学习进度笔记31

观看Tensorflow案例实战视频课程21 卷积网络模型定义

#定义CNN
def crack_captcha_cnn(w_alpha=0.01,b_alpha=0.1):
    x=tf.reshape(X,shape=[-1,IMAGE_HEIGHT,IMAGE_WIDTH,1])

    #w_c1_alpha=np.sqrt(2.0/(IMAGE_HEIGHT*IMAGE_WIDTH))#
    #w_c2_alpha=np.sqrt(2.0/(3*3*32))
    #w_c3_alpha=np.sqrt(2.0/(3*3*64))
    #w_d1_alpha=np.sqrt(2.0/(8*32*64))
    #out_alpha=np.sqrt(2.0/1024)

    # 3 conv layer
    w_c1 = tf.Variable(w_alpha * tf.random_normal([3, 3, 1, 32]))
    b_c1 = tf.Variable(b_alpha * tf.random_normal([32]))
    conv1 = tf.nn.relu(tf.nn.bias_add(tf.nn.conv2d(x, w_c1, strides=[1, 1, 1, 1], padding='SAME'),b_c1))
    conv1 = tf.nn.max_pool(conv1, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME')
    conv1 = tf.nn.dropout(conv1, keep_prob)

    w_c2 = tf.Variable(w_alpha * tf.random_normal([3, 3, 32, 64]))
    b_c2 = tf.Variable(b_alpha * tf.random_normal([64]))
    conv2 = tf.nn.relu(tf.nn.bias_add(tf.nn.conv2d(conv1, w_c2, strides=[1, 1, 1, 1], padding='SAME'),b_c2))
    conv2 = tf.nn.max_pool(conv2, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME')
    conv2 = tf.nn.dropout(conv2, keep_prob)

    w_c3 = tf.Variable(w_alpha * tf.random_normal([3, 3, 64, 64]))
    b_c3 = tf.Variable(b_alpha * tf.random_normal([64]))
    conv3 = tf.nn.relu(tf.nn.bias_add(tf.nn.conv2d(conv2, w_c3, strides=[1, 1, 1, 1], padding='SAME'),b_c3))
    conv3 = tf.nn.max_pool(conv3, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME')
    conv3 = tf.nn.dropout(conv3, keep_prob)

    # Fully connected layer
    w_d = tf.Variable(w_alpha * tf.random_normal([8*20*64, 1024]))
    b_d = tf.Variable(b_alpha * tf.random_normal([1024]))
    dense = tf.reshape(conv3,[-1,w_d.get_shape().as_list()[0]])
    dense = tf.nn.relu(tf.add(tf.matmul(dense,w_d),b_d))
    dense = tf.nn.dropout(conv3, keep_prob)

    w_out = tf.Variable(w_alpha * tf.random_normal([1024,MAX_CAPTCHA*CHAR_SET_LEN]))
    b_out = tf.Variable(b_alpha * tf.random_normal([MAX_CAPTCHA*CHAR_SET_LEN]))
    out=tf.add(tf.matmul(dense,w_out),b_out)
    return out