ERROR: Cannot uninstall 'numpy'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
screenshot(filename)Saves a screenshot of the current element to a PNG image file. ReturnsFalse if there is any IOError, else returns True. Use full paths in your filename.
Args:
filename: The full path you wish to save your screenshot to. This should end with a .png extension.
Usage:
element.screenshot(‘/Screenshots/foo.png’)
Max取得到 screenshot:
透過下面的python程式：
from PIL import Image,ImageDraw image = Image.open("captcha.png").convert("L")
取得convert 為灰階後影像檔：
透過下面程式，用來2分化影像：
def binarizing(img,threshold): #input: gray image
pixdata = img.load()
w, h = img.size
for y in range(h):
for x in range(w):
if pixdata[x, y] < threshold:
pixdata[x, y] = 0
else:
pixdata[x, y] = 255
return img
降噪方案1：（不好用）
def depoint(img): #input: gray image
pixdata = img.load()
w,h = img.size
for y in range(1,h-1):
for x in range(1,w-1):
count = 0
if pixdata[x,y-1] > 245:
count = count + 1
if pixdata[x,y+1] > 245:
count = count + 1
if pixdata[x-1,y] > 245:
count = count + 1
if pixdata[x+1,y] > 245:
count = count + 1
if count > 2:
pixdata[x,y] = 255
return img
似乎只有使用 上/下/左/右 4個方向 shift 1點來判斷，如果遇到較大的噪會無效，處理結果：
效果似乎接近無效，因為黑點都略大。
改服用下面的程式碼：
#二值判断,如果确认是噪声,用改点的上面一个点的灰度进行替换
#该函数也可以改成RGB判断的,具体看需求如何
def getPixel(image,x,y,G,N):
L = image.getpixel((x,y))
if L > G:
L = True
else:
L = False
nearDots = 0
if L == (image.getpixel((x - 1,y - 1)) > G):
nearDots += 1
if L == (image.getpixel((x - 1,y)) > G):
nearDots += 1
if L == (image.getpixel((x - 1,y + 1)) > G):
nearDots += 1
if L == (image.getpixel((x,y - 1)) > G):
nearDots += 1
if L == (image.getpixel((x,y + 1)) > G):
nearDots += 1
if L == (image.getpixel((x + 1,y - 1)) > G):
nearDots += 1
if L == (image.getpixel((x + 1,y)) > G):
nearDots += 1
if L == (image.getpixel((x + 1,y + 1)) > G):
nearDots += 1
if nearDots < N:
return image.getpixel((x,y-1))
else:
return None
# 降噪
# 根据一个点A的RGB值，与周围的8个点的RBG值比较，设定一个值N（0 <N <8），当A的RGB值与周围8个点的RGB相等数小于N时，此点为噪点
# G: Integer 图像二值化阀值
# N: Integer 降噪率 0 <N <8
# Z: Integer 降噪次数
# 输出
# 0：降噪成功
# 1：降噪失败
def clearNoise(image,G,N,Z):
draw = ImageDraw.Draw(image)
for i in range(0,Z):
for x in range(1,image.size[0] - 1):
for y in range(1,image.size[1] - 1):
color = getPixel(image,x,y,G,N)
if color != None:
draw.point((x,y),color)
image.save("test4_clearNoise.jpg")
image = Image.open("captcha.png").convert("L")
image_binary = binarizing(image, 180)
clearNoise(image_binary,50,4,6)
如何從點轉成面呢? 就是以圖像的每一點為中心，取周遭 N x N 格的點構成一個面(N 稱為 Kernel Size，N x N 的矩陣權重稱為『卷積核』)，每一格給予不同的權重，計算加權總和，當作這一點的 output，再移動至下一點以相同方式處理，至圖像的最後一點為止，這就是 CNN 的卷積層(Convolution Layer)。
