Example #1
0
def hunt(imgx,typ ,db):
    global xtyp,tfile
    imgy = stdSize(imgx,typ)
    hcnt = 0
    xtyp = typ
    typex = {
                 #    lim   limh    ms     mx      dz   
             'wt' : [130.0,150.0,  450,    4000,   60],    
             'h2o': [ 60.0, 80.0,  300,    1500,   35],
             'fat': [  9.0, 15.0,  500,    3000,   45]   #300      
            }
   
    exlist = {
            'wt' :  [8, 2, 11  ],
            'h2o' : [2,  8   ],
            'fat' : [7,  2 ]
              }                             #  200 5 600  3000   works h20
    txlist = {
            'wt' :  [ 160, 140   ],
            'h2o' : [ 127 ,190, 160, 140 ],  #160, 140, 205 ],
            'fat' : [ 160, 190, 205 ]
             }
    lim  =  typex[typ][0]    #limt[0]
    limh =  typex[typ][1]
    ms =    typex[typ][2]
    mx =    typex[typ][3]
    dz =    typex[typ][4]
    #imgy.save(Gd)
    for iex in exlist[typ]:
        if db: print '-----rdNumber    ms', ms, ' mx',  mx #, imgy.area()

        if db: print( ['erode image',iex])
        for tx in txlist[typ]:
            #img = imgy.binarize(tx).invert()
            #img = imgy.erode(iex)
            img =  imgy.copy()
            cvs(db,img)
            hcnt = hcnt + 1
            # n is the pattern, rmx the max size, rms min size for iHunt logs
            n,rmx,rms = rdNumber(img,ex=iex, ms=ms   ,dz=dz , mx = mx ,tval=tx )
          
            if db: print '       Hunt 1 n ', hcnt,  n     #  exit here
            nn = 0; j = -1
            n.reverse()
            #nn = 100 * n[1] + 10 * n[2] + n[3] + n[4]/10.0
            if db :
                print 'n' ,n
                #cpause(['nreverse',n],Gd)
            for j, xin in  enumerate(n):
                nn = nn + xin * 10**(j-1)
            if (nn > lim) and nn < limh:
                iHunt.append((typ, hcnt, iex, tx, ms,rms, mx,rmx,  nn ))
                print 'hunt rtn' ,nn
                cvs(db,img,typ)
                return(nn)
            
                
             
    print '>>>>>>>>>>>>>>>>>hunt  ' ,typ, 'failed'
    return (0)                          #  eliminate hunt2 for now
Example #2
0
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
Example #3
0
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