def getType(browser):
""" Identifying the graphic path """
ttype = ''
time.sleep(3.5)
im0 = Image.open(io.BytesIO(browser.get_screenshot_as_png()))
box = browser.find_element_by_id('patternCaptchaHolder')
im = im0.crop((int(box.location['x']) + 10, int(box.location['y']) + 100, int(box.location['x']) + box.size['width'] - 10, int(box.location['y']) + box.size['height'] - 10)).convert('L')
newBox = getExactly(im)
im = im.crop(newBox)
width = im.size[0]
height = im.size[1]
for png in ims.keys():
isGoingOn = True
for i in range(width):
for j in range(height):
if ((im.load()[i, j] >= 245 and ims[png][i][j] < 245) or (im.load()[i, j] < 245 and ims[png][i][j] >= 245)) and abs(ims[png][i][j] - im.load()[i, j]) > 10: # With 245 as the threshold, about 245 as the blank, less than 245 as the line; the difference between two pixels is about 10 to remove the error on the 245 boundary
isGoingOn = False
break
if isGoingOn is False:
ttype = ''
break
else:
ttype = png
else:
break
px0_x = box.location['x'] + 40 + newBox[0]
px1_y = box.location['y'] + 130 + newBox[1]
PIXELS.append((px0_x, px1_y))
PIXELS.append((px0_x + 100, px1_y))
PIXELS.append((px0_x, px1_y + 100))
PIXELS.append((px0_x + 100, px1_y + 100))
return ttype
def getType(browser):
""" 识别图形路径 """
ttype = ''
time.sleep(3.5)
im0 = Image.open(StringIO.StringIO(browser.get_screenshot_as_png()))
box = browser.find_element_by_id('patternCaptchaHolder')
im = im0.crop((int(box.location['x']) + 10, int(box.location['y']) + 100, int(box.location['x']) + box.size['width'] - 10, int(box.location['y']) + box.size['height'] - 10)).convert('L')
newBox = getExactly(im)
im = im.crop(newBox)
width = im.size[0]
height = im.size[1]
print '########### start ', time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(time.time()))
diff_dict = {}
for png in ims.keys():
for i in range(width):
for j in range(height):
# logging.info('im.load()[%s, %s] %s ims[%s][%s][%s] %s' % (i, j, im.load()[i, j], png,i, j, ims[png][i][j]))
# if ((im.load()[i, j] >= 245 and ims[png][i][j] < 245) or (im.load()[i, j] < 245 and ims[png][i][j] >= 245)) and abs(ims[png][i][j] - im.load()[i, j]) > 10: # 以245为临界值，大约245为空白，小于245为线条；两个像素之间的差大约10，是为了去除245边界上的误差
if im.load()[i, j] != ims[png][i][j]:
if png not in diff_dict.keys():
diff_dict[png] = 1
else:
diff_dict[png] += 1
print '########### end ', time.strftime('%Y-%m-%d %H:%M:%S',time.localtime(time.time()))
ttype = sorted(diff_dict.iteritems(), key = lambda x:x[1])[0][0]
px0_x = box.location['x'] + 40 + newBox[0]
px1_y = box.location['y'] + 130 + newBox[1]
PIXELS.append((px0_x, px1_y))
PIXELS.append((px0_x + 100, px1_y))
PIXELS.append((px0_x, px1_y + 100))
PIXELS.append((px0_x + 100, px1_y + 100))
print '#########################', ttype, diff_dict
return ttype
def getType(browser):
""" 识别图形路径 """
ttype = ''
time.sleep(3.5)
im0 = Image.open(io.BytesIO(browser.get_screenshot_as_png()))
try:
box = browser.find_element_by_id('patternCaptchaHolder')
except:
return ttype
im = im0.crop((int(box.location['x']) + 10, int(box.location['y']) + 100, int(box.location['x']) + box.size['width'] - 10, int(box.location['y']) + box.size['height'] - 10)).convert('L')
newBox = getExactly(im)
im = im.crop(newBox)
width = im.size[0]
height = im.size[1]
for png in ims.keys():
isGoingOn = True
for i in range(width):
for j in range(height):
if ((im.load()[i, j] >= 245 and ims[png][i][j] < 245) or (im.load()[i, j] < 245 and ims[png][i][j] >= 245)) and abs(ims[png][i][j] - im.load()[i, j]) > 10: # 以245为临界值，大约245为空白，小于245为线条；两个像素之间的差大约10，是为了去除245边界上的误差
isGoingOn = False
break
if isGoingOn is False:
ttype = ''
break
else:
ttype = png
else:
break
px0_x = box.location['x'] + 40 + newBox[0]
px1_y = box.location['y'] + 130 + newBox[1]
PIXELS.append((px0_x, px1_y))
PIXELS.append((px0_x + 100, px1_y))
PIXELS.append((px0_x, px1_y + 100))
PIXELS.append((px0_x + 100, px1_y + 100))
return ttype
def getType(browser):
""" 识别图形路径 """
ttype = ''
time.sleep(3.5)
im0 = Image.open(StringIO.StringIO(browser.get_screenshot_as_png()))
box = browser.find_element_by_id('patternCaptchaHolder')
im = im0.crop((int(box.location['x']) + 10, int(box.location['y']) + 100, int(box.location['x']) + box.size['width'] - 10, int(box.location['y']) + box.size['height'] - 10)).convert('L')
newBox = getExactly(im)
im = im.crop(newBox)
width = im.size[0]
height = im.size[1]
for png in ims.keys():
isGoingOn = True
for i in range(width):
for j in range(height):
if ((im.load()[i, j] >= 245 and ims[png][i][j] < 245) or (im.load()[i, j] < 245 and ims[png][i][j] >= 245)) and abs(ims[png][i][j] - im.load()[i, j]) > 10: # 以245为临界值，大约245为空白，小于245为线条；两个像素之间的差大约10，是为了去除245边界上的误差
isGoingOn = False
break
if isGoingOn is False:
ttype = ''
break
else:
ttype = png
else:
break
px0_x = box.location['x'] + 40 + newBox[0]
px1_y = box.location['y'] + 130 + newBox[1]
PIXELS.append((px0_x, px1_y))
PIXELS.append((px0_x + 100, px1_y))
PIXELS.append((px0_x, px1_y + 100))
PIXELS.append((px0_x + 100, px1_y + 100))
return ttype
def loadims_to_matrix():
for png in ims.keys():
piclist = []
#show_img(ims[png],""+str(png))
for i in range(160):
for j in range(160):
piclist.append(ims[png][i][j])
ims_dict[png] = np.array(piclist)
def getType(browser):
""" 识别图形路径 """
ttype = ''
time.sleep(3.5)
# im0 = Image.open(io.BytesIO(browser.get_screenshot_as_png()))
browser.save_screenshot("aa.png")
im0 = Image.open("aa.png")
box = browser.find_element_by_id('patternCaptchaHolder')#获取图形验证码对话框部分
# im = im0.crop((int(box.location['x']) + 10, int(box.location['y']) + 100, int(box.location['x']) + box.size['width'] - 10, int(box.location['y']) + box.size['height'] - 10)).convert('L')
im0.crop((int(box.location['x']) + 10, \
int(box.location['y']) + 100, \
int(box.location['x']) + box.size['width'] - 10, \
int(box.location['y']) + box.size['height'] - 10)).save("bb.png")#（left, upper, right, lower）
im = Image.open("bb.png").convert("L")#转换为灰色图像
im.save("cc.png")
newBox = getExactly(im)
im.crop(newBox).save("dd.png")
im = im.crop(newBox)
width = im.size[0]
height = im.size[1]
min_dist = sys.maxsize#python int类型支持的最大值
for png in ims.keys():
# isGoingOn = True
distance = 0
for i in range(width):
for j in range(height):
print("===========print(im.load()[i, j])============")
print(im.load()[i, j])
distance += numpy.square(im.load()[i, j] - ims[png][i][j])# numpy.square计算各元素的平方
if (distance != 0):
distance = numpy.sqrt(distance)#sqrt计算平方根
if (distance <= min_dist):
min_dist = distance
ttype = png
# for i in range(width):
# for j in range(height):
# if ((im.load()[i, j] >= 245 and ims[png][i][j] < 245) or (im.load()[i, j] < 245 and ims[png][i][j] >= 245)) and abs(ims[png][i][j] - im.load()[i, j]) > 10: # 以245为临界值，大约245为空白，小于245为线条；两个像素之间的差大约10，是为了去除245边界上的误差
# isGoingOn = False
# break
# if isGoingOn is False:
# ttype = ''
# break
# else:
# ttype = png
# else:
# break
px0_x = box.location['x'] + 40 + newBox[0]
px1_y = box.location['y'] + 130 + newBox[1]
PIXELS.append((px0_x, px1_y))
PIXELS.append((px0_x + 100, px1_y))
PIXELS.append((px0_x, px1_y + 100))
PIXELS.append((px0_x + 100, px1_y + 100))
print("------PIXELS--------")
print(PIXELS)
return ttype