# HG changeset patch
# User Laman
# Date 2019-02-17 10:44:37
# Node ID 90090fca08f902ba4d88f29469c583f28ef82cfe
# Parent 7c268e382b96e468bfbf9c390a2e7e92975c4187
experiment with double Hough transform
diff --git a/exp/hough.py b/exp/hough.py
--- a/exp/hough.py
+++ b/exp/hough.py
@@ -1,7 +1,6 @@
import sys
sys.path.append("../src")
-import os
import math
from datetime import datetime
import logging as log
@@ -10,9 +9,98 @@ 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):
@@ -33,15 +121,19 @@ class HoughTransform:
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):
@@ -141,13 +233,26 @@ class HoughTransform:
(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):
@@ -207,35 +312,3 @@ def houghLines(bwImg):
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()