OneEye Changeset - 90090fca08f9

Changeset - 90090fca08f9

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Laman - 6 years ago 2019-02-17 10:44:37

experiment with double Hough transform

1 file changed with 114 insertions and 41 deletions:

exp/hough.py

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exp/hough.py

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 import sys
 sys.path.append("../src")
 import os
 import math
 from datetime import datetime
 import logging as log
 import numpy as np
 import scipy.optimize
 import cv2 as cv
-from annotations import DataFile,computeBoundingBox
+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])
 		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 _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)
 		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 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):
 		self._angleBandwidth=30 # degrees
 		(h,w)=img.shape[:2]
@@ @@ -30,21 +118,25 @@ class HoughTransform: @@
 		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)
 		(alpha,beta)=self._detectDominantAngles(peaks)
 		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]))
 		doublePeaks=peaks+[(alpha+180,-d) for (alpha,d) in peaks]
 		params=self._computeGridParams([(gamma,d+shift) for (gamma,d) in doublePeaks if alpha<=gamma<=alpha+self._angleBandwidth])
 		self._drawGridCurve(img,params,0)
 		params=self._computeGridParams([(gamma,d+shift) for (gamma,d) in doublePeaks if beta<=gamma<=beta+self._angleBandwidth])
 		self._drawGridCurve(img,params,1)
 		for (i,line) in enumerate(lines):
 			self.drawLine(img,line,i)
 		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):
@@ @@ -138,19 +230,32 @@ class HoughTransform: @@
 		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=int(curve(x))
+			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,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):
 		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)
@@ @@ -204,38 +309,6 @@ def houghLines(bwImg): @@
 	if lines is None: lines=[]
 	for line in lines:
 		x1,y1,x2,y2 = line[0]
 		cv.line(colorImg,(x1,y1),(x2,y2),(0,255,0),1)
 	show(colorImg)
 if __name__=="__main__":
 	i=sys.argv[1]
 	annotations=DataFile("/home/laman/Projekty/python/oneEye/images/annotations.json.gz")
 	filename="{0}.jpg".format(i)
 	img=cv.imread(os.path.join("/home/laman/Projekty/python/oneEye/images/",filename))
 	(x1,y1,x2,y2)=computeBoundingBox(annotations[filename][0])
 	img=img[y1:y2, x1:x2, :]
 	# blurred=cv.GaussianBlur(img,(5,5),0)
 	# small=cv.resize(img,None,fx=0.5,fy=0.5,interpolation=cv.INTER_AREA)
 	small=img
 	clahe = cv.createCLAHE(clipLimit=2.0, tileGridSize=(8,8))
 	gray=cv.cvtColor(small,cv.COLOR_BGR2GRAY)
 	# gray=clahe.apply(gray)
 	show(gray)
 	edges=cv.Canny(gray,70,130)
 	show(edges)
 	edges=filterHor(edges)+filterVert(edges)+filterDiag(edges)
 	show(edges)
 	# kernel = np.ones((2,2),np.uint8)
 	# edges = cv.morphologyEx(edges, cv.MORPH_DILATE, kernel)
 	# show(edges)
 	# edges=cv.morphologyEx(edges,cv.MORPH_ERODE,kernel)
 	# show(edges)
 	colorEdges=cv.cvtColor(edges,cv.COLOR_GRAY2BGR)
 	# houghLines(edges)
 	h=HoughTransform(edges)
 	h.extract()

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