Image Synthesis
Image synthesis is the base feature of DiffSynth Studio. We can generate images with very high resolution.
OmniGen
OmniGen is a text-image-to-image model, you can synthesize an image according to several given reference images.
Example: FLUX
Example script: flux_text_to_image.py
and flux_text_to_image_low_vram.py
(low VRAM).
The original version of FLUX doesn't support classifier-free guidance; however, we believe that this guidance mechanism is an important feature for synthesizing beautiful images. You can enable it using the parameter cfg_scale
, and the extra guidance scale introduced by FLUX is embedded_guidance
.
Example: Stable Diffusion
Example script: sd_text_to_image.py
LoRA Training: ../train/stable_diffusion/
Example: Stable Diffusion XL
Example script: sdxl_text_to_image.py
LoRA Training: ../train/stable_diffusion_xl/
Example: Stable Diffusion 3
Example script: sd3_text_to_image.py
LoRA Training: ../train/stable_diffusion_3/
Example: Kolors
Example script: kolors_text_to_image.py
LoRA Training: ../train/kolors/
Kolors also support the models trained for SD-XL. For example, ControlNets and LoRAs. See kolors_with_sdxl_models.py
LoRA: https://civitai.com/models/73305/zyd232s-ink-style
ControlNet: https://huggingface.co/xinsir/controlnet-union-sdxl-1.0
Example: Hunyuan-DiT
Example script: hunyuan_dit_text_to_image.py
LoRA Training: ../train/hunyuan_dit/
Example: Stable Diffusion XL Turbo
Example script: sdxl_turbo.py
We highly recommend you to use this model in the WebUI.