Revise README, add pypi action

.github/workflows/release-pypi.yml

@@ -0,0 +1,59 @@
+name: Update internal release
+
+on:
+  push:
+    tags:
+      - 'v*.*.*'
+  pull_request:
+    branches:
+      - main
+    types:
+      - labeled
+      - opened
+      - edited
+      - synchronize
+      - reopened
+
+jobs:
+  release:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Cache dependencies
+        id: pip-cache
+        uses: actions/cache@v4
+        with:
+          path: ~/.cache/pip
+          key: ${{ runner.os }}-pip
+
+      - name: Install dependencies
+        run: |
+          pip install --upgrade pip
+          pip install wheel
+          # NOTE(stes) see https://github.com/pypa/twine/issues/1216#issuecomment-2629069669
+          pip install "packaging>=24.2"
+
+      - name: Checkout code
+        uses: actions/checkout@v3
+
+      - name: Build and publish to Test PyPI
+        if: ${{ (github.ref != 'refs/heads/main') && (github.event.label.name == 'release') }}
+        env:
+          TWINE_USERNAME: __token__
+          TWINE_PASSWORD: ${{ secrets.TEST_PYPI_TOKEN }}
+        run: |
+          make dist
+          ls dist/
+          tar tvf dist/fmpose3d-*.tar.gz
+          python3 -m twine upload --verbose --repository testpypi dist/*
+
+      - name: Build and publish to PyPI
+        if: ${{ github.event_name == 'push' }}
+        env:
+          TWINE_USERNAME: __token__
+          TWINE_PASSWORD: ${{ secrets.PYPI_TOKEN }}
+        run: |
+          make dist
+          ls dist/
+          tar tvf dist/fmpose3d-*.tar.gz
+          python3 -m twine upload --verbose dist/*

README.md

@@ -1,18 +1,27 @@
-# FMPose3D: monocular 3D Pose Estimation via Flow Matching
+# FMPose3D: monocular 3D pose estimation via flow matching
+
+![Version](https://img.shields.io/badge/python_version-3.10-purple)
+[![PyPI version](https://badge.fury.io/py/fmpose3d.svg)](https://badge.fury.io/py/fmpose3d)
+[![License: LApache 2.0](https://img.shields.io/badge/License-Apache2.0-blue.svg)](https://www.gnu.org/licenses/apach2.0)
 
 This is the official implementation of the approach described in the paper:
 
-> [**FMPose3D: monocular 3D Pose Estimation via Flow Matching**](xxx)            
-> Ti Wang, Xiaohang Yu, Mackenzie Weygandt Mathis
+[**FMPose3D: monocular 3D Pose Estimation via Flow Matching**](xxx)            
+Ti Wang, Xiaohang Yu, Mackenzie Weygandt Mathis
 
 <!-- <p align="center"><img src="./images/Frame 4.jpg" width="50%" alt="" /></p> -->
 
 <p align="center"><img src="./images/predictions.jpg" width="95%" alt="" /></p>
 
+## 🚀 TL;DR
+
+FMPose3D replaces slow diffusion models for monocular 3D pose estimation with fast Flow Matching, generating multiple plausible 3D poses via an ODE in just a few steps, then aggregates them using a reprojection-based Bayesian module (RPEA) for accurate predictions, achieving state-of-the-art results on human and animal 3D pose benchmarks.
+
+
 
 ## News!
 
-- [X] Feb 2026: FMPose3D is code and arXiv paper is released - check out the demos here or on our [project page](https://xiu-cs.github.io/FMPose3D/)
+- [X] Feb 2026: FMPose3D code and arXiv paper is released - check out the demos here or on our [project page](https://xiu-cs.github.io/FMPose3D/)
 - [ ] Planned: This method will be integrated into [DeepLabCut](https://www.mackenziemathislab.org/deeplabcut)
 
 ## Installation