def rdNumber(img, tval=160, ex=2, ms=1.0,mx=3, dz = 60):
'''
analyse the img and pass a likely set of features to qnumb for
interpretation
'''
global db, tfile
fz = 0; h= 0; v = 0;
tgrp = [] ;numb = []
dx = dz
print '-----rdNumber tval',tval,' ex',ex,'ms', ms, 'mxsize', mx
fs,mask = findBlobs(img, ms, mx ,ex, db,tval=tval )
if not fs:
if db: print ' no features found'
cvs(db,img,'nothing in rdnumbr')
return ([0,0,0,0],0,0)
else:
# fs = sorted(fs, key = lambda cnt: tuple(cnt[cnt[:,:,0].argmin()][0]))
fs = sorted(fs, key = lambda cnt:cv2.contourArea(cnt))
cv2.drawContours( img, fs, -1, (0, 0, 255), 5 )
rmx = cv2.contourArea(fs[0]) # left most area
rmn = rmx
fz = 0
fs = sorted(fs, key = lambda cnt: tuple(cnt[cnt[:,:,0].argmin()][0]))
# sorted left to right
for ix, f in enumerate( fs):
x,y,w,h = cv2.boundingRect(f)
#fx = x
if cv2.contourArea(f) < rmn: rmn = cv2.contourArea(f)
if cv2.contourArea(f) > rmx: rmx = cv2.contourArea(f)
xd = x - fz # xd is horizontal dist between blobs
if xd > dx: # dx is parm here is where the number is detected
numb.append(qnumb(tgrp,mask)) #,mask,img)) # process the number
tnumb(tgrp,img) # black rectangle and training output
tgrp = [] # start a new group
if db: print 'ix {} w {} h {} dx {} xd {} area {}'\
.format(ix,w,h,dx,xd,cv2.contourArea(f))
tgrp.append(f)
## cv2.drawContours( img, [f], 0, (0, 255, 255), 5 )
## cvs(db,img)
fz = x
numb.append(qnumb(tgrp,mask)) #,mask,img)) # process the last group
tnumb(tgrp,img )
print 'last numb', numb
tpat = numb
if all(i == 'p' for i in tpat):
return([0,0,0,0],rmx,rmn) # nfg return True zero
if len(tpat)>3:
while tpat[-1] == 'p':
tpat.pop()
while( tpat[0] == 'p'):
tpat.pop(0)
# if db: cpause(['end rd',tpat],Gd)
if 'p' in tpat:
return([0,0,0,0],rmx,rmn) # nfg return True zero
else:
return(tpat,rmx,rmn) # maybe good numeric value
cv2.createTrackbar('min','image',0,100,nothing)
cv2.createTrackbar('max','image',0,1000,nothing)
cv2.createTrackbar('tval','image',0,255,nothing)
cv2.createTrackbar('erd','image',0,20,nothing)
while(1):
cv2.imshow('image',imgx)
k = cv2.waitKey(1) & 0xFF
if k == 27:
cvd()
break
if k == ord('s'):
fil = "img3c.png"
fil = 'fatTest.png'
db = False
img = cv2.imread(fil)
blobs = findBlobs(img,ms,mx,erd,db,tval) # 500 3000 2 160
if blobs is not None :
print '{} blobs found '.format(len(blobs))
for i,f in enumerate (blobs):
if i > 20: break
cv2.drawContours(img,[f],0,(0,0,0),2)
cvs(0,img,'contours')
else: print 'no blobs found',
ms = cv2.getTrackbarPos('min','image')
mx = cv2.getTrackbarPos('max','image')
erd = cv2.getTrackbarPos('erd','image')
tval = cv2.getTrackbarPos('tval','image')
cv2.destroyAllWindows()
