min-dalle-test/README.md

# min(DALL·E)

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/kuprel/min-dalle/blob/main/min_dalle.ipynb)

This is a minimal implementation of [DALL·E Mini](https://github.com/borisdayma/dalle-mini).  It has been stripped to the bare essentials necessary for doing inference, and converted to PyTorch.  The only third party dependencies are numpy, torch, and flax (and optionally wandb to download the models).  DALL·E Mega inference with pytorch takes about 10 seconds in colab.

### Setup

Run `sh setup.sh` to install dependencies and download pretrained models.  The `wandb` python package is installed to download DALL·E mini and DALL·E mega.  Alternatively, the models can be downloaded manually here: 
[VQGan](https://huggingface.co/dalle-mini/vqgan_imagenet_f16_16384), 
[DALL·E Mini](https://wandb.ai/dalle-mini/dalle-mini/artifacts/DalleBart_model/mini-1/v0/files), 
[DALL·E Mega](https://wandb.ai/dalle-mini/dalle-mini/artifacts/DalleBart_model/mega-1-fp16/v14/files)

### Usage

Use the python script `image_from_text.py` to generate images from the command line.  Note: the command line script loads the models and parameters each time.  To load a model once and generate multiple times, initialize either `MinDalleTorch` or `MinDalleFlax`, then call `generate_image` with some text and a seed.  See the colab for an example.

### Examples

```
python3 image_from_text.py --text='artificial intelligence' --torch
```
![Alien](examples/artificial_intelligence.png)


```
python image_from_text.py --text='a comfy chair that looks like an avocado' --torch --mega --seed=10
```
![Avocado Armchair](examples/avocado_armchair.png)


```
python image_from_text.py --text='court sketch of godzilla on trial' --mega --seed=100
```

![Godzilla Trial](examples/godzilla_trial.png)