instruct-pix2pix-dataset

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instruct-pix2pix-dataset

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This repository provides utilities to a minimal dataset for InstructPix2Pix like training for Diffusion models.

instruct-pix2pix-dataset 최신버젼 다운로드

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This repository provides utilities to a minimal dataset for [InstructPix2Pix](https://arxiv.org/abs/2211.09800) like training for Diffusion models.

## Steps

1. Download the original dataset as discussed [here](https://github.com/timothybrooks/instruct-pix2pix#generated-dataset). I used this version: `clip-filtered-dataset`. Note that the download can take as long as 24 hours depending on the internet bandwidth. The dataset also requires at least 600 GB of storage.
2. Then run:

```bash
    python make_dataset.py --data_root clip-filtered-dataset --num_samples_to_use 1000
    ```
3. The `make_dataset.py` was specifically designed to obtain a [🤗 dataset](https://huggingface.co/docs/datasets/). So, it's the most useful when you push the minimal dataset to the 🤗 Hub. You can do so by setting `push_to_hub` while running `make_dataset.py`.

## Example dataset

https://huggingface.co/datasets/sayakpaul/instructpix2pix-1000-samples

The full version of the CLIP filtered dataset used for InstructPix2Pix training can be found here: https://huggingface.co/datasets/timbrooks/instructpix2pix-clip-filtered

With the dataset being on the 🤗 Hub, one can do load the dataset with two lines of code:

```python
from datasets import load_dataset

dataset = load_dataset("timbrooks/instructpix2pix-clip-filtered", split="train")
```

And voila 🤗

## Acknowledgements

The structure of `make_dataset.py` is inspired by Nate Raw's [notebook](https://gist.github.com/nateraw/c91fb548c3a749cfbe6436d555a547b0).

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