Spaces:
Running
on
L40S
Running
on
L40S
File size: 7,510 Bytes
4450790 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 |
## ComfyUI-to-Python-Extension
![banner](images/comfyui_to_python_banner.png)
The `ComfyUI-to-Python-Extension` is a powerful tool that translates [ComfyUI](https://github.com/comfyanonymous/ComfyUI) workflows into executable Python code. Designed to bridge the gap between ComfyUI's visual interface and Python's programming environment, this script facilitates the seamless transition from design to code execution. Whether you're a data scientist, a software developer, or an AI enthusiast, this tool streamlines the process of implementing ComfyUI workflows in Python.
**Convert this:**
![SDXL UI Example](images/SDXL-UI-Example.jpg)
**To this:**
```
import random
import torch
import sys
sys.path.append("../")
from nodes import (
VAEDecode,
KSamplerAdvanced,
EmptyLatentImage,
SaveImage,
CheckpointLoaderSimple,
CLIPTextEncode,
)
def main():
with torch.inference_mode():
checkpointloadersimple = CheckpointLoaderSimple()
checkpointloadersimple_4 = checkpointloadersimple.load_checkpoint(
ckpt_name="sd_xl_base_1.0.safetensors"
)
emptylatentimage = EmptyLatentImage()
emptylatentimage_5 = emptylatentimage.generate(
width=1024, height=1024, batch_size=1
)
cliptextencode = CLIPTextEncode()
cliptextencode_6 = cliptextencode.encode(
text="evening sunset scenery blue sky nature, glass bottle with a galaxy in it",
clip=checkpointloadersimple_4[1],
)
cliptextencode_7 = cliptextencode.encode(
text="text, watermark", clip=checkpointloadersimple_4[1]
)
checkpointloadersimple_12 = checkpointloadersimple.load_checkpoint(
ckpt_name="sd_xl_refiner_1.0.safetensors"
)
cliptextencode_15 = cliptextencode.encode(
text="evening sunset scenery blue sky nature, glass bottle with a galaxy in it",
clip=checkpointloadersimple_12[1],
)
cliptextencode_16 = cliptextencode.encode(
text="text, watermark", clip=checkpointloadersimple_12[1]
)
ksampleradvanced = KSamplerAdvanced()
vaedecode = VAEDecode()
saveimage = SaveImage()
for q in range(10):
ksampleradvanced_10 = ksampleradvanced.sample(
add_noise="enable",
noise_seed=random.randint(1, 2**64),
steps=25,
cfg=8,
sampler_name="euler",
scheduler="normal",
start_at_step=0,
end_at_step=20,
return_with_leftover_noise="enable",
model=checkpointloadersimple_4[0],
positive=cliptextencode_6[0],
negative=cliptextencode_7[0],
latent_image=emptylatentimage_5[0],
)
ksampleradvanced_11 = ksampleradvanced.sample(
add_noise="disable",
noise_seed=random.randint(1, 2**64),
steps=25,
cfg=8,
sampler_name="euler",
scheduler="normal",
start_at_step=20,
end_at_step=10000,
return_with_leftover_noise="disable",
model=checkpointloadersimple_12[0],
positive=cliptextencode_15[0],
negative=cliptextencode_16[0],
latent_image=ksampleradvanced_10[0],
)
vaedecode_17 = vaedecode.decode(
samples=ksampleradvanced_11[0], vae=checkpointloadersimple_12[2]
)
saveimage_19 = saveimage.save_images(
filename_prefix="ComfyUI", images=vaedecode_17[0]
)
if __name__ == "__main__":
main()
```
## Potential Use Cases
- Streamlining the process for creating a lean app or pipeline deployment that uses a ComfyUI workflow
- Creating programmatic experiments for various prompt/parameter values
- Creating large queues for image generation (For example, you could adjust the script to generate 1000 images without clicking ctrl+enter 1000 times)
- Easily expanding or iterating on your architecture in Python once a foundational workflow is in place in the GUI
## V1.3.0 Release Notes
- Generate .py file directly from the ComfyUI Web App
![Save As Script](images/save_as_script.png)
## V1.2.1 Release Notes
- Dynamically change `comfyui_to_python.py` parameters with CLI arguments
- Hotfix to handle nodes that accept kwargs.
## V1.2.0 Release Notes
- Updates to adhere to latest changes from `ComfyUI`
## V1.0.0 Release Notes
- **Use all the custom nodes!**
- Custom nodes are now supported. If you run into any issues with code execution, first ensure that the each node works as expected in the GUI. If it works in the GUI, but not in the generated script, please submit an issue.
## Installation
1. Navigate to your `ComfyUI/custom_nodes` directory
2. Clone this repo
```bash
git clone https://github.com/pydn/ComfyUI-to-Python-Extension.git
```
After cloning the repo, your `ComfyUI` directory should look like this:
```
/comfy
/comfy_extras
/custom_nodes
--/ComfyUI-to-Python-Extension
/input
/models
/output
/script_examples
/web
.gitignore
LICENSE
README.md
comfyui_screenshot.png
cuda_mollac.py
execution.py
extra_model_paths.yaml.example
folder_paths.py
latent_preview.py
main.py
nodes.py
requirements.txt
server.py
```
## Web App Use
1. Launch ComfyUI
2. Load your favorite workflow and click `Save As Script`
![Save As Script](images/save_as_script.png)
3. Type your desired file name into the pop up screen.
4. Move .py file from your downloads folder to your `ComfyUI` directory.
5. Now you can execute the newly created .py file to generate images without launching a server.
## CLI Usage
1. Navigate to the `ComfyUI-to-Python-Extension` folder and install requirements
```bash
pip install -r requirements.txt
```
2. Launch ComfyUI, click the gear icon over `Queue Prompt`, then check `Enable Dev mode Options`. **THE SCRIPT WILL NOT WORK IF YOU DO NOT ENABLE THIS OPTION!**
![Enable Dev Mode Options](images/dev_mode_options.jpg)
3. Load up your favorite workflows, then click the newly enabled `Save (API Format)` button under Queue Prompt
4. Move the downloaded .json workflow file to your `ComfyUI/ComfyUI-to-Python-Extension` folder
5. If needed, add arguments when executing `comfyui_to_python.py` to update the default `input_file` and `output_file` to match your .json workflow file and desired .py file name. By default, the script will look for a file called `workflow_api.json`. You can also update the `queue_size` variable to your desired number of images that you want to generate in a single script execution. By default, the scripts will generate 10 images. Run `python comfyui_to_python.py --help` for more details.
6a. Run the script with default arguments:
```bash
python comfyui_to_python.py
```
6b. Run the script with optional arguments:
```bash
python comfyui_to_python.py --input_file "workflow_api (2).json" --output_file my_workflow.py --queue_size 100
```
7. After running `comfyui_to_python.py`, a new .py file will be created in the current working directory. If you made no changes, look for `workflow_api.py`.
8. Now you can execute the newly created .py file to generate images without launching a server.
|