还是直接代码吧(genIDCard.py),代码中有注释很容易读懂,原理跟验证码识别一样(tf20: CNN—识别字符验证码),都属于定长字符串识别,接下来也会介绍不定长数字串识别。
字体(fonts):here。
#!/usr/bin/env python2
# -*- coding: utf-8 -*-
"""
身份证文字+数字生成类
@author: liupeng
"""
import numpy as np
import freetype
import copy
import random
import cv2
class put_chinese_text(object):
def __init__(self, ttf):
self._face = freetype.Face(ttf)
def draw_text(self, image, pos, text, text_size, text_color):
'''
draw chinese(or not) text with ttf
:param image: image(numpy.ndarray) to draw text
:param pos: where to draw text
:param text: the context, for chinese should be unicode type
:param text_size: text size
:param text_color:text color
:return: image
'''
self._face.set_char_size(text_size * 64)
metrics = self._face.size
ascender = metrics.ascender/64.0
#descender = metrics.descender/64.0
#height = metrics.height/64.0
#linegap = height - ascender + descender
ypos = int(ascender)
if not isinstance(text, unicode):
text = text.decode('utf-8')
img = self.draw_string(image, pos[0], pos[1]+ypos, text, text_color)
return img
def draw_string(self, img, x_pos, y_pos, text, color):
'''
draw string
:param x_pos: text x-postion on img
:param y_pos: text y-postion on img
:param text: text (unicode)
:param color: text color
:return: image
'''
prev_char = 0
pen = freetype.Vector()
pen.x = x_pos << 6 # div 64
pen.y = y_pos << 6
hscale = 1.0
matrix = freetype.Matrix(int(hscale)*0x10000L, int(0.2*0x10000L),\
int(0.0*0x10000L), int(1.1*0x10000L))
cur_pen = freetype.Vector()
pen_translate = freetype.Vector()
image = copy.deepcopy(img)
for cur_char in text:
self._face.set_transform(matrix, pen_translate)
self._face.load_char(cur_char)
kerning = self._face.get_kerning(prev_char, cur_char)
pen.x += kerning.x
slot = self._face.glyph
bitmap = slot.bitmap
cur_pen.x = pen.x
cur_pen.y = pen.y - slot.bitmap_top * 64
self.draw_ft_bitmap(image, bitmap, cur_pen, color)
pen.x += slot.advance.x
prev_char = cur_char
return image
def draw_ft_bitmap(self, img, bitmap, pen, color):
'''
draw each char
:param bitmap: bitmap
:param pen: pen
:param color: pen color e.g.(0,0,255) - red
:return: image
'''
x_pos = pen.x >> 6
y_pos = pen.y >> 6
cols = bitmap.width
rows = bitmap.rows
glyph_pixels = bitmap.buffer
for row in range(rows):
for col in range(cols):
if glyph_pixels[row*cols + col] != 0:
img[y_pos + row][x_pos + col][0] = color[0]
img[y_pos + row][x_pos + col][1] = color[1]
img[y_pos + row][x_pos + col][2] = color[2]
class gen_id_card(object):
def __init__(self):
#self.words = open('AllWords.txt', 'r').read().split(' ')
self.number = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9']
self.char_set = self.number
#self.char_set = self.words + self.number
self.len = len(self.char_set)
self.max_size = 18
self.ft = put_chinese_text('fonts/OCR-B.ttf')
#随机生成字串,长度固定
#返回text,及对应的向量18*10
def random_text(self):
text = ''
vecs = np.zeros((self.max_size * self.len))
#size = random.randint(1, self.max_size)
size = self.max_size
for i in range(size):
c = random.choice(self.char_set)
vec = self.char2vec(c)
text = text + c
vecs[i*self.len:(i+1)*self.len] = np.copy(vec)
return text,vecs
#根据生成的text,生成image,返回标签和图片元素数据
def gen_image(self):
text,vec = self.random_text()
img = np.zeros([32,256,3])
color_ = (255,255,255) # Write
pos = (0, 0)
text_size = 21
image = self.ft.draw_text(img, pos, text, text_size, color_)
#仅返回单通道值,颜色对于汉字识别没有什么意义
return image[:,:,2],text,vec
#单字转向量
def char2vec(self, c):
vec = np.zeros((self.len))
for j in range(self.len):
if self.char_set[j] == c:
vec[j] = 1
return vec
#向量转文本
def vec2text(self, vecs):
text = ''
v_len = len(vecs)
for i in range(v_len):
if(vecs[i] == 1):
text = text + self.char_set[i % self.len]
return text
if __name__ == '__main__':
# 生成数字串
genObj = gen_id_card()
image_data,label,vec = genObj.gen_image()
cv2.imshow('image', image_data)
cv2.waitKey(0)
# 生成汉字串
line = '湖南省邵阳县'
img = np.zeros([300,300,3])
color_ = (255,255,255) # Green
pos = (3, 3)
text_size = 20
#ft = put_chinese_text('fonts/msyhbd.ttf')
ft = put_chinese_text('fonts/huawenxihei.ttf')
no = put_chinese_text('fonts/OCR-B.ttf')
image = ft.draw_text(img, pos, line, text_size, color_)
image1 = no.draw_text(image, (50,50), '1232142153253215', 20, (255,255,255))
cv2.imshow('ss', image)
cv2.imshow('image1', image1)
cv2.waitKey(0)