标签:filename gif 简单 pytho 算法 range img 比较 span
验证码多种多样,我这里提供的方法仅对有噪点的验证码进行识别有效。
首先,这是我准备的原始图片 4.png
具体的实现代码
import tesserocr
from PIL import Image, ImageDraw
import time
# image = Image.open("img/4_1.png")
# fh = open("img/1.txt", "w")
# w, h = image.size
# 图片转文本,测试用
# for i in range(h):
# for j in range(w):
# cl = image.getpixel((j, i))
# clall = cl[0] + cl[1] + cl[2]
# # clall == 0即当前像素为黑色
# if clall == 0:
# fh.write("0")
# else:
# fh.write("1")
# fh.write("\n")
# fh.close()
# 将图片转为黑白二色
def black_white(image):
w, h = image.size
for i in range(h):
for j in range(w):
cl = image.getpixel((j, i))
clall = cl[0] + cl[1] + cl[2]
# clall == 0即当前像素为黑色
if clall >= 155*3: # 根据具体的图片修改
image.putpixel((j, i), (255, 255, 255))
else:
image.putpixel((j, i), (0, 0, 0))
#二值数组
t2val = {}
def twoValue(image,G):
for y in range(0,image.size[1]):
for x in range(0,image.size[0]):
g = image.getpixel((x,y))
if g > G:
t2val[(x,y)] = 1
else:
t2val[(x,y)] = 0
# 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
def clearNoise(image,N,Z):
for i in range(0,Z):
t2val[(0,0)] = 1
t2val[(image.size[0] - 1,image.size[1] - 1)] = 1
for x in range(1,image.size[0] - 1):
for y in range(1,image.size[1] - 1):
nearDots = 0
L = t2val[(x,y)]
if L == t2val[(x - 1,y - 1)]:
nearDots += 1
if L == t2val[(x - 1,y)]:
nearDots += 1
if L == t2val[(x- 1,y + 1)]:
nearDots += 1
if L == t2val[(x,y - 1)]:
nearDots += 1
if L == t2val[(x,y + 1)]:
nearDots += 1
if L == t2val[(x + 1,y - 1)]:
nearDots += 1
if L == t2val[(x + 1,y)]:
nearDots += 1
if L == t2val[(x + 1,y + 1)]:
nearDots += 1
if nearDots < N:
t2val[(x,y)] = 1
def saveImage(filename,size):
image = Image.new("1",size)
draw = ImageDraw.Draw(image)
for x in range(0,size[0]):
for y in range(0,size[1]):
draw.point((x,y),t2val[(x,y)])
image.save(filename)
def start(img_path,save_img_path):
image = Image.open(img_path)
black_white(image)
image = image.convert("L")
twoValue(image,100)
clearNoise(image,4,1)
saveImage(save_img_path,image.size)
print(tesserocr.file_to_text(save_img_path))
img_path = "img/4.png"
save_img_path = "img/4_1.png"
start(img_path, save_img_path)
经过处理后得到以下图片 4_1.png
控制台输出结果
ziri
不过以上是在理想情况下的实现,对于某些图片的识别率不高
等后期加上一些算法提高识别率把。
标签:filename gif 简单 pytho 算法 range img 比较 span
原文地址:https://www.cnblogs.com/YLTzxzy/p/11331128.html