A dim tunnel full of graffiti is a great place to find inspiration for your next perfect portrait.
All images are generated with Colab notebook included in the Quick Start Guide.
Positive prompt:
100mm, cover photo portrait, [liza soberano: emma watson:0.7], skirt, stocking,4 k, (dimly lit urban tunnel filled with beautiful graffiti:1.1), liam wong, directional lighting
Negative prompt:
| CFG scale | 7 |
| Image size | 512×704 |
| Sampling steps | 30 |
| Seed | -1 |
| Face restoration | None |
| Sampling method | Euler a |
| Model | F222 |
| Recommended GUI | AUTOMATIC1111 |
Technical notes
- I intended to get a full body realistic portrait. The keywords photo portrait and the portrait image size (512×704) helped. The keyword skirt and stocking helped to make the legs visible.
- Perhaps due to the keyword tunnel, the initial prompt generated a subject too far away. Close up keyword made it too close, making the tunnel not visible. Finally I found the right balance with the keyword cover.
- It was hopeless to generate a good face with that small face size. All faces were fixed with a second inpainting step.
- To finely control the look of my model, I used keyword blending to mix two faces. I chose Liza Soberano for an asian look, and blend with Emma Watson to make the facial feature sharper.
- Keyword stocking is used to make the lower body more interesting.
Structured Stable Diffusion courses
Learn A111 and ComfyUI step-by-step.
Inpainting settings
You will get pretty bad faces because Stable Diffusion is not good at generating small faces.
Inpaint with original prompt and model. The important parameters are
- Mask: The face only
- Prompt: (same as original)
- Mask content: Original
- Inpaint at full resolution
but with full resolution on and face restoration.
Below is a screenshot of the full setting.
Your are a hero, I’m following every single post. Like the detailed explanation in the workflow.
Keeping going!
Thank you Alexander! Comments like this keeps me going!!