https://github.com/beinsezii/quickdif
Quick and easy Diffusers CLI
https://github.com/beinsezii/quickdif
cli diffusers diffusion diffusion-models image-generation image2image img2img pytorch stable-diffusion text2image txt2img
Last synced: 6 months ago
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Quick and easy Diffusers CLI
- Host: GitHub
- URL: https://github.com/beinsezii/quickdif
- Owner: Beinsezii
- License: gpl-3.0
- Created: 2023-11-04T02:12:49.000Z (almost 2 years ago)
- Default Branch: master
- Last Pushed: 2025-04-14T04:13:52.000Z (6 months ago)
- Last Synced: 2025-04-14T05:25:11.993Z (6 months ago)
- Topics: cli, diffusers, diffusion, diffusion-models, image-generation, image2image, img2img, pytorch, stable-diffusion, text2image, txt2img
- Language: Python
- Homepage:
- Size: 1.71 MB
- Stars: 13
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# quickdif
Quick and easy CLI inference that just works™ for a variety of Diffusers models
## Including
* Verified working across many models
+ AuraFlow
+ FLUX
+ Hunyuan
+ Kandinsky
+ Kolors
+ Lumina T2X
+ Pixart (Alpha/Sigma)
+ Sana
+ Stable Cascade
+ Stable Diffusion (1.5/2.1)
+ Stable Diffusion 3
+ Stable Diffusion XL
- No refiner
+ Wuerstchen
* Other Diffusers format models will likely work to varying degrees
* Multi-lora fusion using `peft` for minimal performance loss
* Features all of the most common generation parameters
* Includes many advanced generation parameters
* 1, 2, 3, 4, 5, 6, 7, 8-bit quantization
* PAG / Perturbed-Attention Guidance
* Many latent augmentation params
* Many post processing effects
* Fully modular samplers/schedules, courtesy of [skrample](https://github.com/Beinsezii/skrample)
* Iterate over most parameters and create grids
* Expand prompts with `photo of {all|of|these}` or `photo of [one|of|these]`
* Load settings from JSON, TOML, PNG
* Extremely small 1-shot script using `accelerate` for hot loading models
* Targeted AMD/ROCm optimizations
* NVIDIA/CUDA does not need additional optimizations
## Not Including
- ControlNet, Inpaint
- Multi-stage models: DFIF Stage 2, SDXL Refiner
- Server/API for a perpetual instance
- 100% maximum throughput
- 1-click installer
- MacOS/MPS and Intel OneAPI may not function properly
## Installation
This project only supports `pip` based installs on Python 3.11+
#### Basic setup
```sh
> git clone https://github.com/Beinsezii/quickdif.git
> cd ./quickdif/
```
#### Create a venv in the quickdif folder
```sh
> python3 -m venv ./venv
# alternatively, it's recommended to use the full virtualenv if you have it
> virtualenv ./venv
```
#### Install dependencies
```sh
# replace with appropriate activation script for other shells
> source ./venv/bin/activate
# It's recommended to first install torch using the recommended commands from https://pytorch.org/get-started/locally/
> pip install torch --index-url https://download.pytorch.org/whl/rocm6.0 # AMD example
# finally
> pip install -e .
> deactivate
> ./quickdif.sh "kitten"
# Windows users will instead have to invoke Python directly
> python quickdif.py "kitten"
```
### As a module
Additionally, you may use the project as a python module
```sh
pip install git+https://github.com/Beinsezii/quickdif.git
python -m quickdif "kitten"
```
## Usage
```sh
# See all options. Always refer to the script help over the other examples in this README
> ./quickdif.sh --help
# Run with defaults
> ./quickdif.sh "high resolution dslr photograph of pink roses in the misty rain"
# Custom model
> ./quickdif.sh "analogue photograph of a kitteon on the beach in golden hour sun rays" -m "ptx0/terminus-xl-gamma-v1"
# Single files work for Stable Diffusion
> ./quickdif.sh "colorful fantasy artwork side profile of a feminine robot in a dark cyberpunk city" -m ./checkpoints/sd15/dreamshaper-v6.safetensors
# Four dog and four cat images at twenty steps
> ./quickdif.sh "photo of a dog" "painting of a cat" -B 4 -s 20
# Colored latent for an offset noise effect
> ./quickdif.sh "underwater photograph of a dark cave full of bioluminescent glowing mushrooms" -g 9.0 -s 30 -C black -c 0.8
# Compile for a long job
> ./quickdif.sh $(cat prompts.txt) --compile
# Export favorite settings to the defaults JSON
> ./quickdif.sh -m "stabilityai/stable-cascade" -s 20 -n "blurry, noisy, cropped" --json ./quickdif.json
# Save a style to a custom JSON
> ./quickdif.sh "fantasy artwork of a kitten wearing gothic plate armor" -g 10 -G 0.5 --json ./epic_kitten.json
# Merge multiple configs
> ./quickdif.sh -I underwater_cave.png epic_kitten.json
```
## F.A.Q.
Question|Answer
---|---
Why not X popular UI?|SD.Next's diffusers backend is extremely buggy/broken in multiple areas and InvokeAI (+non-diffusers UIs) only really supports Stable Diffusion.
Windows?|The python script should work just fine but you'll need to set up the powershell/CMD stuff on your own.
Gradio?|No. If a UI ever gets made for this it'll be its own separate entity that interfaces via API. Cramming a bad gradio interface into the main script wont do anyone any favors
Feature XYZ?|Maybe. Things in the *Not Including* list may come eventually™ if this script winds up being useful enough