OneEye Changeset - 6d4447a2e050

Changeset - 6d4447a2e050

Parent rev.

Child rev.

[Not reviewed]

default

0 1 0

Laman - 6 years ago 2019-02-07 11:27:25

filtering close points, detecting dominant angles

1 file changed with 47 insertions and 3 deletions:

exp/hough.py

0 comments (0 inline, 0 general)

exp/hough.py

➞

Show inline comments

 import sys
 sys.path.append("../src")
 import os
 import sys
 import math
 from datetime import datetime
 import logging as log
 import numpy as np
 import cv2 as cv
 from annotations import DataFile,computeBoundingBox
 from analyzer.epoint import EPoint
 class HoughTransform:
 	def __init__(self,img):
 		(h,w)=img.shape[:2]
 		diagLen=np.sqrt(h**2+w**2)
 		self._center=(w//2,h//2)
 		self._acc=np.zeros((360,int(diagLen//2)+1),dtype=np.int32)
 		self.update(img)
 	def extract(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)
 		log.debug(sorted(list(findPeaks(self._acc)),key=lambda rc: self._acc[rc],reverse=True)[:2*19])
 		peaks=sorted(list(findPeaks(self._acc)),key=lambda rc: self._acc[rc],reverse=True)[:2*19]
 		peaks=self._filterClose(peaks)
 		peaks=[(alpha,d) if alpha<180 else (alpha-180,-d) for (alpha,d) in peaks]
 		peaks.sort(key=lambda rc: rc[0])
 		log.debug("detected peaks: %s",peaks)
 		self._detectDominantAngles(peaks)
 		show(img,"Hough transform accumulator")
 	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(0,360):
 					d=self._computeDist(c,r,alphaDeg)
 					if d>=0: self._acc[(alphaDeg,d)]+=weight
 		log.debug("Hough updated in %s s",round(datetime.now().timestamp()-start,3))
 	def _computeDist(self,x,y,alphaDeg):
 		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 int(d)
 	def _filterClose(self,peaks): # a naive implementation
 		minDist=10
 		center=EPoint(*self._center)
 		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))
 		return res
 def findPeaks(arr2d): # naive implementation
 	def _detectDominantAngles(self,peaks):
 		angles=[alpha for (alpha,d) in peaks]
 		n=len(angles)
 		bandwidth=30
 		k1=0
 		k2=1
 		histogram=[]
 		while k1<n:
 			while (k2<n and angles[k1]+bandwidth>angles[k2]) or (k2>=n and angles[k1]+bandwidth>angles[k2%n]+180):
 				k2+=1
 			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 165>abs(alpha[0]-beta[0])>15]
 		beta=dominantAngles[0]
 		log.debug("dominant angles: %s, %s",alpha,beta)
 		return (alpha[0],beta[0])
 def findPeaks(arr2d): # a naive implementation
 	(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):
 		for c in range(w):
 			if all(r+dr<0 or r+dr>=h or c+dc<0 or c+dc>=w or arr2d[r,c]>arr2d[r+dr,c+dc] or (i<4 and arr2d[r,c]>=arr2d[r+dr,c+dc]) for (i,(dr,dc)) in enumerate(neighbours)):
 				yield (r,c)
 def show(img,filename="x"):
 	cv.imshow(filename,img)
 	cv.waitKey(0)
 	cv.destroyAllWindows()

0 comments (0 inline, 0 general)