OneEye Changeset - 6aace8f39e75

Changeset - 6aace8f39e75

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Laman - 6 years ago 2019-03-04 19:29:53

detecting board diagonals with RANSAC

3 files changed with 86 insertions and 4 deletions:

exp/board_detect.py

exp/hough.py

exp/ransac.py

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exp/board_detect.py

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@@ @@ -3,7 +3,6 @@ import sys @@
 sys.path.append("../src")
 import os
 import math
 import random
 import itertools
 import logging as log
@@ @@ -15,6 +14,7 @@ import scipy.ndimage @@
 import scipy.signal
 from geometry import Line
 from ransac import DiagonalRansac
 from annotations import DataFile,computeBoundingBox
 from hough import show,prepareEdgeImg,HoughTransform
 from analyzer.epoint import EPoint
@@ @@ -125,6 +125,16 @@ class BoardDetector: @@
 		transformed=cv.warpPerspective(rect,matrix,(self._rectW,self._rectH))
 		# determine precise board edges
 		intersections=[]
 		for p in lines[0]:
 			for q in lines[1]:
 				intersections.append(p.intersect(q))
 		sack=DiagonalRansac(intersections,19)
 		diagonals=sack.extract(10,2000)
 		log.debug("diagonals candidates: %s",diagonals)
 		for line in diagonals:
 			self._drawLine(linesImg,line,[0,255,255])
 		show(linesImg,"diagonals candidates")
 	def _detectRough(self,img,filename):
 		corners=self._annotations[filename][0]
@@ @@ -191,7 +201,8 @@ class BoardDetector: @@
 		return matrix
 	def _drawLine(self,img,line):
 	def _drawLine(self,img,line,color=None):
 		if not color: color=[0,255,0]
 		(h,w)=img.shape[:2]
 		corners=[EPoint(0,0),EPoint(w,0),EPoint(0,h),EPoint(w,h)] # NW NE SW SE
 		borders=[
@@ @@ -207,7 +218,7 @@ class BoardDetector: @@
 		if any(abs(x)>10**5 for x in [*a,*b]):
 			log.debug("ignored")
 			return
-		cv.line(img,(int(a.x),int(a.y)),(int(b.x),int(b.y)),[0,255,0])
+		cv.line(img,(int(a.x),int(a.y)),(int(b.x),int(b.y)),color)
 if __name__=="__main__":

exp/hough.py

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@@ @@ -27,6 +27,7 @@ class LineBag: @@
 		res=[]
 		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
 			# avoid intersecting lines
 			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
@@ @@ -65,7 +66,7 @@ class HoughTransform: @@
 				(alphaDeg,d)=keys[k]
 				line=Line(alphaDeg*math.pi/180,d-self._diagLen//2)
 				res[-1].append(self._transformOutput(line))
 			res[-1].sort(key=lambda line: line.d)
+			res[-1].sort(key=lambda line: line.d if line.alpha<math.pi else -line.d)
 			i+=1
 		self.show(img)

exp/ransac.py

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@@ new file 100644 @@
 import random
 from geometry import Line
 class LineBag:
 	def __init__(self,capacity):
 		self._capacity=capacity
 		self._bag=[]
 	def put(self,item):
 		# early abort
 		if self._bag and item>self._bag[-1]: return
 		(v,p)=item
 		# mostly filter duplicates
 		for (i,(vi,pi)) in enumerate(self._bag):
 			if abs(p.alpha-pi.alpha)<0.02 and abs(p.d-pi.d)<5:
 				if v<vi: self._bag[i]=item
 				return
 		# add new and remove the last
 		self._bag.append(item)
 		self._bag.sort()
 		if len(self._bag)>self._capacity:
 			self._bag.pop()
 	def pull(self,count=0):
 		return self._bag[:count] if count else self._bag[:]
 class Ransac:
 	def __init__(self,points):
 		self._points=points
 	def extract(self,count,iterations):
 		bag=LineBag(count)
 		for i in range(iterations):
 			line=self._generateLine()
 			score=self._scoreLine(line)
 			bag.put((score+random.random()/1000,line))
 		return [line for (score,line) in bag.pull()]
 	def _generateLine(self):
 		(a,b)=random.sample(self._points,2)
 		return Line.fromPoints(a,b)
 	def _scoreLine(self,line):
 		return sum(min(line.distanceTo(p),5) for p in self._points)
 class DiagonalRansac(Ransac):
 	def __init__(self,points,sideLen):
 		super().__init__(points)
 		self._sideLen=sideLen
 	def _generateLine(self):
 		n=len(self._points)
 		m=self._sideLen
 		ka=random.randrange(0,n)
 		kb=ka
 		while ka//m==kb//m or ka%m==kb%m:
 			kb=random.randrange(0,n)
 		a=self._points[ka]
 		b=self._points[kb]
 		return Line.fromPoints(a,b)

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