Method get_verify_batch

train_model.py:104–119

(self, size=50)

        return batch_x, batch_y

    def get_verify_batch(self, size=50):
        batch_x = np.zeros([size, self.image_height * self.image_width])  # 初始化
        batch_y = np.zeros([size, self.max_captcha * self.char_set_len])  # 初始化

        verify_images = []
        for i in range(size):
            # TODO:
            verify_images.append(random.choice(self.train_images_list))

        for i, img_name in enumerate(verify_images):
            # TODO:
            label, image_array = self.gen_captcha_text_image(self.train_img_path, img_name)
            image_array = self.convert2gray(image_array)  # 灰度化图片
            batch_x[i, :] = image_array.flatten() / 255  # flatten 转为一维
            batch_y[i, :] = self.text2vec(label)  # 生成 oneHot
        return batch_x, batch_y

    def train(self):
        y_pred = self.alexnet_model()