Image synthesis is the base feature of DiffSynth Studio. We can generate images with very high resolution.
OmniGen is a text-image-to-image model, you can synthesize an image according to several given reference images.
Reference image 1 | Reference image 2 | Synthesized image |
---|---|---|
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
.
1024*1024 (original) | 1024*1024 (classifier-free guidance) | 2048*2048 (highres-fix) |
---|---|---|
Example script: sd_text_to_image.py
LoRA Training: ../train/stable_diffusion/
512*512 | 1024*1024 | 2048*2048 | 4096*4096 |
---|---|---|---|
Example script: sdxl_text_to_image.py
LoRA Training: ../train/stable_diffusion_xl/
1024*1024 | 2048*2048 |
---|---|
Example script: sd3_text_to_image.py
LoRA Training: ../train/stable_diffusion_3/
1024*1024 | 2048*2048 |
---|---|
Example script: kolors_text_to_image.py
LoRA Training: ../train/kolors/
1024*1024 | 2048*2048 |
---|---|
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
Base model | with LoRA (alpha=0.5) | with LoRA (alpha=1.0) | with LoRA (alpha=1.5) |
---|---|---|---|
ControlNet: https://huggingface.co/xinsir/controlnet-union-sdxl-1.0
Reference image | Depth image | with ControlNet | with ControlNet |
---|---|---|---|
Example script: hunyuan_dit_text_to_image.py
LoRA Training: ../train/hunyuan_dit/
1024*1024 | 2048*2048 |
---|---|
Example script: sdxl_turbo.py
We highly recommend you to use this model in the WebUI.
"black car" | "red car" |
---|---|