The github repo includes (among other things) a script (relying on python-pptx) to output decomposed layer images into a pptx file “where you can edit and move these layers flexibly.” (I've never user Powerpoint for this, but maybe it is good enough for this and ubiquitous enough that this is sensible?)
I saw some people at a company called Pruna AI got it down to 8 seconds with Cloudflare/Replicate, but I don't know if it was on consumer hardware or an A100/H100/H200, and I don't know if the inference optimization is open-source yet.
with torch.inference_mode():
output = pipeline(**inputs)
output_image = output.images[0]
for i, image in enumerate(output_image):
image.save(f"{i}.png")
Unless it's a joke that went over my head or you're talking about some other GitHub readme (there's only one GitHub link in TFA), posting an outright lie like this is not cool.
The word "powerpoint" is not there, however this text is:
“The following scripts will start a Gradio-based web interface where you can decompose an image and export the layers into a pptx file, where you can edit and move these layers flexibly.”
Oh okay I missed it, sorry. But that’s just using a separate python-pptx package to export the generated list of images to a .pptx file, not something inherent to the model.
...of all the possible formats, it outputs.. a powerpoint presentation..? What.
The github repo includes (among other things) a script (relying on python-pptx) to output decomposed layer images into a pptx file “where you can edit and move these layers flexibly.” (I've never user Powerpoint for this, but maybe it is good enough for this and ubiquitous enough that this is sensible?)
Lol, right?!?! I would've expected sequential PNGs followed by SVGs once the model improved.
That's what the example code at https://old.reddit.com/r/StableDiffusion/comments/1pqnghp/qw... generates. You get 0.png, 1.png ... n.png, where n= the requested number of layers-1.
It'll drop a 600W RTX 6000 to its knees for about a minute, but it does work.
I saw some people at a company called Pruna AI got it down to 8 seconds with Cloudflare/Replicate, but I don't know if it was on consumer hardware or an A100/H100/H200, and I don't know if the inference optimization is open-source yet.
I don't see the word powerpoint anywhere in https://github.com/QwenLM/Qwen-Image-Layered, I only see a code snippet saving a bunch of PNGs:
Unless it's a joke that went over my head or you're talking about some other GitHub readme (there's only one GitHub link in TFA), posting an outright lie like this is not cool.> I don't see the word powerpoint anywhere in https://github.com/QwenLM/Qwen-Image-Layered,
The word "powerpoint" is not there, however this text is:
“The following scripts will start a Gradio-based web interface where you can decompose an image and export the layers into a pptx file, where you can edit and move these layers flexibly.”
Oh okay I missed it, sorry. But that’s just using a separate python-pptx package to export the generated list of images to a .pptx file, not something inherent to the model.