# 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`.  PyTorch inference with DALL·E Mega 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.  The colab notebook demonstrates how to load a model once and run it multiple times.

Here are some 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)