Photographing without a Camera.

3DWRKSHP is an open curriculum for image production without a camera. It treats 3D in Blender and AI image generation in ComfyUI as one shared workflow, not as competitors.

It's for photographers, designers, agencies and vocational education, from apprentices to professional production. It's written by Matthias Demand, a photographer with 30 years of professional practice — from catalogue photography through CGI to AI — and 17 years of teaching at trade chambers and vocational schools.

→ About

No. All articles are free to read without signing up, and that will stay the case. The tools are free too: Blender and ComfyUI are open source, and the models used have open weights. The RAY-L add-on is available on Gumroad at a pay-what-you-want price starting at $0.

→ RAY-L

Most image generators are diffusion models. During training they learned statistical patterns from billions of image-text pairs; they don't store images.

Every image starts as pure noise that is denoised over 20 to 50 steps. A text encoder translates the prompt into numbers, and through a mechanism called attention the prompt steers every single step. At the end, the VAE translates the result into pixels. The image is computed anew, not assembled from existing images.

→ How AI image generation works

You need three things:

• ComfyUI as a free interface, easiest to install via Stability Matrix
• the model files, for example SDXL or Flux.1
• a computer with enough memory: Nvidia with 8 GB VRAM or more, or Apple Silicon with 16 GB or more — 32 GB or more recommended for Flux

Local means your images and data never leave your machine, there's no subscription, and you have full control over model and parameters. That's exactly what makes results reproducible.

→ What is a model · SDXL setup · Flux.1 dev setup

Because every image starts from different noise. That noise is computed from a number, the seed. With the same seed, the same prompt and the same settings, the same machine produces the same image. In ComfyUI, set the seed to “fixed” for this.

If resolution or step count change, the same seed still gives a different image. The only reliable way to hold a fixed composition is ControlNet.

→ How AI image generation works · Flux.1 Krea dev: iteration and finalization

• SDXL is the accessible entry point: low memory needs, fast, with a mature ControlNet ecosystem.
• Flux.1 dev understands prompts much more precisely and needs more memory.
• Flux.1 Krea dev is the same setup with a markedly photographic look, and the recommendation for RAY-L.
• Flux.2 Klein is very fast (4B: about 36 s per image versus 143 s for SDXL on a MacBook Pro), but has no ControlNet Canny.
• Flux.2 dev delivers the highest quality, but takes about 40 minutes per image.

→ Model types overview

Mostly yes, but two questions need to be kept apart: who owns the images, and may I run the model commercially?

• Flux.1 dev, Krea dev and Flux.2 Klein 9B (FLUX Non-Commercial License): the images you generate belong to you and may be used and sold. The only exception is training a competing model. Running the model itself commercially requires a license from Black Forest Labs.
• Flux.2 Klein 4B (Apache 2.0): free to use, including commercially.

Separate from this are three further questions: copyright in the image, the labeling obligation under the AI Act, and personality rights. Each has its own article. This is guidance, not legal advice.

→ Licensing · Copyright · Labeling · Personality rights

Yes — that's the core of this site. Blender defines what should stay fixed: geometry, camera, perspective, composition. The AI generates what may vary: material, light, atmosphere.

The connection runs through ControlNet Canny: the Blender render becomes an edge image the model follows. The RAY-L add-on turns this into a one-click workflow from Blender to ComfyUI and back, with SDXL, Flux.1 dev and Krea dev. Even simple block geometry is enough, as the Highland Cottage case study shows.

→ RAY-L · Highland Cottage case study