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CFSum: A Coarse-to-Fine Contributions Network for Multimodal Summarization

This is the official repository of CFSum (ACL 2023).

framework

Some code in this repo are copied/modified from opensource implementations made available by UNITER

The image features are extracted as UNITER. Due to some problems in image feature extraction by UNITER, we tried to restore the image feature extraction process of UNITER. Specifically:

(1) UNITER uses BUTD image feature extractor faster-rcnn, thus we use BUTD docker to extract image feature;

(2) The checkpoint of the faster-rcnn model is derived from the pretrain-model provided by BUTD.

Requirements

Please install the following:

We only support Linux with NVIDIA GPUs. We test on Ubuntu 16.04 and 3090 cards.

Quick Start

NOTE: Please refer to UNITER bash scripts/download_pretrained.sh $PATH_TO_STORAGE to get pretrained checkpoints. This will download both the base and large models.

  • Data preparation

    1. Dataset download: Download the dataset from ZNLP/ZNLP-Dataset (github.com) or the google driver https://drive.google.com/file/d/14LoM5-6h1eFa9-NAPuAJnAIyNXF8xNpu/view

    2. Feature Extract: Utilize the BUTD to extract the feature of images, the data format can refer to ./example

    3. Download pre-trained UNITER checkpoint: >> sh ./utils/download_pretrained_uniter.sh.

  • train

    • First, init the model with python train.py ./configs/base_multi.py, and save the model checkpoint.

    • Second, use the above checkpoint to init the model. Specifically, setting model_init_path with the path of the checkpoint.

    • Begin training:

      python train.py ./configs/CFSum_F3W6P9.json

  • test

    • Begin testing:

      python inference.py ./configs/CFSum_F3W6P9.json ./output/train_dir/model_path

      The results will be saved in ./output/train_dir/hyp.txt

Evaluation

We use the [files2rouge](ZNLP/ZNLP-Dataset (github.com)) to evaluate the performance of generated summary:

>> files2rouge /path_of_test_title.txt hyp.txt

Docker Fetch

  1. docker install on Ubuntu: refer to [blog](Ubuntu · Docker -- 从入门到实践 (docker-practice.github.io))

如果遇到镜像无法下载，可使用国内镜像：Docker快速入门二：Docker配置国内镜像源、常用命令_docker设置镜像-CSDN博客

Docker将镜像导出到本地,上传至内网服务器上-腾讯云开发者社区-腾讯云 (tencent.com)

镜像导入导出： https://blog.csdn.net/u010797364/article/details/120430270