Add MobileSAM comparison

README.md

@@ -39,14 +39,27 @@ prompts and ground-truth masks as reference:
 
 | Protocol | mIoU |
 |---|---|
-| Crop space, 96x96 (upstream evaluation protocol) | **0.707** |
-| Full image, end-to-end via `LibrePicoSAM3.predict()` | **0.714** |
+| Crop space, 96x96 (upstream evaluation protocol) | **0.692** |
+| Full image, end-to-end via `LibrePicoSAM3.predict()` | **0.697** |
 
-Measured on 500 randomly sampled non-crowd instances (seed 0, no area filter).
+Measured on 2000 randomly sampled non-crowd instances (seed 0, no area filter).
 The PicoSAM3 paper reports 65.45 mIoU on COCO; our sampling and filtering may
 differ from theirs, so we publish the number we measured rather than restating
 theirs as reproduced.
 
+### Against MobileSAM
+
+Same 150 COCO instances, same box prompts, single-threaded CPU:
+
+| Model | Params | mIoU | CPU latency |
+|---|---|---|---|
+| LibrePicoSAM3 | 1.37M | 0.691 | **8.6 ms/prompt** |
+| LibreMobileSAM | 10.13M | **0.800** | 407 ms/prompt |
+
+MobileSAM is the better segmenter; prefer it when a GPU is available or quality
+dominates. PicoSAM3 trades ~11 mIoU points for 7x fewer parameters and ~47x
+lower CPU latency, which is what makes CPU-only and in-sensor deployment viable.
+
 ## Provenance
 
 - **Architecture**: ported from [pbonazzi/picosam3](https://github.com/pbonazzi/picosam3)