Snapshot: full project state

README.md

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+# Vision Bench — Android-Control Vision Model Benchmark
+
+Measured (not vibes) comparison of tiny Ollama vision models for driving
+Android via ADB/MCP. Ground truth = uiautomator XML dumps; 8 real device
+situations × 4 tasks × 4 models = 320 scored calls.
+
+## Scores (identify / ground / agent JSON)
+- **qwen2.5vl:3b — 1.00 / 0.57 (0.91 visible) / 0.62** ← winner
+- granite3.2-vision:2b — 0.62 / 0.00 / 0.38
+- llava-phi3:3.8b — 0.62 / 0.27 / 0.00
+- moondream:1.8b — 0.12 / 0.00 / 0.00
+
+## Files
+`bench.py` harness · `capture_situations.sh` ground-truth capture ·
+`final_scores.py` / `analyze.py` scoring · `bench_results.jsonl` raw data ·
+`REPORT.md` full write-up · `android_control_demo.py` working agent demo
+