pink or green/orange dots in generated images

#3
by thomasefer - opened

First, thanks so much for this amazing model! I have a question though:

Is the following effect that I get on nearly all generated images wanted (watermark/fingerprint) or a (possibly avoidable) artifact of teh generation?

image.png

image.png

ByteDance org

Which model / checkpoint are you using?
Is it from diffusers or ComfyUI?
Are you sure you have use the correct sampler setting as in the documentation?

Thanks for the quick response!

I am using the provided sample code for diffusers (stable-diffusion-xl-base-1.0 with the unet.load_state_dict method as provided).

I got these results with sdxl_lightning_4step_unetand 4 inference steps, as well as sdxl_lightning_8step_unetand 8 inference steps accordingly.

What do you mean by sampler? I use EulerDiscreteScheduler with timestep_spacing="trailing" as in the demo code.

guidance_scale is also set to 0 as instructed.

width and height are default (1024 iir. correctly)

It might be related to watermarking problem from diffusers lib, not from the SDXL-Lightning models.
Please check https://github.com/huggingface/diffusers/issues/6292 and https://github.com/huggingface/diffusers/issues/4074

@seravee008 Thanks a lot! That seems to be the case indeed!

Adding

class NoWatermark:
    def apply_watermark(self, img):
        return img
pipe.watermark = NoWatermark()

solved that problem for me (and got rid of any steganographic tracking - I assume this is still OK with the Stable Diffusion license...)

@PeterL1n - maybe these lines could be added to the example code?

ByteDance org
edited Feb 21

@thomasefer

output (23).png

The images I generated do not have this artifact. I am using diffusers==0.26.3. Maybe it is already fixed in the latest version?

Hmmm... Somehow I am stuck with diffusers==0.21.1 as it seems... Then sorry for the false alarm!

thomasefer changed discussion status to closed

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