68 lines
2.5 KiB
Markdown
68 lines
2.5 KiB
Markdown
Latent blending enables the creation of super-smooth video transitions between prompts. Powered by [stable diffusion 2.1](https://stability.ai/blog/stablediffusion2-1-release7-dec-2022), this method involves specific mixing of intermediate latent representations to create a seamless transition – with users having the option to choose full customization or preset options.
|
||
|
||
# Quickstart
|
||
```python
|
||
fp_ckpt = 'path_to_SD2.ckpt'
|
||
fp_config = 'path_to_config.yaml'
|
||
|
||
sdh = StableDiffusionHolder(fp_ckpt, fp_config, 'cuda')
|
||
lb = LatentBlending(sdh)
|
||
|
||
lb.load_branching_profile(quality='medium', depth_strength=0.4)
|
||
lb.set_prompt1('photo of my first prompt1')
|
||
lb.set_prompt2('photo of my second prompt')
|
||
|
||
imgs_transition = lb.run_transition()
|
||
```
|
||
## Gradio UI
|
||
To run the UI on your local machine, run `gradio_ui.py`
|
||
|
||
## Example 1: Simple transition
|
||
|
||
To run a simple transition between two prompts, run `example1_standard.py`
|
||
|
||
## Example 2: Inpainting transition
|
||
|
||
To run a transition between two prompts where you want some part of the image to remain static, run `example2_inpaint.py`
|
||
|
||
## Example 3: Multi transition
|
||
To run multiple transition between K prompts, resulting in a stitched video, run `example3_multitrans.py`
|
||
|
||
# Relevant parameters
|
||
|
||
|
||
# Installation
|
||
#### Packages
|
||
```commandline
|
||
pip install -r requirements.txt
|
||
```
|
||
#### Download Models from Huggingface
|
||
[Download the Stable Diffusion v2-1_768 Model](https://huggingface.co/stabilityai/stable-diffusion-2-1)
|
||
|
||
[Download the Stable Diffusion Inpainting Model (optional)](https://huggingface.co/stabilityai/stable-diffusion-2-inpainting)
|
||
|
||
[Download the Stable Diffusion x4 Upscaler (optional)]([https://huggingface.co/stabilityai/stable-diffusion-2-inpainting](https://huggingface.co/stabilityai/stable-diffusion-x4-upscaler))
|
||
|
||
#### (Optional but recommended) Install [Xformers](https://github.com/facebookresearch/xformers)
|
||
With xformers, stable diffusion will run faster with smaller memory inprint. Necessary for higher resolutions / upscaling model.
|
||
|
||
```commandline
|
||
conda install xformers -c xformers/label/dev
|
||
```
|
||
|
||
Alternatively, you can build it from source:
|
||
```commandline
|
||
# (Optional) Makes the build much faster
|
||
pip install ninja
|
||
# Set TORCH_CUDA_ARCH_LIST if running and building on different GPU types
|
||
pip install -v -U git+https://github.com/facebookresearch/xformers.git@main#egg=xformers
|
||
# (this can take dozens of minutes)
|
||
```
|
||
|
||
# How does it work
|
||
|
||
|
||
what makes a transition a good transition?
|
||
* absence of movement
|
||
* every frame looks like a credible photo
|