Highlights: Can we measure spatial composition in living room photographs? We score 100 interior images using saliency-based rule-of-thirds alignment, Gemini Vision layout ratings, and CLIP composition prompts — then cross-correlate with color scores from #018 to find rooms that nail both color and layout. Method 1 — Rule of Thirds + Balance: gradient saliency → Gaussian-weig...

Highlights: Can three completely independent methods agree on which living room has the best colors? We rank 500 interior images using Cohen-Or harmonic templates, Hasler-Süsstrunk colorfulness, and CLIP IQA with 44 color-focused prompts — then measure whether they correlate at all. Method 1 — Cohen-Or: K-means palette → saturation-weighted hue histogram → sweep 7 harmonic te...

Highlights: Can you score color quality algorithmically? Not as taste — as math. This post builds a scoring system from first principles: two adjacent color squares, then triplets, then a real room with three spatial regions. We walk through every formula with brand and flag examples you already know, then prove that geometry alone can move the score by five points on an iden...

Highlights: Every computer vision pipeline that touches color starts with the same mistake: using RGB. RGB is built for screens, not for human perception. In this post we build a complete color scoring system for living room images — from the right color space (Lab), through palette extraction (K-means), to a two-color harmony scorer tested on 10 global brand palettes. We dis...

Highlights: Every modern LLM agent — from ChatGPT plugins to Claude tools — relies on a single learned skill: outputting a structured JSON function call instead of free text. In this post we teach that skill to a 3-billion parameter model using QLoRA on a free Google Colab T4. We start from the fundamentals — why fine-tuning, when LoRA, how quantization works — then build the...