README: onnx repo is public, per-task folders

README.md

@@ -29,7 +29,7 @@ The model fixes a 1024×768 input tensor (NCHW with H=1024, W=768, a portrait ca
 
 ## CPU-friendly ONNX exports
 
-Companion repo: [`WeReCooking/sapiens2-onnx`](https://huggingface.co/WeReCooking/sapiens2-onnx) (private). File naming `<task>_<size>_<precision>.onnx` plus a `.onnx.data` external sidecar. 15 ONNX artifacts shipped: 12 covering 0.4b/0.8b/1b (fp16 for seg-0.4b, fp32 for the rest), and 3 new 5B int8 files (seg, normal, pointmap). Cosine similarity vs PyTorch fp32 is 0.999 or better on all shipped variants.
+Companion repo: [`WeReCooking/sapiens2-onnx`](https://huggingface.co/WeReCooking/sapiens2-onnx) (public). Files live in per-task folders `seg/`, `normal/`, `pointmap/`, `pose/`. Each variant is `<task>/<task>_<size>_<precision>.onnx` plus a `.onnx.data` external sidecar. 15 ONNX artifacts shipped: 12 covering 0.4b/0.8b/1b (fp16 for seg-0.4b, fp32 for the rest), and 3 new 5B int8 files (seg, normal, pointmap). Cosine similarity vs PyTorch fp32 is 0.999 or better on all shipped variants.
 
 Turnkey CLI built into `app.py` (no sapiens2 / PyTorch dep needed; install `requirements.txt`):