Hello. I created script to get arrows from the image. Im trying to detect orientation for each arrow. With my script i manage to get somewhat accurate results. The problem is that Im getting same results if arrows are oriented up or down, to the left or to the right. How to know if the arrow is pointing to left or to the right? In both cases of the pictures below i get same result around 90 deg.
the script is folowing
import numpy as np
import cv2
import math
img = cv2.imread('sample7.png')
height, width, channels = img.shape
img = cv2.resize(img, (width*8, height*8))
img = cv2.medianBlur(img,5)
imgray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret,th1 = cv2.threshold(imgray,100,255,cv2.THRESH_BINARY)
edged=cv2.Canny(th1,127,200)
im2,contours,h = cv2.findContours(edged.copy(),cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
(img2,cnts, _) = cv2.findContours(edged.copy(), cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
screenCnt=None
flag_t=False
flag_s=False
kot=[]
for c in cnts:
approx = cv2.approxPolyDP( c, 0.01*cv2.arcLength(c,True), True )
area = cv2.contourArea(c)
#print area
if int(len(approx)) > 8 and area > 600 and area < 1100:
anglelist=[]
cv2.drawContours(img, [approx], -1, (0, 255, 255), 1)
(x,y),(MA,ma),angle = cv2.fitEllipse(c)
print round(angle,-1)
kot.append(round(angle,-1))
d = {}
for elm in kot:
d[elm] = d.get(elm, 0) + 1
counts = [(j,i) for i,j in d.items()]
count, max_elm = max(counts)
print 'most common:'
print max_elm
cv2.imshow('img',img)
cv2.waitKey(0)
cv2.destroyAllWindows()
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