def test_captcha():
captcha = generate_captcha.generateCaptcha(width=100,
height=30,
characters=string.digits)
width, height, char_num, characters, classes = captcha.get_parameter()
x = tf.placeholder(tf.float32, [None, height, width, 1])
y_ = tf.placeholder(tf.float32, [None, char_num * classes])
keep_prob = tf.placeholder(tf.float32)
model = captcha_model.captchaModel(width, height, char_num, classes)
y_conv = model.create_model(x, keep_prob)
saver = tf.train.Saver()
with tf.Session() as sess:
# sess.run(tf.global_variables_initializer())
saver.restore(sess, tf.train.latest_checkpoint("./ckpt"))
# batch_x, batch_y = captcha.gen_test_captcha()
batch_x, batch_y = captcha.gen_api_captcha()
loss = sess.run([y_conv],
feed_dict={
x: batch_x,
y_: batch_y,
keep_prob: 0.75
})
print("real == %s, predict = %s, result = %s" %
(captcha.decode_captcha(batch_y), captcha.decode_captcha(loss),
"Match" if captcha.decode_captcha(batch_y)
== captcha.decode_captcha(loss) else "Not Match"))
return True if captcha.decode_captcha(batch_y) == captcha.decode_captcha(
loss) else False
def test_captcha(file_path):
captcha = generate_captcha.generateCaptcha(width=100, height=30, characters=string.digits)
width, height, char_num, characters, classes = captcha.get_parameter()
x = tf.placeholder(tf.float32, [None, height, width, 1])
y_ = tf.placeholder(tf.float32, [None, char_num * classes])
keep_prob = tf.placeholder(tf.float32)
model = captcha_model.captchaModel(width, height, char_num, classes)
y_conv = model.create_model(x, keep_prob)
saver = tf.train.Saver()
with tf.Session() as sess:
saver.restore(sess, tf.train.latest_checkpoint("./ckpt"))
batch_x, batch_y = captcha.gen_local_captcha(file_path)
loss = sess.run([y_conv], feed_dict={x: batch_x, y_: batch_y, keep_prob: 0.75})
return captcha.decode_captcha(loss)
#!/usr/bin/python
from PIL import Image, ImageFilter
import tensorflow as tf
import numpy as np
import string
import sys
import generate_captcha
import captcha_model
if __name__ == '__main__':
captcha = generate_captcha.generateCaptcha()
width, height, char_num, characters, classes = captcha.get_parameter()
gray_image = Image.open(sys.argv[1]).convert('L')
img = np.array(gray_image.getdata())
test_x = np.reshape(img, [height, width, 1]) / 255.0
x = tf.placeholder(tf.float32, [None, height, width, 1])
keep_prob = tf.placeholder(tf.float32)
model = captcha_model.captchaModel(width, height, char_num, classes)
y_conv = model.create_model(x, keep_prob)
predict = tf.argmax(tf.reshape(y_conv, [-1, char_num, classes]), 2)
init_op = tf.global_variables_initializer()
saver = tf.train.Saver()
gpu_options = tf.GPUOptions(per_process_gpu_memory_fraction=0.95)
with tf.Session(config=tf.ConfigProto(log_device_placement=False,
gpu_options=gpu_options)) as sess:
sess.run(init_op)
saver.restore(sess, "capcha_model.ckpt")
pre_list = sess.run(predict, feed_dict={x: [test_x], keep_prob: 1})
# -*- coding:utf-8 -*-
import string
import tensorflow as tf
import generate_captcha
import captcha_model
if __name__ == '__main__':
captcha = generate_captcha.generateCaptcha(width=100,
height=30,
characters=string.digits)
width, height, char_num, characters, classes = captcha.get_parameter()
x = tf.placeholder(tf.float32, [None, height, width, 1])
y_ = tf.placeholder(tf.float32, [None, char_num * classes])
keep_prob = tf.placeholder(tf.float32)
model = captcha_model.captchaModel(width, height, char_num, classes)
y_conv = model.create_model(x, keep_prob)
cross_entropy = tf.reduce_mean(
tf.nn.sigmoid_cross_entropy_with_logits(labels=y_, logits=y_conv))
train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)
predict = tf.reshape(y_conv, [-1, char_num, classes])
real = tf.reshape(y_, [-1, char_num, classes])
correct_prediction = tf.equal(tf.argmax(predict, 2), tf.argmax(real, 2))
correct_prediction = tf.cast(correct_prediction, tf.float32)
accuracy = tf.reduce_mean(correct_prediction)
saver = tf.train.Saver()
with tf.Session() as sess:
#coding=utf-8
# File : generate_testing_set.py
# Desc :
# Author : jianhuChen
# license : Copyright(C), USTC
# Time : 2018/10/31 10:44
from generate_captcha import generateCaptcha
captcha = generateCaptcha()
for i in range(100):
captcha.gen_test_captcha('TestingSet')
print("Complete.........")
