Python achieved Wizard button (B) - FIG looking looking color

 

First, realize the function

　　Within the specified coordinate range is determined whether there is similarity of images is greater than n, and returns the coordinates.

Second, the basic idea

　　A = You need to find the picture

　　B = intercept of the current page in the specified range image

　　A position is determined using opencv B,

　　In this position A, taken with the same size image C in FIG.

　　Similarity contrast picture with the picture A, C

Third, to achieve snippets

　　1, install the required libraries

pip install opencv-python
pip install pywin32

　　2, the interception of specified coordinates Pictures

　　　　Parameter Description

　　　　filename: save filename

　　　　hwnd: Please find a way to get the window handle

　　　　pos: a position coordinate [x1, y1, x2, y2]. x1, y1 are the coordinates of the upper left corner, x2, y2 refers to the lower right corner coordinates.

　　　　This function can not return to the top level program screenshot.

def window_capture(filename,hwnd=0,pos=None):
    HWND = HWND   # numbered window number 0 indicates that the current active window 
    # acquired window handle the window according to the device context the DC (Divice the Context) 
    hwndDC = win32gui.GetWindowDC (HWND)
     # acquisition window according mfcDC the DC 
    mfcDC = win32ui.CreateDCFromHandle (hwndDC )
     # mfcDC create compatible DC 
    SaveDC = mfcDC.CreateCompatibleDC ()
     # create bigmap ready to save the picture 
    saveBitMap = win32ui.CreateBitmap ()
     # get monitor information 
    MoniterDev = win32api.EnumDisplayMonitors (None, None)
     IF POS == None:
        x1=0
        y1=0
        w = MoniterDev[0][2][2]
        h = MoniterDev[0][2][3]
    else:
        x1=pos[0]
        y1 = post [1 ]
        w=pos[2]-pos[0]
        H = POS [. 3] -POS [. 1 ]
     # Print W, image size H # 
    # of open space bitmap 
    saveBitMap.CreateCompatibleBitmap (mfcDC, MoniterDev [0] [2] [2], MoniterDev [0] [2] [3 ])
     # height saveDC, the screenshot is saved to saveBitmap 
    saveDC.SelectObject (saveBitMap)
     # taken image from the upper left corner (0,0) of length and width (w, h) of 
    saveDC.BitBlt ((x1, y1), (w , H), mfcDC, (X1, Y1), win32con.SRCCOPY) 
    saveBitMap.SaveBitmapFile (SaveDC, filename)

　　3, in the position A is determined using opencv B is

　　　　Parameter Description

　　　　target: cv2.imread ( " Picture B")

　　　　template: cv2.imread ( "Picture A")

DEF find_picture (target, Template):
     # obtained template image size Aspect 
    theight, TWIDTH template.shape = [: 2 ]
     # performing template matching, the match is in the cv2.TM_SQDIFF_NORMED 
    Result = cv2.matchTemplate (target, Template, CV2 .TM_SQDIFF_NORMED)
     # normalization process 
    cv2.normalize (Result, Result, 0,. 1, cv2.NORM_MINMAX, -1 )
     # maximum and minimum values match with an array (one-dimensional array as a vector, defined by Mat) of results and position 
    min_val, MAX_VAL, min_loc, max_loc = cv2.minMaxLoc (result)
     # match value to a string 
    # for cv2.TM_SQDIFF and cv2.TM_SQDIFF_NORMED methods and approaches 0 min_val the better the matching, the matching position taken min_loc 
    # for other methods max_val tends to 1, the better the match, the matching position taken max_loc 
    strmin_val =STR (MIN_VAL)
     # draw a bounding rectangle, the matching area marked out 
    # min_loc: Rectangular point 
    # (min_loc [0] + TWIDTH, min_loc [. 1] + theight): The width and height of rectangle 
    # (0,0,225): a rectangular frame color; 2: a rectangular border width 
    cv2.rectangle (target, min_loc, (min_loc [0] + TWIDTH, min_loc [. 1] + theight), (0,0,225), 2 )
     # display the results, and the value is displayed in the title match the bar 
    # cv2.imshow ( "a MatchResult ---- MatchingValue =" + strmin_val, target) 
    # cv2.waitKey () 
    # cv2.destroyAllWindows () 
    X = min_loc [0]
    The = min_loc [1 ]

    return X,Y

　　4, the return of the designated location specified coordinates specified picture

# Target original picture 
# X, Y start coordinate 
# W, H returned width to length 
DEF get_pic_from_pic (X, Y, W, H, target):
    region = target[y:y+h,x:x+w]
    retrun region

　　5, compare two pictures of similarity

DEF compare_picture (frame ImageA, frame ImageB):
     # grayscale images Compare 
    grayA = cv2.cvtColor (frame ImageA, cv2.COLOR_BGR2GRAY)
    grayB = cv2.cvtColor(imageB, cv2.COLOR_BGR2GRAY)

    (score, diff) = compare_ssim(grayA, grayB, full=True)return float(score)