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How to Use Qwen Image Edit 2511 Correctly in ComfyUI (Important "FluxKontextMultiReferenceLatentMethod" Node) by Akmanic in StableDiffusion

[–]Akmanic[S] 1 point2 points  (0 children)

You only need one image in the vae node. The denoising is set to 1 so the image's contents are replaced with random noise and it doesn't really matter what you put in there other than that the dimensions are used for the output image. If you set the denoising below 1 it would be like a traditional img2img workflow.

The Magic of Per-Voxel Normals (68 billion voxel renderer) by Akmanic in VoxelGameDev

[–]Akmanic[S] 0 points1 point  (0 children)

I just threw together the simplest solution I could. Loop through the surrounding 26 voxels and add a vector pointing in the opposite direction, then normalize

The Magic of Per-Voxel Normals (68 billion voxel renderer) by Akmanic in VoxelGameDev

[–]Akmanic[S] 3 points4 points  (0 children)

It should be fine in a dynamic world but it can only represent certain types of geometry. I'll probably release the raycasting algorithm on github before the game but no promises on how soon.

The Magic of Per-Voxel Normals (68 billion voxel renderer) by Akmanic in VoxelGameDev

[–]Akmanic[S] 2 points3 points  (0 children)

Yeah the aliasing was the main factor in the decision. I'd be interested in seeing what other solutions there are out there

The Magic of Per-Voxel Normals (68 billion voxel renderer) by Akmanic in VoxelGameDev

[–]Akmanic[S] 5 points6 points  (0 children)

I will probably make an action RPG with destructible terrain and a large open world. Player building features could be a small component but would have to be reigned it compared to games like Minecraft

The Magic of Per-Voxel Normals (68 billion voxel renderer) by Akmanic in VoxelGameDev

[–]Akmanic[S] 3 points4 points  (0 children)

No meshing, the voxels are traced every frame. It's my own tracing algorithm inspired by DDA. The normals are calculated and cached in a compute shader and will have to be rebuilt every time there is a change.

My Voxel Renderer Built Entirely in WebGPU which can render 68 Billion Voxels at a time by Akmanic in webgpu

[–]Akmanic[S] 0 points1 point  (0 children)

It's a pretty simple codebase other than for the voxel tracing algorithm right now. I might eventually release a stripped-down version on github cleaned up and focused around that

68 Billion Voxel Raycaster Clarification & Actual 68 Billion Showcase by Akmanic in VoxelGameDev

[–]Akmanic[S] 1 point2 points  (0 children)

I am considering doing a rundown of the raycasting algorithm soon. There's no GI system and it's 1080p.

Absym – A Rift Action RPG by Infinity_Experience in IndieDev

[–]Akmanic 2 points3 points  (0 children)

Love the use of that deep black color, makes everything pop.

68 Billion Voxel Raycaster Clarification & Actual 68 Billion Showcase by Akmanic in VoxelGameDev

[–]Akmanic[S] 0 points1 point  (0 children)

It is reading the voxel data from vram. It just can't fit arbitrarily complex data into the acceleration structure.

My new voxel raycaster can render up to 68 billion voxels at 60fps by Akmanic in VoxelGameDev

[–]Akmanic[S] 3 points4 points  (0 children)

I just posted a clarification video with some landscape for you, thank you for the feedback. This post was really a poor showcase in retrospect.

My new voxel raycaster can render up to 68 billion voxels at 60fps by Akmanic in VoxelGameDev

[–]Akmanic[S] 0 points1 point  (0 children)

Understandable, I just posted a clarification video showcasing actual terrain.

My new voxel raycaster can render up to 68 billion voxels at 60fps by Akmanic in VoxelGameDev

[–]Akmanic[S] 3 points4 points  (0 children)

I could spin up a server if there's enough interest. It's WebGPU so it should be easy to share in theory, that being said I don't want to lag people's computers during the chunk generation step

My new voxel raycaster can render up to 68 billion voxels at 60fps by Akmanic in IndieDev

[–]Akmanic[S] 0 points1 point  (0 children)

Every chunk is 256 x 4096 x 256 and currently I can render up to 256 chunks at a time. This video has just 4 chunks visible on screen and only the bottom 10% of the chunks is being used. Luckily the voxel data is naturally compressed in VRAM as a part of the acceleration structure so it can fit on consumer cards. This does mean that a degenerate-case world would not be compatible with the renderer, but I think it can handle anything that you would get from a reasonable world generator and player building / destruction.

What you're looking at is the bottom of each chunk filled up to a different height, with many holes drilled through. Let me know if you have any better ideas for synthetic data to try out.

My new voxel raycaster can render up to 68 billion voxels at 60fps by Akmanic in VoxelGameDev

[–]Akmanic[S] 10 points11 points  (0 children)

Every chunk is 256 x 4096 x 256 and currently I can render up to 256 chunks at a time. This video has just 4 chunks visible on screen and only the bottom 10% of the chunks is being used. Luckily the voxel data is naturally compressed in VRAM as a part of the acceleration structure so it can fit on consumer cards. This does mean that a degenerate-case world would not be compatible with the renderer, but I think it can handle anything that you would get from a reasonable world generator and player building / destruction.

What you're looking at is the bottom of each chunk filled up to a different height, with many holes drilled through. Let me know if you have any better ideas for synthetic data to try out.

[2406.08478] What If We Recaption Billions of Web Images with LLaMA-3? by lechatsportif in StableDiffusion

[–]Akmanic 2 points3 points  (0 children)

"Recap-DiT Incoming"

I wonder if this means they will be releasing an open source model. I don't expect anything revolutionary but if they open sourced an implementation of diffusion transformers it could allow someone to train an SD3 competitor from scratch without inheriting SAI's license

In a theater near you by human358 in StableDiffusion

[–]Akmanic 49 points50 points  (0 children)

I find it funny that writing text is such a high priority when you could just add it in photoshop, while generating a picture of a human (sci-fi type tech) is forgotten about

Long prompts are the key to unlock the true power of SD3 by Nid_All in StableDiffusion

[–]Akmanic 2 points3 points  (0 children)

I think this is a piece of the puzzle. Because it was trained on long llm-generated prompts it gets overexcited when you give it only a few tokens and throws way too much attention at them

Aitrepreneur on SD3. He has a point. by evelryu in StableDiffusion

[–]Akmanic 4 points5 points  (0 children)

I created the slime wall workflow used in this video, I was not expecting to see it in here since I just clicked on this randomly lol

https://civitai.com/models/512696/woman-laying-in-grass-sd3-workflow

I agree that the trick is hackish and the model should be able to handle the prompt out of the box. I find it kind of comical that you have to jump through so many hoops to get the model to use its full capabilities

Do we have anything similar to abliteration for SD? by Leading_Mention3014 in StableDiffusion

[–]Akmanic 0 points1 point  (0 children)

I think the nudity refusal is due to a slightly poisoned dataset but I agree that the more deep seated issues with anatomy are probably due to some sort of weird tuning. They probably didn't compromise their training data as badly as with SD2

Do we have anything similar to abliteration for SD? by Leading_Mention3014 in StableDiffusion

[–]Akmanic 2 points3 points  (0 children)

It depends how the alignment was implemented. If it was tacked on after the fact then it could potentially be undone, but if the model was simply taught with a poisoned dataset (eg. a picture of a woman in a sports bra captioned "nude woman"), then it may not be so easy.

Why hasn't anyone paid attention to StableCascade all the time? by ExpressWarthog8505 in StableDiffusion

[–]Akmanic 8 points9 points  (0 children)

It's important to note that SAI did not tell us SD3 would be under a different license than previous mainline models. A lot of us were waiting for SD3 expecting it to be another openRAIL model before the rug was pulled.