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DISTS-Sq Smoke Checkpoint

dists_sq_placeholder_v0 is a tiny-AI smoke checkpoint for the dists_sq full-reference extractor. It locks the DISTS host ABI and lets libvmaf test the two-input ONNX path while the real Ding et al. weights are tracked separately as T7-DISTS-followup.

Model

Field Value
Registry id dists_sq_placeholder_v0
File model/tiny/dists_sq.onnx
Sidecar model/tiny/dists_sq.json
SHA-256 ec8433e8c7c6a33ef3032a6e4538833e0bbb59de9f088054bbcb3be0e371ee55
ONNX opset 17
License BSD-3-Clause-Plus-Patent
Generator scripts/gen_dists_sq_placeholder_onnx.py

Contract

Inputs:

Name Type Shape Meaning
ref float32 [1, 3, H, W] ImageNet-normalised RGB reference frame
dist float32 [1, 3, H, W] ImageNet-normalised RGB distorted frame

Output:

Name Type Shape Meaning
score float32 scalar Mean squared distance between ref and dist tensors

The extractor publishes the scalar as the per-frame dists_sq feature. The host side accepts planar YUV 4:2:0 / 4:2:2 / 4:4:4 at 8, 10, 12, or 16 bpc and normalises high-bit-depth samples into the same RGB8 tensor contract before ImageNet normalisation.

Intended Use

Use this checkpoint for build, packaging, registry, and smoke-test coverage of the dists_sq extractor. It proves that model lookup, named two-input binding, dynamic image dimensions, and scalar output collection work through the tiny-AI runtime.

Do not use this checkpoint for perceptual-quality decisions. It is not a trained DISTS model and intentionally sets "smoke": true in model/tiny/registry.json.

Regeneration

.venv/bin/python scripts/gen_dists_sq_placeholder_onnx.py

The generator writes the ONNX file, sidecar JSON, and registry entry in one pass. Re-run registry validation after regeneration:

.venv/bin/python ai/scripts/validate_model_registry.py model/tiny/registry.json

Limitations

The graph is Sub -> Mul -> ReduceMean; it contains no learned feature backbone and no DISTS texture/structure statistics. The production follow-up must replace the placeholder with upstream-derived DISTS-compatible weights, pin a new SHA-256, update this model card, and verify representative scores against an independent reference.