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  license: apache-2.0
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  license: apache-2.0
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+
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+ ![Python >=3.8](https://img.shields.io/badge/Python->=3.8-blue.svg)
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+ ![PyTorch >=1.1](https://img.shields.io/badge/PyTorch->=1.1-yellow.svg)
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+
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+ ## Accountable Textual-Visual Chat Learns to Reject Human Instructions in Image Re-creation
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+ The *official* repository for [Accountable Textual-Visual Chat Learns to Reject
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+ Human Instructions in Image Re-creation]().
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+
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+ ![ Qualitative results of CLEVR-ATVM dataset.](./assets/atvc.png)
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+
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+ ### Requirements
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+
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+ - Python 3.8
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+ - matplotlib == 3.1.1
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+ - numpy == 1.19.4
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+ - pandas == 0.25.1
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+ - scikit_learn == 0.21.3
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+ - torch == 1.8.0
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+
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+ ### Installation
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+
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+ We provide an environment file; ``environment.yml`` containing the required dependencies. Clone the repo and run the following command in the root of this directory:
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+ ```
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+ conda env create -f environment.yml
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+ ```
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+
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+ ### Dataset
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+
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+ Please refer to [DOWNLOAD.md](data/DOWNLOAD.md) for dataset preparation.
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+
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+
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+ ### Pretrained Models
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+ Please refer to [pretrained-models](pretrained-models/README.md) to download the released models.
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+
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+
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+ ### Train
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+
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+ #### Training commands
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+
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+ + To train the first stage:
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+ ```shell
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+ bash dist_train_vae.sh ${DATA_NAME} ${NODES} ${GPUS}
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+ ```
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+ + To train the second stage:
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+ ```shell
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+ bash dist_train_atvc.sh ${VAE_PATH} ${DATA_NAME} ${NODES} ${GPUS}
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+ ```
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+
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+ #### Arguments
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+
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+ + `${VAE_PATH}`: path of pretrained vae model.
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+ + `${DATA_NAME}`: dataset for training, e.g. `CLEVR-ATVC`, `Fruit-ATVC`.
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+ + `${NODES}`: number of node.
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+ + `${GPUS}`: number of gpus for each node.
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+
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+
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+ ### Test
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+
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+ #### Testing commands
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+
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+ + To test image reconstruction ability of the first stage:
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+ ```shell
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+ bash gen_vae.sh ${GPU} ${VAE_PATH} ${IMAGE_PATH}
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+ ```
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+ + To test atvc final model:
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+ ```shell
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+ bash gen_atvc.sh ${GPU} ${ATVC_PATH} ${TEXT_QUERY} ${IMAGE_PATH}
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+ ```
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+
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+ #### Arguments
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+
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+ + `${GPU}`: id of one gpu, e.g. `0`.
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+ + `${VAE_PATH}`: path of pretrained vae model.
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+ + `${IMAGE_PATH}`: image path for reconstrction, e.g. `input.png`.
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+ + `${ATVC_PATH}`: path of pretrained atvc model.
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+ + `${TEXT_QUERY}`: text-based query, e.g. `"Please put the small blue cube on top of the small yellow cylinder."`.
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+
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+
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+ ### License
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+
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+ `ATVC` is released under the [Apache 2.0 license](LICENSE).
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+
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+
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+ ### Citation
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+ If you find this code useful for your research, please cite our paper
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+ ```
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+ @article{zhang2023accountable,
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+ title={Accountable Textual-Visual Chat Learns to Reject Human Instructions in Image Re-creation},
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+ author={Zhang, Zhiwei and Liu, Yuliang},
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+ journal={arXiv preprint arXiv:2303.05983},
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+ year={2023}
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+ }
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+ ```
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+
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+ ## Acknowledgement
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+
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+ Our code is learned from [DALLE-pytorch](https://github.com/lucidrains/DALLE-pytorch) and [CLIP](https://github.com/openai/CLIP). We would like to thank all the people who help label text-image pairs and participate in human evaluation experiments. We hope our explorations and findings contribute valuable insights regarding the accountability of textual-visual generative models.
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+
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+ ## Contact
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+
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+ This project is developed by Zhiwei Zhang ([@zzw-zwzhang](https://github.com/zzw-zwzhang)) and Yuliang Liu ([@Yuliang-Liu](https://github.com/Yuliang-Liu)).
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+