weight: -5.0 to 5.0
positive: warmer colors (orange)
negative: cooler colors (blue)
Yeah, you could just do some post processing. Sure. But why solve the problem with a tiny mallet when you can hit it with a giant sledgehammer?
I find some models have to many warm tones. Sometimes when I am inpainting or outpainting, the model struggles with color temperatures beyond its median. Some loras have side effects of making colors warmer and cooler. This is made to combat that without having to do post processing. It is also a new method I am working on for training these, so this was more of an experiment than anything else.
If you like my work, a kind review is always appreciated.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
1from diffusers import AutoPipelineForText2Image
2import torch
3
4pipeline = AutoPipelineForText2Image.from_pretrained('runwayml/stable-diffusion-v1-5', torch_dtype=torch.float16).to('cuda')
5pipeline.load_lora_weights('ostris/color-temperature-slider-lora', weight_name='color_temperature_slider_v1.safetensors')
6image = pipeline('photo of a hippie man playing guitar, award winning photo ').images[0]
For more details, including weighting, merging and fusing LoRAs, check the
documentation on loading LoRAs in diffusers