Sexiam - Txt2Img & Img2Img
This is not meant to be an overly complex ComfyUI workflow.
The goal is to give beginner and intermediate users a flexible two-stage generation setup without overwhelming them with extra systems, heavy post-processing chains, or complicated node networks. I do a lot of Img2Img work across different styles using Illustrious-based models, and I often found myself switching between Txt2Img and Img2Img setups.
I did not want separate redundant node networks doing almost the same thing, but I also did not want complicated switches that require remembering assigned numbers, bypassing groups, or breaking creative flow.
The solution was to reduce the main mode switching to a simple On/Off system using boolean and if/else nodes.
When the switch is off, the workflow can run as Txt2Img.
When the switch is on, it can run as Img2Img.
How to Use Workflow
Load Models & Prompt
1. Load Checkpoint!
2. Load External VAE model
3. Turn the "Use External VAE" on or off
(Optional) Turn the "Use External VAE" node to true if you want to use the VAE model instead of the built-in VAE that comes with the checkpoint.
4. Load your LoRA models in the "Power LoRA Loader" node.
1. Press the add LoRA button.
2. Select a LoRA from the list.
3. To find a LoRA’s trigger words or Civitai link, right-click the LoRA in the node and select "Show Info". You can then select the trigger words you want and press copy in the "trained words" cell.
5. Enter your positive and negative prompt.
The positive prompt is broken up into three sections labeled Suffix, Body, and Prefix. This is to give you the flexibility to set your quality tags, LoRA trigger words, and effects tags without affecting the main prompt in the Body text node. This way you can copy and paste your character and scene tags without affecting your other modifier tags.
The text encoder node network is also broken up into three separate positive prompt nodes and combined with a Condition Concat function so that checkpoints with smaller token limits have greater flexibility.
KSampler - 1st Stage
6. Turn the "Txt2Img" node ON if you want to use standard text-to-image processing.
(Optional) Turn the "Txt2Img" node OFF if you want to use Img2Img processing instead.
7. Turning ON the "Upscale by Model" switch will result in the input image being upscaled 4x by an upscaler model and then downscaled to the targeted latent space dimensions. This process can take longer than a simple latent upscale.
(Optional) Turning OFF the "Upscale by Model" switch will result in the image being upscaled in latent space instead of pixel space. This is a less resource-intensive and faster process than upscale by model.
8. The Resolution Master node allows you to perform a number of processes automatically when adjusting the latent space size of the generation.
At the bottom of the node are a number of presets that represent most of the most-used checkpoints and their latent space sizes.
In the workflow, the "Auto-Detect" option is turned on, and any image loaded into the "Load Image" node will trigger it. This will result in the node picking the closest standard size for your model.
You can also upscale the generation dimensions by a factor or by total megapixels.
The "Swap" button will swap the width and height.
The 2D preview of the node will also show you what the orientation of the generation will look like before generation begins.
9. Adjust the denoise value to your preferred setting.
If you set the "Txt2Img" node to true, then the denoise setting of the KSampler will automatically be set to 1.0.
If selecting Img2Img by turning the "Txt2Img" node to false, then you will need to manually adjust the setting on the pink 2D slider at the top of the KSampler - 1st Stage group.
The 2D slider will adjust the integer numbers to floats automatically. For instance, if you set the slider to 70, then the KSampler will read it as 0.7 in the denoise setting.
If you're only wanting small changes to the input image, then a setting lower than 50 would be recommended.
If you're making large changes to the image, then a setting of 60 to 70 would be recommended.
If you're curious about using Img2Img with a high denoise strength for new creative compositions, then you can refer to my article explaining the process Underpainting for AI .
10. Load your preferred upscaler model and upscaling method for either upscale by model or upscale by latent.
11. Adjust the KSampler settings to your preferred setup.
KSampler - 2nd Stage
This group will upscale the first stage and result in more detail without the need for detailer nodes.
12. Adjust the denoise value to a lower setting for the upscale to work.
A setting over 40 isn't recommended on most Illustrious checkpoints since you will get big changes to the upscaled image.
To avoid changes to eyes, details, and composition, a denoise setting below 40 is recommended.
13. Adjust the "Upscale Image By" node to your preferred upscale factor.
A setting of 2 means the image size will be doubled, and 1.5 means 1.5x or 50% bigger.
Depending on how much VRAM you have, you may need to adjust this to a lower value like 1.5.
14. Load your preferred upscaler model and upscaling method.
15. Adjust the settings for the second-stage KSampler to your preferred settings.
Generally, you can set the CFG of the second stage to a lower setting than you did with the first stage.
Setting the CFG too low may result in a color shift, though.
16. The "SD Prompt Saver" is set up to organize your generations by Model Name folder.
The saved images should also work with Civitai's system for metadata retrieval.
