updated readme

Author: FilippoMB

README.md

@@ -1,5 +1,21 @@
-## Prompt engineering guide
-Let's say you want to draw an image of ``lion``. The raw promt, ``lion`` will give you images that are usually chaotic or of bad quality.
+## 1. Quick start 
+
+Recently, the [Stable Diffusion Public Release](https://stability.ai/blog/stable-diffusion-public-release) made available to everyone one of the most powerful deep learning model for image generation. 
+
+This repository is a collection of simple scripts that can be used to generate images with Stable Diffusion and gives an introduction to the theory behind diffusion models.
+
+To start using Stable Diffusion, you first need to create an account on [Huggin's Face](https://huggingface.co/) and generate a [token](https://huggingface.co/docs/hub/security-tokens). Afterwards, if you have access to a GPU server, you can follow the basic tutorial in the [model card](https://huggingface.co/CompVis/stable-diffusion-v1-4).
+If you don't have a GPU server to run the model, you can try out Stable Diffusion using one of the Colab notebooks below. 
+
+- Text to image [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1zjr9n60q3G8Qd87WG3ZnjDgI-D1YBCbG?usp=sharing)
+- Image to image [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1zjr9n60q3G8Qd87WG3ZnjDgI-D1YBCbG?usp=sharing)
+- Sketch to image [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1MyESLsR8D5l_EBqumwxL0eMzNmd3uqs6?usp=sharing)
+
+
+## 2. Prompt engineering guide
+Let's say you want to draw an image of ``lion``. The raw promt, ``lion`` will give you images that are usually a bit chaotic or worse quality.
+
+<img src="./img/lion_short.png">
 
 To obtain better results, the prompt should be egineered. A basic recipe is the following:
 
@@ -9,14 +25,28 @@ To obtain better results, the prompt should be egineered. A basic recipe is the
 - Examples of ``artist`` are: Jan van Eyck (when ``style`` = *Portrait*), *Vincent Van Gogh* (when ``style`` = *Oil painting*), *Leonardo Da Vinci* (when ``style`` = *Pencil drawing*), and so on. Note that you can also mix artists, to get original results.
 - Examples of ``details`` are *Unreal Engine* if you want to add realistic lightining, *8 k* if you want to add more details, *artstation* if you want to make your image more artistic, and so on.
 
-Example of elaborated prompt: 
+Example of elaborated prompts: 
+
+*"Professional photograph of a lion with a black mane, high quality, highly detailed, award-winning, hd, 8k, awe-inspirin"*
+
+<img src="./img/lion_long1.png">
 
 *"retrofuturistic portrait of a lion in astro suit, space graphics art in background, close up, wlop, dan mumford, artgerm, liam brazier, peter mohrbacher, raw, featured in artstation, octane render, cinematic, elegant, intricate, 8 k"*
 
+<img src="./img/lion_long.png">
+
 To see more examples of prompts and get inspirations, check [here](https://lexica.art/).
 
 
-## Resources
+## 3. Diffusion model theory and step-by-step implementation
+
+Pytorch implementation of the diffussion model presented in [].
+
+
+## 4. Resources
+
+**Repositories**
+- A browser interface based on Gradio library for Stable Diffusion [link](https://github.com/AUTOMATIC1111/stable-diffusion-webui).
 
 **Colab notebooks**
 - Introduction to diffusers 🧨, the Hugging Face 🤗 library for diffusion models [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/notebooks/blob/main/diffusers/diffusers_intro.ipynb)
@@ -28,3 +58,6 @@ To see more examples of prompts and get inspirations, check [here](https://lexic
 - [What are Diffusion Models?](https://lilianweng.github.io/posts/2021-07-11-diffusion-models/#nice) introduction to Diffusion models and mathematical derivations.
 - [The Annotated Diffusion Model](https://huggingface.co/blog/annotated-diffusion) step-by-step tutorial for building a Diffusion model from scratch in Pytorch
 - [Generative Modeling by Estimating Gradients of the Data Distribution](https://yang-song.net/blog/2021/score/) Introduction to score-based generative models.
+
+**Papers**
+- [[1](https://openaccess.thecvf.com/content/CVPR2022/papers/Rombach_High-Resolution_Image_Synthesis_With_Latent_Diffusion_Models_CVPR_2022_paper.pdf)] Rombach, Robin, et al. "High-resolution image synthesis with latent diffusion models." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2022.