Technology

Guided by φ

φ is Deep Phi’s proprietary measure of local structure. Every phiXplorer model is trained under its guidance — and ships without ever revealing the formula.

From pixels to a guided result

Image

Any image, exactly as it is — no setup, no labels.

φ — proprietary

A deterministic structural measure, computed inside Deep Phi.

Structure map

A dense map: hot on structure, dark on flat areas.

Guided model

A featherweight network that acts only where φ points.

Result

φ, in action

φ scores, at every point of an image, how rich the local structure is — independent of meaning. The formula stays inside Deep Phi; only its behaviour ships in the model.

Image and its φ map — Feathers, beak and eye light up; the blurred background stays ignored.

Same pixels in, same map out — no randomness, nothing hallucinated. φ is a deterministic measure you can audit, not a generative model you have to trust.

Deterministic by nature

φ as a relief

Read an image as a landscape: peaks where structure is dense — feathers, edges, texture — plains where it is flat. The very same pixels always produce the very same surface. A measurement, drawn to the pixel.

The image as a structural landscape — peaks are rich zones, plains are flat areas.

The same values as isolines — a topographic map of structure, traced to the pixel.

A black box, on purpose

You see φ’s output — the maps, the relief, the results — never its formula. The behaviour ships inside the model; the recipe stays at Deep Phi. That is how phiXplorer can be free to try while the core stays protected.

Try it in the studio