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README.md

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 # Datasets for the Direct Preference for Denoising Diffusion Policy Optimization (D3PO)
 
-**Description**: The dataset for the image distortion experiment of the [`anything-v5`](https://huggingface.co/stablediffusionapi/anything-v5) model in the paper [Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model](https://arxiv.org/abs/2311.13231).
-                (2024.1.22 Update: Add the dataset for evaluating text and image alignment before and after fine-tuning.)
+**Description**: This repository contains the dataset for the D3PO method in this paper [Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model](https://arxiv.org/abs/2311.13231). The *d3po_dataset* file pertains to the image distortion experiment of the [`anything-v5`](https://huggingface.co/stablediffusionapi/anything-v5) model.
+                The *text2img_dataset* comprises the images generated from the pretrained, preferred image fine-tuned, reward weighted fine-tuned and D3PO fine-tuned models in the prompt-image alignment experiment.
                 
-**Source Code**: The code used to generate this data can be found [here](https://github.com/yk7333/D3PO/tree/main).
+**Source Code**: The code used to generate this data can be found [here](https://github.com/yk7333/D3PO/).
 
 **Directory**
 - d3po_dataset