recent updates

2026-06-09 18:31:59 +02:00
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+# 05 — Quality Improvement Levers
+
+Three levers control FLUX output quality, in order of impact:
+
+## 1. Prompt (highest impact, zero cost)
+
+Incoherent objects in the frame are almost always prompt bleed — the model fills
+empty or ambiguous space with training-data defaults. Fix by naming every part of
+the frame explicitly.
+
+**Background** — name it, don't imply it:
+- Bad: "living room" (model invents furniture, decor, wall art)
+- Good: "plain cream painted wall with a single frosted sliding glass door"
+
+**Floor material** — always explicit:
+- "plush cream berber carpet" or "light oak hardwood floor"
+- Ambiguous floor → random floor type generated
+
+**Ceiling** — if visible, name it; if not wanted, push it out of frame with a
+lower camera angle:
+- "white drop ceiling with recessed can lights"
+- Or: lower the angle until ceiling exits the frame entirely
+
+**Negative scene elements** — add inline, not as a separate negative prompt
+(FLUX Schnell ignores negative prompts):
+- "no furniture clutter, no decorative objects, no picture frames, no signage"
+- "no cleaning equipment, no machines, no people"
+
+**What not to use:**
+- "wide shot" without a camera angle qualifier — produces flat frontal views
+- Vague room names ("office", "lobby") without specifying what fills the space
+
+## 2. Steps (marginal gain, 2x slower)
+
+FLUX Schnell is distilled to 4 steps. The distillation process compresses
+a full diffusion model's quality into very few steps.
+
+| Steps | Quality change | Time impact |
+|---|---|---|
+| 4 (default) | Baseline | ~4 min/image |
+| 6 | Slightly sharper edges, cleaner fine detail | ~6 min/image |
+| 8 | Diminishing returns past 6 | ~8 min/image |
+
+Not recommended as a first fix. The distillation ceiling is the constraint,
+not step count. Step increases help texture detail but will not fix scene
+incoherence — that requires prompt changes.
+
+KSampler in `gen-images-flux.py`:
+```python
+"steps": 4,   # increase to 6 for detail passes
+```
+
+## 3. Model size (real quality jump, 6x slower on CPU)
+
+| Model | Steps | Quality | CPU time/image |
+|---|---|---|---|
+| FLUX.1 Schnell (current) | 4 | Good depth, some coherence gaps | ~4 min |
+| FLUX.1 Dev (full, non-distilled) | 20-30 | Better coherence, sharper geometry | ~20-30 min |
+
+FLUX Dev would fix most coherence issues. At current CPU-only speed (2GB VRAM
+insufficient), a full 28-image batch would take 9+ hours.
+
+**Practical path to FLUX Dev:**
+- Cloud GPU: RunPod or Vast.ai A100 runs FLUX Dev in ~90 seconds/image
+- Same prompts, same ComfyUI workflow — only model file and step count change
+- Switch `flux1-schnell-Q8_0.gguf` → FLUX Dev GGUF, set steps to 20, cfg to 3.5
+
+## Decision matrix
+
+| Issue | Fix |
+|---|---|
+| Objects that shouldn't be in frame | Prompt: name every surface explicitly |
+| Wrong floor/wall material | Prompt: be specific about material |
+| Flat angle despite prompt | Prompt: add "low-angle", lens mm, "foreground sharp" |
+| Soft edges on carpet fibers | Steps: increase 4 → 6 |
+| Incoherent room geometry | Model: switch to FLUX Dev on cloud GPU |
+| Overall composition wrong | Prompt: camera position + lens + foreground/bokeh split |
+
+## Re-running specific images
+
+To re-run only the problem frames without regenerating all 28:
+
+1. Edit `tools/gen-images-flux.py`
+2. Change the `IMAGES` list to include only the failed image keys
+3. Run: `python3 tools/gen-images-flux.py 2>&1 | tee tools/flux-gen.log`
+4. Run: `python3 tools/convert-to-webp.py` (converts only new JPGs)
+5. Rebuild: `docker compose build --no-cache web && docker compose up -d`