def gen(batch_size=32):
X = np.zeros((batch_size, height, width, 3), dtype=np.uint8)
y = [np.zeros((batch_size, n_class), dtype=np.uint8) for i in range(n_len)]
generator = ImageCaptcha(width=width, height=height)
while True:
for i in range(batch_size):
random_str = ''.join([random.choice(characters) for j in range(4)])
X[i] = generator.generate_image(random_str)
for j, ch in enumerate(random_str):
y[j][i, :] = 0
y[j][i, characters.find(ch)] = 1
yield X, y
def random_img(captcha_len=4, img_w=width, img_h=height):
"""
利用ImageCaptcha库生成随机验证码图片
:param img_h:
:param img_w:
:param captcha_len: 验证码长度
:return: 验证码图片和内容
"""
generator = ImageCaptcha(width=img_w,
height=img_h,
fonts=[os.path.join(file_path, 'kongxin.ttf')])
# generator = ImageCaptcha(width=img_w, height=img_h)
random_str = ''.join([random.choice(alphabet) for j in range(captcha_len)])
captchas = random_str
img = generator.generate_image(random_str)
return img, captchas
def gen123():
batch_size = 32
X = np.zeros((batch_size, height, width, 3), dtype=np.uint8)
y = [np.zeros((batch_size, n_class), dtype=np.uint8) for i in range(n_len)]
generator = ImageCaptcha(width=width, height=height)
while True:
for i in range(batch_size):
# 生产随机字符
random_str = ''.join([random.choice(characters) for j in range(4)])
# 生产图片
X[i] = generator.generate_image(random_str)
# 把Y设置成4个列表
for j, ch in enumerate(random_str):
y[j][i, :] = 0
y[j][i, characters.find(ch)] = 1
yield X, y
def captcha():
letters = string.ascii_uppercase
length = random.randint(4, 5)
global captcha_text
global captcha_img
captcha_text = ''.join(random.choice(letters) for i in range(length))
img = ImageCaptcha(width=160, height=60, fonts=None, font_sizes=None)
image = img.generate_image(captcha_text)
image.save('captcha.jpg')
open_image = Image.open("captcha.jpg")
photo = ImageTk.PhotoImage(open_image)
captcha_img = tk.Label(image=photo)
captcha_img.image = photo
captcha_img.pack()
captcha_img.place(y=120, x=100)
def gen_captcha(self,batch_size = 50):
X = np.zeros([batch_size,self.height,self.width,1])
img = np.zeros((self.height,self.width),dtype=np.uint8)
Y = np.zeros([batch_size,self.char_num,self.classes])
image = ImageCaptcha(width = self.width,height = self.height)
while True:
for i in range(batch_size):
captcha_str = ''.join(random.sample(self.characters,self.char_num))
img = image.generate_image(captcha_str).convert('L')
img = np.array(img.getdata())
X[i] = np.reshape(img,[self.height,self.width,1])/255.0
for j,ch in enumerate(captcha_str):
Y[i,j,self.characters.find(ch)] = 1
Y = np.reshape(Y,(batch_size,self.char_num*self.classes))
yield X,Y
def gen(batch_size=128):
X = np.zeros((batch_size, width, height, 3), dtype=np.uint8)
y = np.zeros((batch_size, n_len), dtype=np.uint8)
generator = ImageCaptcha(width=width, height=height)
while True:
for i in range(batch_size):
random_str = ''.join(
[random.choice(characters) for j in range(n_len)])
X[i] = np.array(generator.generate_image(random_str)).transpose(
1, 0, 2)
y[i] = [characters.find(x) for x in random_str]
yield [
X, y,
np.ones(batch_size) * rnn_length,
np.ones(batch_size) * n_len
], np.ones(batch_size)
def gen_sample(height=80, width=170, batch_size=1, n_class=36):
print("生成样本")
X = np.zeros((batch_size, height, width, 3), dtype=np.float)
Y = [np.zeros((batch_size, n_class), dtype=np.uint8) for i in range(4)]
# 生成器
generator = ImageCaptcha(height=height, width=width)
while 1:
for i in range(batch_size):
code, raw, = random_code()
generate_code = generator.generate_image(code)
X[i] = np.array(generate_code).astype('float32') / 255
for j, ch in enumerate(code):
Y[j][i, :0] = 0
Y[j][i, raw.find(ch)] = 1
yield X, Y, raw, generate_code, code
def gen(batch_size=32):
X = np.zeros((batch_size, HEIGHT, WIDTH, 3), dtype=np.uint8)
Y = [
np.zeros((batch_size, N_CLASS), dtype=np.uint8)
for i in range(N_LENGTH)
]
generator = ImageCaptcha(width=WIDTH, height=HEIGHT)
while True:
for i in range(batch_size):
random_str = "".join(
[random.choice(characters) for k in range(N_LENGTH)])
X[i] = generator.generate_image(random_str)
for j, ch in enumerate(random_str):
Y[j][i, :] = 0
Y[j][i, characters.find(ch)] = 1
yield X, Y
def gen_code(batch_size=32):
X = np.zeros((batch_size, height * 4, width * 4, 3), dtype=np.uint8)
y = [np.zeros((batch_size, n_class), dtype=np.uint8) for i in range(n_len)]
generator = ImageCaptcha(width=width, height=height)
while True:
for i in range(batch_size):
random_str = ''.join(
[random.choice(characters) for j in range(n_len)])
img = generator.generate_image(random_str)
img = Image__.fromarray(
cv2.resize(np.asarray(img), (width * 4, height * 4)))
X[i] = img
for j, ch in enumerate(random_str):
y[j][i, :] = 0
y[j][i, characters.find(ch)] = 1
yield np.array(X), y
def gen(batch_size=128):
X = np.zeros((batch_size, height, width, 3), dtype=np.uint8)
y = np.zeros((batch_size, n_len), dtype=np.uint8)
while True:
generator = ImageCaptcha(width=width, height=height)
for i in range(batch_size):
random_str = ''.join([random.choice(characters) for j in range(4)])
X[i] = np.array(generator.generate_image(random_str))
# X[i]=np.transpose(X[i],(2,1,0))
# 长n_len 下标表示
y[i] = [characters.find(x) for x in random_str]
yield [
X.transpose((0, 3, 2, 1)), y,
np.ones(batch_size) * int(conv_shape[1] - 2),
np.ones(batch_size) * n_len
], np.ones(batch_size)
def gen(height=gConfig['hight'],
width=gConfig['width'],
batch_size=1,
nclass=gConfig['num_datasetclasses']):
X = np.zeros((batch_size, height, width, 3), dtype=np.float)
y = [np.zeros((batch_size, nclass), dtype='uint8') for i in range(4)]
generator = ImageCaptcha(height=height, width=width)
while True:
for i in range(batch_size):
random_str, raw = randomCode()
genCode = generator.generate_image(random_str)
X[i] = np.array(genCode).astype('float32') / 255.
for j, ch in enumerate(random_str):
y[j][i, :] = 0
y[j][i, raw.find(ch)] = 1
yield X, y, raw, genCode, random_str
def main():
dirs = [TRAIN_DIR, VAL_DIR]
for d in dirs:
if not os.path.exists(d):
os.mkdir(d)
if d == TRAIN_DIR:
step = 10000
else:
step = 1000
for ns in range(step):
file_name = create()
img = ImageCaptcha(width=IMG_WIDTH, height=IMG_HEIGHT)
image = img.generate_image(file_name)
image.save(f'{d}/{file_name}_1.png')
def gen(batch_size=32): # X=np.zeros((batch_size,height,width,3),dtype=np.uint8) # one-hot y=[np.zeros((batch_size,n_class),dtype=np.uint8) for i in range(n_len)] generator=ImageCaptcha(width=width,height=height) while True: for i in range(batch_size): random_str=''.join([random.choice(characters) for j in range(n_len)]) X[i]=generator.generate_image(random_str) for j,ch in enumerate(random_str): y[j][i,:]=0 y[j][i,characters.find(ch)]=1 # 将图片输入转为th格式输入 # X=np.transpose(X,(0,3,1,2)) yield np.transpose(X,(0,3,1,2)),y
def gen_captcha(self,batch_size = 50):
X = np.zeros([batch_size,self.height,self.width,1])
img = np.zeros((self.height,self.width),dtype=np.uint8)
Y = np.zeros([batch_size,self.char_num,self.classes])
image = ImageCaptcha(width = self.width,height = self.height)
while True:
for i in range(batch_size):
captcha_str = ''.join(random.sample(self.characters,self.char_num))
img = image.generate_image(captcha_str).convert('L') #转灰度
img = np.array(img.getdata())
X[i] = np.reshape(img,[self.height,self.width,1])/255.0 #归一化[60,160,1]
for j,ch in enumerate(captcha_str):
Y[i,j,self.characters.find(ch)] = 1
Y = np.reshape(Y,(batch_size,self.char_num*self.classes))
yield X,Y
def gen_image():
image_width = 100
image_height = 60
origin_dir = './images/origin/'
char_set = ['1', '2', '3', '4', '5', '6', '7', '8', '9']
char_set_len = len(char_set)
captcha_len = 4
generator = ImageCaptcha(width=100, height=60, fonts=['images/captcha.ttf'])
for i in range(20000):
print("正在生成第%d张图片"%(i + 1))
random_str = ''.join(random.choice(char_set) for i in range(captcha_len))
random_num = random.randint(10000,99999)
img = generator.generate_image(random_str)
file_name = random_str + "_" + str(random_num) + ".jpg"
img.save(origin_dir + file_name)
print("ok")
def gen(batch_size=32):
X = np.zeros((batch_size, height, width, 3), dtype=np.uint8)
y = np.zeros((batch_size, n_len * n_class), dtype=np.uint8)
generator = ImageCaptcha(width=width, height=height)
while True:
for i in range(batch_size):
random_str = ''.join([random.choice(characters) for j in range(4)])
X[i] = generator.generate_image(random_str)
for j, c in enumerate(random_str):
index = j * n_class + CAPTCHA_LIST.index(c)
y[i][index] = 1
# for j, ch in enumerate(random_str):
# y[i]
# y[j][i, :] = 0
# y[j][i, characters.find(ch)] = 1
yield X, y
def generate_image_sets_for_multi_digits(nb_sample=SAMPLE_SIZE, fonts=None):
captcha = ImageCaptcha(fonts=fonts) if fonts else ImageCaptcha()
# print DIGIT_FORMAT_STR
labels = []
images = []
for i in range(0, nb_sample):
digits = 0
last_digit = INVALID_DIGIT
for j in range(0, DIGIT_COUNT):
digit = last_digit
while digit == last_digit:
digit = random.randint(0, 9)
last_digit = digit
digits = digits * 10 + digit
digits_as_str = DIGIT_FORMAT_STR % digits
labels.append(digits_as_str)
images.append(captcha.generate_image(digits_as_str))
digit_labels = np.empty((nb_sample, DIGIT_COUNT), dtype="int8")
shape = (nb_sample, RGB_COLOR_COUNT, IMAGE_STD_HEIGHT,
IMAGE_STD_WIDTH) if IS_TH else (nb_sample, IMAGE_STD_HEIGHT,
IMAGE_STD_WIDTH, RGB_COLOR_COUNT)
digit_image_data = np.empty(shape, dtype="float32")
for index in range(0, nb_sample):
img = images[index].resize((IMAGE_STD_WIDTH, IMAGE_STD_HEIGHT),
PIL.Image.LANCZOS)
# if index < SHOW_SAMPLE_SIZE:
# display.display(img)
img_arr = np.asarray(img, dtype="float32") / 255.0
if IS_TH:
digit_image_data[index, :, :, :] = np.rollaxis(img_arr, 2)
else:
digit_image_data[index, :, :, :] = img_arr
for digit_index in range(0, DIGIT_COUNT):
digit_labels[index][digit_index] = labels[index][digit_index]
x, y_as_num = digit_image_data, np.rollaxis(digit_labels, 1)
y = {(OUT_PUT_NAME_FORMAT % i):
np_utils.to_categorical(y_as_num[i], CLASS_COUNT)
for i in range(0, DIGIT_COUNT)}
return x, y
def generateVerificationCode(self, len=4):
''' 随机生成4位的验证码 '''
list_code = []
for i in range(10): # 0-9数字
list_code.append(str(i))
for i in range(65, 91): # 对应从“A”到“Z”的ASCII码
list_code.append(chr(i))
for i in range(97, 123): #对应从“a”到“z”的ASCII码
list_code.append(chr(i))
slice = random.sample(list_code, len) # 从list中随机获取4个元素，作为一个验证码返回
verification_code = ''.join(slice) # list to str
img = ImageCaptcha()
image_code = img.generate_image(verification_code)
pixmap_image_code = image_code.toqpixmap()
return verification_code, pixmap_image_code
def gen_test_captcha(self):
image = ImageCaptcha(width=self.width, height=self.height)
captcha_str = ''.join(random.sample(self.characters, self.char_num))
img = image.generate_image(captcha_str)
# 生成测试数据并保存
img.save(captcha_str + '.jpg')
# X：其 shape 为 [ 1, height, width, 1 ]，1 表示每批次多少个训练数据，height ,width 表示验证码图片的高和宽，1 表示这是1个通道的黑白图片。
# Y：X 中每个训练数据属于哪一类验证码，其形状为 [ 1, class ] ，对验证码中每个字符进行 One-Hot 编码，所以 class 大小为 4*62
X = np.zeros([1, self.height, self.width, 1])
Y = np.zeros([1, self.char_num, self.classes])
img = img.convert('L')
img = np.array(img.getdata())
X[0] = np.reshape(img, [self.height, self.width, 1]) / 255.0
for j, ch in enumerate(captcha_str):
Y[0, j, self.characters.find(ch)] = 1
Y = np.reshape(Y, (1, self.char_num * self.classes))
return X, Y
def generate_test_data(batch_size):
img_generator = ImageCaptcha()
while True:
test_labels_batch = []
test_imgs_batch = []
length = random.randint(4, 7)
for _ in range(batch_size):
char = ''.join([random.choice(chars) for _ in range(length)])
img = img_generator.generate_image(char)
img = np.asarray(img)
test_labels_batch.append(char)
h = 32
w = int(img.shape[1] * 32 / img.shape[0])
img_gray = cv2.cvtColor(cv2.resize(img, (w, h)),
cv2.COLOR_BGR2GRAY)
test_imgs_batch.append(img_gray)
yield ([np.array(test_imgs_batch), np.array(test_labels_batch)])
class CaptchaSequence(Sequence):
def __init__(self,
batch_size,
steps,
width=160,
height=60,
n_capt=4,
include_char=False):
"""
:param batch_size: batch size
:param steps: step nums
:param width: the width of captcha image
:param height: the height of captcha image
:param n_capt: captcha length, Default is 4
:param include_char: whether including english character. Default is False
"""
self.batch_size = batch_size
self.steps = steps
self.width = width
self.height = height
self.n_capt = n_capt
self.include_char = include_char
self.generator = ImageCaptcha(width=self.width, height=self.height)
self.characters = get_captcha_str_map(include_char=include_char)
self.n_char = len(self.characters) # character type num
def __len__(self):
return self.steps
def __getitem__(self, index):
X = np.zeros((self.batch_size, self.height, self.width, 3),
dtype=np.float32)
Y = [
np.zeros((self.batch_size, self.n_char), dtype=np.uint8)
for _i in range(self.n_capt)
]
for _i in range(self.batch_size):
captcha_string = random_captcha_string(
length=self.n_capt, include_char=self.include_char)
X[_i] = np.array(
self.generator.generate_image(captcha_string)) / 255.0
for _j, ch in enumerate(captcha_string):
Y[_j][_i, self.characters.find(ch)] = 1
return X, Y
def gen_training_data(output_dir, num_samples):
min_chars = 4
max_chars = 5
char_set = string.ascii_letters + string.digits
image_gen = ImageCaptcha()
for n in range(num_samples):
captcha_length = random.choice(range(min_chars, max_chars + 1))
captcha_text = ''
for c in range(captcha_length):
captcha_text += random.choice(char_set)
gen_result = image_gen.generate_image(captcha_text, for_training=True)
target = gen_result["final"]
target.save(os.path.join(output_dir, f'{captcha_text}.png'))
label = []
for c, char_img in enumerate(gen_result["char_onlys"]):
left = -1
right = -1
top = -1
bottom = -1
for x in range(char_img.width):
for y in range(char_img.height):
if char_img.getpixel((x, y)) != (255, 255, 255):
if left == -1:
left = x
if x > right:
right = x
if top == -1 or top > y:
top = y
if y > bottom:
bottom = y
label.append({
'left': left,
'right': right,
'top': top,
'bottom': bottom
})
with open(os.path.join(output_dir, f'{captcha_text}.json'), 'w') as f:
json.dump(label, f)
def gen(batch_size=32):
X = np.zeros((batch_size, height, width, 3), dtype=np.uint8)
y = [np.zeros((batch_size, n_class), dtype=np.uint8) for i in range(n_len)]
generator = ImageCaptcha(width=width, height=height)
while True:
for i in range(batch_size):
random_str_len = random.randint(4, 6)
random_str = ''.join(
[random.choice(characters) for j in range(random_str_len)])
X[i] = generator.generate_image(random_str)
if random_str_len < n_len:
for k in range(n_len - random_str_len):
random_str += ' '
for j, ch in enumerate(random_str):
y[j][i, :] = 0
y[j][i, characters.find(ch)] = 1
yield X, y
def capImage(self, captcha_text):
image_captcha = ImageCaptcha()
# Create the captcha image.
image = image_captcha.generate_image(captcha_text)
# Add noise curve for the image.
image_captcha.create_noise_curve(image, image.getcolors())
# Add noise dots for the image.
image_captcha.create_noise_dots(image, image.getcolors())
# Save the image to a png file.
image_file = "./captcha_" + captcha_text + ".png"
image_captcha.write(captcha_text, image_file)
# Display the image in a matplotlib viewer.
plt.imshow(image)
plt.show()
def gen(batch_size=32):
X = np.zeros(
(batch_size, height, width, 3), dtype=np.uint8
) # X 的形状是 (batch_size, height, width, 3)，比如一批生成32个样本，图片宽度为170，高度为80，那么形状就是 (32, 80, 170, 3)，取第一张图就是 X[0]。
y = [
np.zeros((batch_size, n_class), dtype=np.uint8) for i in range(n_len)
] # y 的形状是四个 (batch_size, n_class)，如果转换成 numpy 的格式，则是 (n_len, batch_size, n_class)，比如一批生成32个样本，验证码的字符有36种，长度是4位，那么它的形状就是4个 (32, 36)，也可以说是 (4, 32, 36)
generator = ImageCaptcha(width=width, height=height)
while True:
for i in range(batch_size):
random_str = ''.join(
[random.choice(characters) for j in range(n_len)])
img = generator.generate_image(random_str)
X[i] = img
for j, ch in enumerate(random_str):
y[j][i, :] = 0
y[j][i, characters.find(ch)] = 1
yield X, y
async def generate_captcha(user):
letters = "0123456789abcdefghijklmnopqrstuvwxyz?!()@"
captcha_answer=''.join(random.choice(letters) for i in range(config.FAUCET_CAPTCHALENGTH))
image_captcha = ImageCaptcha()
captcha_image_file_name = os.getcwd()+"\\faucet_images\\"+str(user.id)+"_captcha_image.png"
image = image_captcha.generate_image(captcha_answer)
arr=BytesIO()
image.save(arr, format='png',optimize=True)
arr.seek(0)
await user.send(file=discord.File(arr, "captcha.png"))
return captcha_answer
def generate_image_sets_for_single_digit(nb_sample=SAMPLE_SIZE, single_digit_index=0, fonts=None):
captcha = ImageCaptcha(fonts=fonts) if fonts else ImageCaptcha()
# print DIGIT_FORMAT_STR
labels = []
images = []
for i in range(0, nb_sample):
digits = 0
last_digit = INVALID_DIGIT
for j in range(0, DIGIT_COUNT):
digit = last_digit
while digit == last_digit:
digit = random.randint(0, 9)
last_digit = digit
digits = digits * 10 + digit
digits_as_str = DIGIT_FORMAT_STR % digits
labels.append(digits_as_str)
images.append(captcha.generate_image(digits_as_str))
digit_labels = list()
for digit_index in range(0, DIGIT_COUNT):
digit_labels.append(np.empty(nb_sample, dtype="int8"))
shape = (nb_sample, RGB_COLOR_COUNT, IMAGE_STD_HEIGHT, IMAGE_STD_WIDTH) if IS_TH else (nb_sample, IMAGE_STD_HEIGHT, IMAGE_STD_WIDTH, RGB_COLOR_COUNT)
digit_image_data = np.empty(shape, dtype="float32")
for index in range(0, nb_sample):
img = images[index].resize((IMAGE_STD_WIDTH, IMAGE_STD_HEIGHT), PIL.Image.LANCZOS)
# if index < SHOW_SAMPLE_SIZE:
# display.display(img)
img_arr = np.asarray(img, dtype="float32") / 255.0
if IS_TH:
digit_image_data[index, :, :, :] = np.rollaxis(img_arr, 2)
else:
digit_image_data[index, :, :, :] = img_arr
for digit_index in range(0, DIGIT_COUNT):
digit_labels[digit_index][index] = labels[index][digit_index]
x = digit_image_data
y = np_utils.to_categorical(digit_labels[single_digit_index], CLASS_COUNT)
return x, y
def captcha_img(width=160, height=60, font_sizes=(50, 55, 60), fonts=None):
captcha_len = 5
#captcha_range = string.digits + string.ascii_letters #大小写+数字
captcha_range = string.ascii_lowercase
captcha_range_len = len(captcha_range)
captcha_text = ""
for i in range(captcha_len):
captcha_text += captcha_range[randint(0, captcha_range_len - 1)]
img = ImageCaptcha(width=width, height=height, font_sizes=font_sizes)
image = img.generate_image(captcha_text)
#save to bytes
bytes_image = BytesIO()
image.save(bytes_image, format='png')
bytes_image = bytes_image.getvalue()
return bytes_image, captcha_text
def gen(batch_size=32):
'''
一批的数量:32
:param batch_size:
:return:
'''
X = np.zeros((batch_size, height, width, 3), dtype=np.uint8) # 无符号整数64位
y = [
np.zeros((batch_size, n_class), dtype=np.uint8) for i in range(n_len)
] # 一个长度为4的列表，每个元素是一个二维张量
generator = ImageCaptcha(width=width, height=height)
while True:
for i in range(batch_size):
random_str = ''.join([random.choice(characters) for j in range(4)])
X[i] = generator.generate_image(random_str)
for j, ch in enumerate(random_str):
y[j][i, :] = 0
y[j][i, characters.find(ch)] = 1
yield X, y
def data_generator(times=100, batch_size=32):
generator = ImageCaptcha(width=width, height=height)
for _ in range(times):
X = np.zeros((batch_size, height, width, 3), dtype=np.uint8)
XX = np.zeros((batch_size, 3, height, width), dtype=np.uint8)
y = np.zeros((batch_size, n_len, n_class), dtype=np.uint8)
yy = np.zeros((batch_size, 4), dtype=np.uint8)
s = []
for i in range(batch_size):
random_str = ''.join(
[random.choice(characters) for j in range(n_len)])
X[i] = generator.generate_image(random_str)
XX[i] = np.transpose(X[i], (2, 0, 1))
s.append(random_str)
for j, ch in enumerate(random_str):
y[i][j][characters.find(ch)] = 1
yy[i][j] = characters.find(ch)
yield torch.from_numpy(XX).float(), torch.from_numpy(y).float()
def main(app_args):
"""
Main application.
"""
if os.path.exists(app_args.out_path):
shutil.rmtree(app_args.out_path)
os.makedirs(app_args.out_path)
fonts = []
for file in os.listdir("fonts"):
if file.endswith(".ttf"):
fonts.append(os.path.join(app_args.fonts_dir, file))
image_captcha_gen = ImageCaptcha(fonts=fonts,
height=app_args.image_height,
width=app_args.image_width)
for i in xrange(app_args.files_count):
samples = []
labels = []
for k in xrange(app_args.file_size):
captcha_text = random.sample(ALPHABET, app_args.captcha_size)
data = image_captcha_gen.generate_image(captcha_text)
captcha = np.array(data)
captcha = cv2.resize(captcha,
(app_args.image_width, app_args.image_height))
label = _get_label(captcha_text)
labels.append(label)
samples.append(captcha)
if k % 1000 == 0:
print("Generated: %d" % k)
samples = np.array(samples)
labels = np.array(labels)
labels = labels.astype(np.int32)
cur_file_name = "%d_set.hdf5" % i
cur_hdf5 = h5py.File(os.path.join(app_args.out_path, cur_file_name),
"w")
cur_hdf5.create_dataset("data", data=samples)
cur_hdf5.create_dataset("labels", data=labels)
cur_hdf5.close()
print("Write %s" % cur_file_name)
def get_randm_image(target_str, random_flag):
'''
生成单幅的验证码图片
:param target_str: 要生成的验证码对应的字符串
:param random_flag: 是否使用随机模式生成验证码 为True是 target_str参数无效
:return: 返回验证码图片
'''
width, height, n_len, n_class = 170, 80, 4, len(characters)
generator = ImageCaptcha(width=width, height=height)
if not random_flag:
random_str = target_str
else:
random_str = ''.join([random.choice(characters) for j in range(n_len)])
img = generator.generate_image(random_str)
plt.imshow(img)
plt.title(random_str)
plt.show()
return img
def main():
width, height = 170, 80
generator = ImageCaptcha(width=width, height=height)
img = generator.generate_image("AAAA")
img.save("ABCD.png")
characters = string.digits + string.ascii_uppercase
#读取model
model = model_from_json(open('model.json').read())
model = model.load_weights_from_hdf5_group('model.h5')
image = cv2.imread("./ABCD.png")
X = np.zeros((1, height, width, 3), dtype=np.uint8)
X[0] = image
y_pred = model.predict(X)
result = decode(y_pred, characters)
print(result)
def generate_image_sets_for_multi_digits(nb_sample=SAMPLE_SIZE):
captcha = ImageCaptcha()
labels = []
images = []
for i in range(0, nb_sample):
digits = 0
last_digit = INVALID_DIGIT
for j in range(0, DIGIT_COUNT):
digit = last_digit
while digit == last_digit:
digit = random.randint(0, 9)
last_digit = digit
digits = digits * 10 + digit
digits_as_str = DIGIT_FORMAT_STR % digits
labels.append(digits_as_str)
images.append(captcha.generate_image(digits_as_str))
digit_labels = np.empty((nb_sample, DIGIT_COUNT), dtype="int8")
shape = (nb_sample, IMAGE_STD_HEIGHT, IMAGE_STD_WIDTH, RGB_COLOR_COUNT)
digit_image_data = np.empty(shape, dtype="float32")
for index in range(0, nb_sample):
img = images[index].resize((IMAGE_STD_WIDTH, IMAGE_STD_HEIGHT), PIL.Image.LANCZOS)
img_arr = np.asarray(img, dtype="float32") / 255.0
digit_image_data[index, :, :, :] = img_arr
for digit_index in range(0, DIGIT_COUNT):
digit_labels[index][digit_index] = labels[index][digit_index]
x, y_as_num = digit_image_data, np.rollaxis(digit_labels, 1)
y = { (OUT_PUT_NAME_FORMAT % i ): to_categorical(y_as_num[i], CLASS_COUNT) for i in range(0, DIGIT_COUNT) }
# y = [to_categorical(y_as_num[i], CLASS_COUNT) for i in range(0, DIGIT_COUNT)]
return x, y
def gen_test_captcha(self):
image = ImageCaptcha(width = self.width,height = self.height)
captcha_str = ''.join(random.sample(self.characters,self.char_num))
img = image.generate_image(captcha_str)
img.save(captcha_str + '.jpg')
class PyCaptcha(BaseCaptcha):
def __init__(self, app):
from captcha.image import ImageCaptcha # pip install captcha
super().__init__(app)
self.app = app
self.fonts = app.config['PYCAPTCHA_FONTS']
self.prefix = app.config['PYCAPTCHA_CACHE_PREFIX']
self.chars = app.config['PYCAPTCHA_CHARS']
self.case_sens = app.config['PYCAPTCHA_CASE_SENSITIVE']
self.length = app.config['PYCAPTCHA_LENGTH']
rnd = utils_random.randrange(10**11, 10**12)
k = self.prefix + '_cache_test_{}'.format(rnd)
self.app.cache.set(k, rnd, timeout=10)
if self.app.cache.get(k) != rnd:
raise RuntimeError('PyCaptcha requires working cache (e.g. memcached)')
self.generator = ImageCaptcha(fonts=self.fonts)
self.bind_captcha_views()
def bind_captcha_views(self):
from flask import Blueprint
bp = Blueprint('pycaptcha', __name__)
bp.route('/captcha/<int:captcha_id>.jpg')(self.captcha_view)
self.app.register_blueprint(bp)
def _draw_and_save_image(self, captcha_id):
from io import BytesIO
solution = utils_random.random_string(self.length, self.chars)
with self.generator.generate_image(solution) as im: # class PIL.Image
data = BytesIO()
im.save(data, format='JPEG', quality=55)
data = data.getvalue()
tm = time.time()
k = self.prefix + str(captcha_id)
self.app.cache.set(k, [tm, data, solution], timeout=7200)
return data
def captcha_view(self, captcha_id):
from flask import abort, make_response
k = self.prefix + str(captcha_id)
result = self.app.cache.get(k)
if result is None:
abort(404)
if time.time() - result[0] > 1:
data = self._draw_and_save_image(captcha_id)
else:
data = result[1]
response = make_response(data)
response.headers['Content-Type'] = 'image/jpeg'
response.headers["Cache-Control"] = "no-cache, no-store, must-revalidate"
response.headers["Pragma"] = "no-cache"
response.headers["Expires"] = "0"
response.headers['Cache-Control'] = 'public, max-age=0'
return response
def generate(self, lazy=True):
captcha_id = utils_random.randrange(10**11, 10**12)
k = 'pycaptcha_{}'.format(captcha_id)
self.app.cache.set(k, [0, b'', ''], timeout=7200)
if self.app.cache.get(k) != [0, b'', '']:
raise RuntimeError('PyCaptcha requires working cache (e.g. memcached)')
if not lazy:
self._draw_and_save_image(captcha_id)
return {'cls': 'mini_fiction.captcha.PyCaptcha', 'pycaptcha_id': str(captcha_id)}
def get_fields(self):
return ('captcha_id', 'captcha_solution')
def check(self, form):
captcha_id = form.get('captcha_id')
solution = form.get('captcha_solution')
if isinstance(captcha_id, str):
if captcha_id.isdigit():
captcha_id = int(captcha_id)
if not captcha_id or not solution:
return False
if not isinstance(solution, str) or len(solution) > 254 or not isinstance(captcha_id, int):
return False
k = self.prefix + str(captcha_id)
result = self.app.cache.get(k)
if not result:
return False
result = result[2]
self.app.cache.set(k, None, timeout=10)
if not self.case_sens:
solution = solution.lower()
result = result.lower()
return solution == result
# -*-coding=utf-8-*-
# @Time : 2018/8/21 13:47
# @File : captcha_usage.py
from captcha.image import ImageCaptcha
import matplotlib.pyplot as plt
import numpy as np
import random
import string
characters = string.digits + string.ascii_uppercase
print(characters)
width,height,n_len,n_class=170,80,4,len(characters)
generator = ImageCaptcha(width=width,height=height)
rand_str = ''.join([random.choice(characters) for i in range(n_len)])
img = generator.generate_image(rand_str)
plt.imshow(img)
plt.title(rand_str)
plt.show()
def gen(batch_size=32):
X = np.zeros((batch_size, height, width, 3), dtype=np.uint8)
y = [np.zeros((batch_size, n_class), dtype=np.uint8) for i in range(n_len)]
generator = ImageCaptcha(width=width, height=height)
while True:
for i in range(batch_size):
random_str = ''.join([random.choice(characters) for j in range(4)])
X[i] = generator.generate_image(random_str)
for j, ch in enumerate(random_str):
y[j][i, :] = 0
y[j][i, characters.find(ch)] = 1
