Bangla Natural Language Image to Text (BNLIT)

We represented a new Bangla dataset with a Hybrid Recurrent Neural Network model which generated Bangla natural language description of images. This dataset achieved by a large number of images with classification and containing natural language process of images. We conducted experiments on our self-made Bangla Natural Language Image to Text (BNLIT) dataset. Our dataset contained 8,743 images. We made this dataset using Bangladesh perspective images. We used one annotation for each image. In our repository, we added two types of pre-processed data which is 224 × 224 and 500 × 375 respectively alongside annotations of full dataset. We also added CNN features file of whole dataset in our repository which is features.pkl.

本研究借助可生成图像孟加拉语自然语言描述的混合循环神经网络（Hybrid Recurrent Neural Network）模型，构建了一款全新的孟加拉语（Bangla）数据集。该数据集基于海量带分类标注的图像构建，涵盖图像自然语言处理相关任务数据。我们基于自主构建的孟加拉语图像转文本（Bangla Natural Language Image to Text, BNLIT）数据集开展了实验。本数据集共包含8743张图像，所有图像均取材自孟加拉国本土视角。我们为每张图像仅配备一条标注。在本研究的代码仓库中，我们除提供完整数据集的标注文件外，还额外添加了两种预处理图像数据，分辨率分别为224×224与500×375。此外，我们还将全数据集的卷积神经网络（Convolutional Neural Network, CNN）特征文件features.pkl上传至该仓库中。