OneEye Changeset - 634319abff9f

Changeset - 634319abff9f

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Laman - 6 years ago 2019-04-16 20:19:53

experimental randomized Hough transform

1 file changed with 113 insertions and 0 deletions:

exp/hough.py

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exp/hough.py

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 import sys
 sys.path.append("../src")
 import math
 import random
 from datetime import datetime
 import os.path
 import logging as log
 import numpy as np
 import scipy.optimize
 import scipy.signal
 import cv2 as cv
 import config as cfg
 from geometry import EPoint,Line
 DEBUG=True
 class LineBag:
 	def __init__(self):
 		self._lines=[]
 	def put(self,score,alpha,beta,peaks):
 		self._lines.append((score,alpha,beta,peaks))
 	def pull(self,count):
 		self._lines.sort(reverse=True)
@@ @@ -147,48 +148,160 @@ class HoughTransform: @@
 		(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 _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)
 class Accumulator:
 	NEIGHBOURHOOD=2
 	def __init__(self):
 		self._acc=[]
 		self._hits=[]
 	def add(self,line):
 		(d,k)=self._findClosest(line)
 		if d<=self.NEIGHBOURHOOD:
 			self._acc=self._averageLines(self._acc[k],line,self._hits[k],1)
 			self._hits[k]+=1
 		else:
 			k=-1
 			self._acc.append(line)
 			self._hits.append(1)
 		return (self._hits[k],k)
 	def pop(self,k):
 		acc=self._acc
 		(acc[k],acc[-1])=(acc[-1],acc[k])
 		hits=self._hits
 		(hits[k],hits[-1])=(hits[-1],hits[k])
 		hits.pop()
 		return acc.pop()
 	def _findClosest(self,line):
 		def dist(p,q):
 			alpha=p.alpha*180/math.pi
 			beta=q.alpha*180/math.pi
 			gamma=abs(alpha-beta)
 			if gamma>180: gamma=360-gamma
 			return math.sqrt(gamma**2+(p.d-q.d)**2)
 		(d,key)=min(zip((dist(line,p) for p in self._acc), range(len(self._acc))))
 		return (d,key)
 	def _averageLines(self,ab,cd,w1,w2):
 		w=w1+w2
 		(a,b)=ab.toPoints()
 		(c,d)=cd.toPoints()
 		e=(a*w1+c*w2)/w
 		f=(b*w1+c*w2)/w
 		return Line.fromPoints(e,f)
 class RandomizedHoughTransform:
 	HIT_LIMIT=10
 	CANDIDATE_LIMIT=10
 	MIN_SCORE=50
 	def __init__(self,img):
 		self._img=np.copy(img)
 		(self._h,self._w)=img.shape[:2]
 		self._acc=Accumulator()
 		self._candidates=[]
 		self._res=[]
 	def _sampleLine(self):
 		""":return: (Line) p"""
 		a=self._chooseRandomPixel()
 		b=self._chooseRandomPixel()
 		while b==a: b=self._chooseRandomPixel()
 		return Line.fromPoints(a,b)
 	def _updateAcc(self,line):
 		(hits,k)=self._acc.add(line)
 		if hits>=self.HIT_LIMIT:
 			self._addCandidate(self._acc.pop(k))
 	def _addCandidate(self,line):
 		self._candidates.append(line)
 		if len(self._candidates)>=self.CANDIDATE_LIMIT:
 			for p in self._candidates:
 				p_=self._confirmLine(p)
 				if p_: self._res.append(p_)
 			self._candidates=[]
 	def _chooseRandomPixel(self):
 		val=0
 		while not val:
 			x=random.randrange(0,self._w)
 			y=random.randrange(0,self._h)
 			val=self._img[y,x]
 		return EPoint(x,y)
 	def _confirmLine(self,line):
 		score=0
 		for point in self._walkLine(line):
 			if self._img[point]==1:
 				score+=1
 		if score>self.MIN_SCORE:
 			for point in self._walkLine(line): # erase the line
 				self._img[point]=0
 			return line
 		else: return None
 	def _walkLine(self,line):
 		(a,b,c)=line.toNormal()
 		if abs(line.alpha-math.pi/2)<math.pi/4 or abs(line.alpha-3*math.pi/2)<math.pi/4: # vertical normal ~ horizontal line
 			for x in range(self._w):
 				y=int((-c-a*x)/b)
 				if 0<=y<self.h:
 					yield (y,x)
 		else: # a predominantly vertical line
 			for y in range(self._h):
 				x=int((-c-b*y)/a)
 				if 0<=x<self.w:
 					yield (y,x)
 def show(img,filename="x"):
 	if cfg.INTERACTIVE:
 		cv.imshow(filename,img)
 		cv.waitKey(0)
 		cv.destroyAllWindows()
 	else:
 		d=int(datetime.now().timestamp())
 		path=os.path.join(cfg.imgDir,"{0} {1:03} {2}.png".format(d,cfg.i,filename))
 		cfg.i+=1
 		cv.imwrite(path,img)
 def filterVert(edges):
 	kernel = np.array([[1,0,1],[1,0,1],[1,0,1]],np.uint8)
 	edges = cv.erode(edges,kernel)
 	kernel=np.array([[0,1,0],[0,1,0],[0,1,0]],np.uint8)
 	edges=cv.dilate(edges,kernel)
 	return edges
 def filterHor(edges):
 	kernel = np.array([[1,1,1],[0,0,0],[1,1,1]],np.uint8)
 	edges = cv.erode(edges,kernel)
 	kernel=np.array([[0,0,0],[1,1,1],[0,0,0]],np.uint8)
 	edges=cv.dilate(edges,kernel)

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