Changeset - 40cc3b625eb2
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Laman - 6 years ago 2019-01-22 11:18:50

work on polar hough
2 files changed with 86 insertions and 90 deletions:
exp/stone_detect.py
78
90
src/analyzer/epoint.py
8
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exp/stone_detect.py
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@@ -4,11 +4,13 @@ sys.path.append("../src")
 
import os
 
import math
 
import random
 
import itertools
 

			




	
	
	
		
 
import cv2 as cv

			




	
	
	
		
 
import numpy as np

			




	
	
	
		
 
import scipy.cluster

			




	
	
	
		
 
import scipy.ndimage

			




	
	
	
		
 
import scipy.signal

			




	
	
	
		
 

			




	
	
	
		
 
from annotations import DataFile,computeBoundingBox

			




	
	
	
		
 
from hough import show

			




	
	
		
 
@@ -53,6 +55,62 @@ class Line():

			




	
	
	
		
 
	def __repr__(self): return "Line({0},{1})".format(repr(self.a),repr(self.b))

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
class PolarHough:

			




	
	
	
		
 
	# http://www.cis.pku.edu.cn/vision/vpdetection/LiPYZ10isvc.pdf

			




	
	
	
		
 
	def __init__(self,anglePrecision,lengthPrecision):

			




	
	
	
		
 
		self._anglePrecision=anglePrecision

			




	
	
	
		
 
		self._lengthPrecision=lengthPrecision

			




	
	
	
		
 
		self._maxLength=4096

			




	
	
	
		
 
		n=math.ceil(2*math.pi/anglePrecision)

			




	
	
	
		
 
		self._acc=[[] for i in range(n)]

			




	
	
	
		
 

			




	
	
	
		
 
	def put(self,item):

			




	
	
	
		
 
		k=int(item[0]//self._anglePrecision)

			




	
	
	
		
 
		self._acc[k].append(item)

			




	
	
	
		
 

			




	
	
	
		
 
	def extract(self,count):

			




	
	
	
		
 
		vanishingPoints=[]

			




	
	
	
		
 
		angles=self._extractAngles(count)

			




	
	
	
		
 
		angles=[alpha for (alpha,prominence) in angles]

			




	
	
	
		
 
		bins=self._mapAngles(angles)

			




	
	
	
		
 
		for (alpha,bin) in zip(angles,bins):

			




	
	
	
		
 
			(length,sampleCount)=self._extractLength([dist for (beta,dist) in bin])

			




	
	
	
		
 
			vanishingPoints.append((alpha,length))

			




	
	
	
		
 
		return vanishingPoints

			




	
	
	
		
 

			




	
	
	
		
 
	def _extractAngles(self,k):

			




	
	
	
		
 
		lens=np.array(list(map(len,self._acc)))

			




	
	
	
		
 
		print(lens)

			




	
	
	
		
 
		(peakKeys,info)=scipy.signal.find_peaks(lens,prominence=0)

			




	
	
	
		
 
		res=sorted(zip(info["prominences"],peakKeys),reverse=True)[:k]

			




	
	
	
		
 
		res=[(key*self._anglePrecision,prominence) for (prominence,key) in res]

			




	
	
	
		
 
		print("(angle, prominence):",res,"...",[alpha/self._anglePrecision for (alpha,_) in res])

			




	
	
	
		
 
		return res

			




	
	
	
		
 

			




	
	
	
		
 
	def _mapAngles(self,angles):

			




	
	
	
		
 
		res=[[] for alpha in angles]

			




	
	
	
		
 
		for (i,bin) in enumerate(self._acc):

			




	
	
	
		
 
			beta=i*self._anglePrecision

			




	
	
	
		
 
			key=min(zip(map(lambda alpha: angleDiff(alpha,beta), angles), itertools.count()))[1]

			




	
	
	
		
 
			res[key].extend(bin)

			




	
	
	
		
 
		return res

			




	
	
	
		
 

			




	
	
	
		
 
	def _extractLength(self,arr):

			




	
	
	
		
 
		acc=np.zeros(self._maxLength+1,dtype=np.int32)

			




	
	
	
		
 
		for dist in arr:

			




	
	
	
		
 
			dist=min(dist,self._maxLength)

			




	
	
	
		
 
			acc[int(dist//self._lengthPrecision)]+=1

			




	
	
	
		
 
		res=acc.argmax()

			




	
	
	
		
 
		print("(length, count):",(res*self._lengthPrecision,acc[res]))

			




	
	
	
		
 
		return (res*self._lengthPrecision,acc[res])

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
def angleDiff(alpha,beta):

			




	
	
	
		
 
	diff=abs(alpha-beta)

			




	
	
	
		
 
	if diff>math.pi: diff=2*math.pi-diff

			




	
	
	
		
 
	return diff

			




	
	
	
		
 

			




	
	
	
		
 

			




	
	
	
		
 
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)

			




	
	
		
 
@@ -190,9 +248,9 @@ if __name__=="__main__":

			




	
	
	
		
 
	kernel=np.ones((3,3),np.uint8)

			




	
	
	
		
 
	maskB=cv.inRange(rect,centers[0]-unit,centers[0]+unit)

			




	
	
	
		
 
	maskB=cv.morphologyEx(maskB,cv.MORPH_OPEN,kernel,iterations=1)

			




	
	
	
		
 
	maskB=cv.erode(maskB,kernel,iterations=2)

			




	
	
	
		
 
	maskB=cv.erode(maskB,kernel,iterations=4)

			




	
	
	
		
 
	maskW=cv.inRange(rect,centers[1]-unit,centers[1]+unit)

			




	
	
	
		
 
	maskW=cv.erode(maskW,kernel,iterations=2)

			




	
	
	
		
 
	maskW=cv.erode(maskW,kernel,iterations=3)

			




	
	
	
		
 

			




	
	
	
		
 
	show(img,filename)

			




	
	
	
		
 
	show(maskB,filename)

			




	
	
		
 
@@ -241,92 +299,22 @@ if __name__=="__main__":

			




	
	
	
		
 
		(xb,yb)=line.b

			




	
	
	
		
 
		cv.line(linesImg,(int(xa),int(ya)),(int(xb),int(yb)),(255,255,0),1)

			




	
	
	
		
 
	res.sort()

			




	
	
	
		
 
	# for row in res: print(row)

			




	
	
	
		
 
	# linePack=[

			




	
	
	
		
 
	# 	Line(EPoint(174.457,166.127),EPoint(174.96,27.253)),

			




	
	
	
		
 
	# 	Line(EPoint(191.333,38.075),EPoint(191.485,71.227)),

			




	
	
	
		
 
	# 	Line(EPoint(210.117,167.092),EPoint(205.0,50.0)),

			




	
	
	
		
 
	# 	Line(EPoint(127.7,25.6),EPoint(120.172,179.405)),

			




	
	
	
		
 
	# 	Line(EPoint(127.809,58.481),EPoint(124.324,127.427)),

			




	
	
	
		
 
	# 	Line(EPoint(85.964,191.64),EPoint(97.68,14.477)),

			




	
	
	
		
 
	# 	Line(EPoint(56.447,124.662),EPoint(54.889,137.918))

			




	
	
	
		
 
	# ]

			




	
	
	
		
 
	# linePack=[

			




	
	
	
		
 
	# 	Line(EPoint(56.447,124.662),EPoint(139.695,128.104)),

			




	
	
	
		
 
	# 	Line(EPoint(288.267,74.433),EPoint(191.485,71.227)),

			




	
	
	
		
 
	# 	Line(EPoint(252.926,29.71),EPoint(174.96,27.253)),

			




	
	
	
		
 
	# 	Line(EPoint(274.412,120.07),EPoint(41.065,112.759)),

			




	
	
	
		
 
	# 	Line(EPoint(289.674,108.019),EPoint(26.17,100.538)),

			




	
	
	
		
 
	# 	Line(EPoint(240.702,107.818),EPoint(41.065,112.759)),

			




	
	
	
		
 
	# 	Line(EPoint(174.457,166.127),EPoint(88.192,164.5))

			




	
	
	
		
 
	# ]

			




	
	
	
		
 
	# for (i,p) in enumerate(linePack):

			




	
	
	
		
 
	# 	for q in linePack[i+1:]:

			




	
	
	
		
 
	# 		print(p.intersect(q))

			




	
	
	
		
 
	# show(linesImg)

			




	
	
	
		
 

			




	
	
	
		
 
	# parallels=[]

			




	
	
	
		
 
	# for (i,ab) in enumerate(lines):

			




	
	
	
		
 
	# 	for cd in lines[i+1:]:

			




	
	
	
		
 
	# 		if ab.computeAngle(cd)>math.pi/4:

			




	
	
	
		
 
	# 			continue

			




	
	
	
		
 
	# 		parallels.append((ab,cd))

			




	
	
	
		
 
	# print("parallel lines candidate pairs:",len(parallels))

			




	
	
	
		
 

			




	
	
	
		
 
	# parallels=list(groupParallels(lines,50,w))

			




	
	
	
		
 
	# print("parallel triples:",len(parallels))

			




	
	
	
		
 
	# for (p,q,r) in parallels:

			




	
	
	
		
 
	# 	print(p,q,r)

			




	
	
	
		
 
	# 	print(p.intersect(q))

			




	
	
	
		
 
	# 	print(p.intersect(r))

			




	
	
	
		
 
	# 	print(q.intersect(r))

			




	
	
	
		
 
	# 	print()

			




	
	
	
		
 
	# 	matsImg_=np.copy(matsImg)

			




	
	
	
		
 
	# 	for pi in (p,q,r):

			




	
	
	
		
 
	# 		cv.line(matsImg_,(int(pi.a.x),int(pi.a.y)),(int(pi.b.x),int(pi.b.y)),(0,255,255),1)

			




	
	
	
		
 
	# 	show(matsImg_)

			




	
	
	
		
 
	show(linesImg)

			




	
	
	
		
 

			




	
	
	
		
 
	# p=Line(corners[0],corners[1])

			




	
	
	
		
 
	# q=Line(corners[2],corners[3])

			




	
	
	
		
 
	# r=Line(corners[1],corners[2])

			




	
	
	
		
 
	# s=Line(corners[3],corners[0])

			




	
	
	
		
 
	#

			




	
	
	
		
 
	# matrix=computeRectiMatrix(p,q,r,s)

			




	
	
	
		
 
	# print(matrix)

			




	
	
	
		
 
	# for (point,contour) in stoneLocs:

			




	
	
	
		
 
	# 	point_=EPoint.fromProjective(transformPoint(point.toProjective(),matrix))

			




	
	
	
		
 
	# 	# print(point,"->",point_)

			




	
	
	
		
 
	# 	cv.line(matsImg,(int(point.x),int(point.y)),(int(point_.x),int(point_.y)),(0,255,255),1)

			




	
	
	
		
 
	# points1=np.float32([[p.x-x1,p.y-y1] for p in corners])

			




	
	
	
		
 
	# points2=np.float32([[0,0],[0,400],[400,400],[400,0]])

			




	
	
	
		
 
	# print(points1)

			




	
	
	
		
 
	# print(points2)

			




	
	
	
		
 
	# mat=cv.getPerspectiveTransform(points1,points2)

			




	
	
	
		
 
	# print(mat)

			




	
	
	
		
 
	# show(rect)

			




	
	
	
		
 
	# warped=cv.warpPerspective(rect,matrix,(400,400))

			




	
	
	
		
 
	# show(warped)

			




	
	
	
		
 

			




	
	
	
		
 
	# mats=[]

			




	
	
	
		
 
	# for (i,(p,q)) in enumerate(parallels):

			




	
	
	
		
 
	# 	for (r,s) in parallels[i+1:]:

			




	
	
	
		
 
	# 		if p is r or p is s or q is r or q is s:

			




	
	
	
		
 
	# 			continue

			




	
	
	
		
 
	# 		matrix=computeRectiMatrix(p,q,r,s)

			




	
	
	
		
 
	# 		score=scoreMatrix(matrix,p,r,lines)

			




	
	
	
		
 
	# 		mats.append((score,p,q,r,s,matrix))

			




	
	
	
		
 
	# mats.sort(key=lambda x: x[0])

			




	
	
	
		
 
	# for (score,p,q,r,s,matrix) in mats[:4]:

			




	
	
	
		
 
	# 	print(score,p,q,r,s,matrix)

			




	
	
	
		
 
	# 	matsImg_=np.copy(matsImg)

			




	
	
	
		
 
	# 	for ab in (p,q,r,s):

			




	
	
	
		
 
	# 		((xa,ya),(xb,yb))=(ab.a,ab.b)

			




	
	
	
		
 
	# 		cv.line(matsImg_,(int(xa),int(ya)),(int(xb),int(yb)),(255,255,0),1)

			




	
	
	
		
 
	# 	show(matsImg_)

			




	
	
	
		
 
	# for (score,p,q,r,s,matrix) in mats[-4:]:

			




	
	
	
		
 
	# 	print(score,p,q,r,s,matrix)

			




	
	
	
		
 
	# 	matsImg_=np.copy(matsImg)

			




	
	
	
		
 
	# 	for ab in (p,q,r,s):

			




	
	
	
		
 
	# 		((xa,ya),(xb,yb))=(ab.a,ab.b)

			




	
	
	
		
 
	# 		cv.line(matsImg_,(int(xa),int(ya)),(int(xb),int(yb)),(0,0,255),1)

			




	
	
	
		
 
	# 	show(matsImg_)

			




	
	
	
		
 
	imgSize=img.shape[:2]

			




	
	
	
		
 
	print("image size:",imgSize)

			




	
	
	
		
 
	imgCenter=EPoint(imgSize[1]/2,imgSize[0]/2)-EPoint(x1,y1)

			




	
	
	
		
 
	polarHough=PolarHough(math.pi/180,10)

			




	
	
	
		
 
	for (i,ab) in enumerate(lines):

			




	
	
	
		
 
		for cd in lines[i+1:]:

			




	
	
	
		
 
			point=ab.intersect(cd)

			




	
	
	
		
 
			if 0<=point.x<=w and 0<=point.y<=h: continue

			




	
	
	
		
 
			print(point,"->",point.toPolar(imgCenter))

			




	
	
	
		
 
			polarHough.put(point.toPolar(imgCenter))

			




	
	
	
		
 
	vanish=[EPoint.fromPolar(p,imgCenter) for p in polarHough.extract(2)]

			




	
	
	
		
 
	print(vanish)

			




	
	
	
		
 
	(a,b,c,d)=corners

			




	
	
	
		
 
	(p,q,r,s)=(Line(a,b),Line(b,c),Line(c,d),Line(d,a))

			




	
	
	
		
 
	v1=p.intersect(r)

			




	
	
	
		
 
	v2=q.intersect(s)

			




	
	
	
		
 
	print("true vanishing points:",v1,"~",v1.toPolar(imgCenter),"and",v2,"~",v2.toPolar(imgCenter))

			




        

    


    
    

    

        

                

                    src/analyzer/epoint.py
                

                

                  
                      
                        

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@@ -24,12 +24,20 @@ class EPoint:

			




	
	
	
		
 
		if point.item(0)==0: return None

			




	
	
	
		
 
		return EPoint(point.item(1)/point.item(0),point.item(2)/point.item(0))

			




	
	
	
		
 

			




	
	
	
		
 
	@staticmethod

			




	
	
	
		
 
	def fromPolar(point,center):

			




	
	
	
		
 
		(alpha,length)=point

			




	
	
	
		
 
		x=math.cos(alpha)

			




	
	
	
		
 
		y=math.sin(alpha)

			




	
	
	
		
 
		return length*EPoint(x,y)+center

			




	
	
	
		
 

			




	
	
	
		
 
	def toProjective(self):

			




	
	
	
		
 
		return (1,self._x,self._y)

			




	
	
	
		
 

			




	
	
	
		
 
	def toPolar(self,center):

			




	
	
	
		
 
		v=self-center

			




	
	
	
		
 
		alpha=math.atan2(v.y,v.x)

			




	
	
	
		
 
		if alpha<0: alpha+=2*math.pi

			




	
	
	
		
 
		k=self.dist(center)

			




	
	
	
		
 
		return (alpha,k)

			




	
	
	
		
 

			




        

    



    


    



    



      

      





    
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