self._readLine(alpha,beta)
 		for alpha in range(0,180,3):
 			for beta in range(min(alpha-60,0),alpha+60,3):
 				accLine=[self._acc[key] for key in self._readLineKeys(alpha,beta)]
 				(peaks,props)=scipy.signal.find_peaks(accLine,prominence=0)
 				prominences=sorted(props["prominences"],reverse=True)[:19]
 				bag.put(sum(prominences),alpha,beta)
 				(prominences,peaks)=zip(*sorted(zip(props["prominences"],peaks),reverse=True)[:19])
 				bag.put(sum(prominences),alpha,beta,peaks)
 		return bag.pull(2)
-	def _readLine(self,alpha,beta):
+	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:
 				if k<-180 or k>360: print(alpha,beta,i,k)
 				k=k%180
 				i=n+1-i
-			res.append(self._acc[k][i])
+			res.append((k,i))
 		return res
 	def _computeGridParams(self,lines):
 		log.debug("computing grid parameters for: %s",lines)
 		angles=[alpha for (alpha,d) in lines]
 		dists=[d for (alpha,d) in lines]
 		curve=lambda x,a,b,c,d: a*x**3+b*x**2+c*x+d
 		(params,cov)=scipy.optimize.curve_fit(curve,dists,angles)
 		log.debug("result: %s",params)
 		return params
 	def show(self,img=None):
@@ @@ -169,30 +171,42 @@ class HoughTransform: @@
 	def _drawGridCurve(self,img,params,colorKey=0):
 		colors=[[0,255,255],[255,0,255],[255,255,0]]
 		color=colors[colorKey]
 		(a,b,c,d)=params
 		(h,w)=img.shape[:2]
 		curve=lambda x: a*x**3+b*x**2+c*x+d
 		for x in range(0,w,3):
 			y=round(curve(x))
 			if y<0 or y>=2*h: continue
 			if y<h:	img[y,x]=color
 			else: img[y%h,-x]=color
 	def _drawLine(self,img,alpha,beta,peaks,colorKey):
 		colors=[[0,255,255],[255,0,255],[255,255,0]]
 		color=colors[colorKey]
 		(h,w)=img.shape[:2]
 		keys=self._readLineKeys(alpha,beta)
 		for (y,x) in keys:
 			if x%3!=0: continue
 			if y<0 or y>=h: continue
 			img[y,x]=color
 		for k in peaks:
 			(y,x)=keys[k]
 			cv.drawMarker(img,(x,y),color,cv.MARKER_TILTED_CROSS,8)
 	def drawLine(self,img,line,colorKey=0):
 		colors=[[0,255,255],[255,0,255],[255,255,0]]
 		color=colors[colorKey]
 		(h,w)=img.shape[:2]
 		(a,b,c)=line.toNormal()
 		print("%",a,b,c)
 		if b==0: return
 		for x in range(1,w,3):
 			y=round((-c-a*x)/b) + (0 if b>=0 else 180)
 			if y<0 or y>=h: continue
 			img[y,x]=color
 def findPeaks(arr2d): # a naive implementation
 	"""Scan 8-neighbourhood and for each peak or top plateau yield one point. For plateaus yield the """
 	(h,w)=arr2d.shape
 	neighbours=[(-1,-1),(-1,0),(-1,1),(0,-1),(0,1),(1,-1),(1,0),(1,1)]
 	for r in range(h):

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