Add pipeline and results diagrams to model card

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+figures/painting-pipeline.png filter=lfs diff=lfs merge=lfs -text
+figures/painting-results.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -92,6 +92,9 @@ The kit is designed end-to-end around those questions.
 
 ## Capabilities
 
+![How it works](figures/painting-pipeline.png)
+
+
 ### 1. Ten-class semantic segmentation + substrate head
 The model family is **SegFormer-B2** (the hosted `best.pt` is the facade checkpoint; interior classes are
 C2's); `models.py --arch` also builds MobileNetV3-Large and ResNet-50/101
@@ -218,6 +221,8 @@ Frozen protocol (`benchmark/SPEC.md`, v1.0); every number is tied to one checkpo
 | `best.pt` (sha256 `3ef02176…`) | **yes** | SegFormer-B2, 768 px; semantic + material (drywall) heads; trained for exterior facades |
 | `C2-cal` | release candidate | SegFormer-B2 lineage with wallpaper and condition heads, painted-wall hard negatives and reviewed real interiors; calibrated operating points |
 
+![Measured results](figures/painting-results.png)
+
 ### This release: `best.pt` on real facades
 
 Held-out real facade frames (76) from the 136-frame test split: