def rdWeight(imgx,typ,db):
img = stdSize(imgx,typ)
imgray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
ret,thresh = cv2.threshold(imgray,127,255,0)
img = thresh.copy()
cvs(1,img,'x')
y1 = 45; y2 = y1 + 322; x1 = 152; x2=200
wtx00 = img[y1:y2, x1:x2].copy()
w100 = tMatch(wtx00,typ,db) # search for a number
# cvs(1,wtx00,'y')
y1 = 45; y2 = y1 + 322; x1 = 240; x2=360
wtx01 = img[y1:y2, x1:x2].copy()
# cvs(1,wtx01,'y')
w010 = tMatch(wtx01,typ,db) # search for a number
y1 = 45; y2 = y1 + 322; x1 = 405; x2=535
wtx02 = img[y1:y2, x1:x2].copy()
cvs(0,wtx02,'yy')
w001 = tMatch(wtx02,typ,db)
y1 = 45; y2 = y1 + 322; x1 = 580; x2=720
wtx03 = img[y1:y2, x1:x2].copy()
cvs(0,wtx03,'yy')
wp1 = tMatch(wtx03,typ,db)
print w100, w010, w001, wp1
n = 100 * w100 + 10 * w010 + w001 + float(wp1 / 10.0)
print n
def rdTyp(imgx,typ,db):
'''rdTyp finds the screen area of a digit based on the x y co-ordinates
in the tables below. It passes this area to tMatch which returns
a number '''
img = stdSize(imgx,typ)
d = 150
#cvs(1,imgx,'rdTyp input')
hsv = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
# define range of blue color in HSV
h = 46; s = 20; v = 212
lower_blue = np.array([h,s,v]) #np.array([110,50,50])
upper_blue = np.array( [h+d,s+d,v+d]) #np.array([130,255,255])
# Threshold the HSV image to get only blue colors
thresh = cv2.inRange(hsv, lower_blue, upper_blue)
img = thresh.copy()
Y= {
# y1 y2 j limit
'wt' : [ 45, 367 , 4 ],
'fat': [ 84, 344 , 3 ],
'h2o': [ 35, 230 , 3 ]
}
XX = {
# 100 10 one tenth
'wt' : [(152, 200) , (240,360) , (415,530), (580,720) ],
'fat': [(20, 80) , (100,220) , (250,350), (0,0) ],
'h2o': [(10, 90) , (110,210) , (235,320), (0,0) ]
}
n = []
# look at each digit in the image by xx position
for j in range(0,Y[typ][2]): # loops across XX table above
y1 =Y[typ][0]; y2 = Y[typ][1];
x1 =XX[typ][j][0]; x2=XX[typ][j][1]
digit = img[y1:y2, x1:x2].copy()
cv2.imwrite('digTest.png',digit) # save for future debug
n.append( tMatch(digit,typ,db)) # interpret as a number
if db: print ' rdTyp n ', n # exit here
nn = 0; j = -1
n.reverse()
#nn = 100 * n[1] + 10 * n[2] + n[3] + n[4]/10.0
for j, xin in enumerate(n):
nn = nn + xin * 10**(j-1)
cvs(db,img,typ,5000)
return(nn) # the decoded number
def qnumb(grp,mask): # what number does this group encode??
'''
we count horizontal bars. The we create an encoding of the four
possible vertical bars upper left and right lower left and right
An 8 has three horizontal bars and all four vertical bars for an
encoding of 3 1 1 1 1.
'''
#xd = 999
global tfile
# mask = stdSize(mask,xtyp) #cv2.resize(img, (1040,410))
if not len(grp) > 0:
if db: ( 'zero len group. -- quitting')
return(0)
## x,y, w, h = boundsBlob(grp)
## #w = 110; h = 300 # nasty hack w and h
## tmsk = mask[y:y+h , x:x+w].copy()
## pxls = tMatch(tmsk,xtyp,db) # search for a number
## print 'number is',pxls
## cvs(db,tmsk,'tmsk')
## return(pxls)
xll =0; xlh=0; xrl=0; xrh = 0 # pixel counts
v=0 ; h=0; # pixel groups
x, y, wg, hg = boundsBlob(grp)
for b in grp:
bx,by,bw,bh = cv2.boundingRect(b)
if bh < 1.1 * bw:
h = h + 1 # add to the horizontal count
else: #v
v = v + 1
if (bx < wg/2 + x) : # if left side
if (by > hg/2 + y): # if low
xll = 1 # count vertical left low
else:
xlh = 1 # high
else: # must be right side
if (by > hg/2 + y): # so if low
xrl = 1 # count vertical right low
else:
xrh = 1 # else high
#if db: print( 'p so far is h {} v {} xll {} xlh {} xrl {} xrh {}'
# .format(h, v, xll, xlh, xrl, xrh) )
p = h * 10000 + xll * 1000 + xlh * 100 + xrl * 10 + xrh
''' ptrn translates the results of the pattern analysis into numbers '''
ptrn = {
1100: 1, #
31001: 2,
30011: 3,
10111: 4,
30110: 5,
31110: 6,
10011: 7, #?
11001: 7,
31111: 8,
30111: 9,
21111: 0
}
if p in ptrn: # HOO RAY we found a digit
if db: print '>>>>>>found a {} {} '.format( ptrn[p] , p)
writeNumb(ptrn[p],grp,mask) # keep the mask image for future use
return ptrn[p]
else: # we don't seem to have a number
print '<<<<<<<qptrn - pattern problem p is >{}<'.format( p)
#return('p')
x,y, w, h = boundsBlob(grp)
w = 110; h = 300 # nasty hack w and h
tmsk = mask[y:y+h , x:x+w].copy()
pxls = tMatch(tmsk,xtyp,db) # search for a number
print 'number is',pxls
cvs(db,tmsk,'tmsk')
return(pxls)