Migrate Python bindings from SWIG to nanobind

extras/jetson/README.md

@@ -94,7 +94,10 @@ Tested with a _Jetson AGX Orin Developer Kit_ module.
 - Build _rpt_ package inside container:
 
   ```bash
-  cd /RapidPoseTriangulation/swig/ && make all && cd ../tests/ && python3 test_interface.py && cd ..
+  cd /RapidPoseTriangulation/
+  uv sync --group dev
+  uv run pytest tests/test_interface.py
+  uv build
 
   cd /RapidPoseTriangulation/scripts/ && \
   g++ -std=c++2a -fPIC -O3 -march=native -Wall -Werror -flto=auto \

extras/jetson/dockerfile

@@ -12,10 +12,10 @@ RUN apt-get update && apt-get install -y --no-install-recommends libatlas-base-d
 # Show matplotlib images
 RUN apt-get update && apt-get install -y --no-install-recommends python3-tk
 
-# Install swig and later dependencies
+# Install build dependencies
 RUN apt-get update && apt-get install -y --no-install-recommends build-essential
-RUN apt-get update && apt-get install -y --no-install-recommends swig
 RUN apt-get update && apt-get install -y --no-install-recommends libopencv-dev
+RUN pip3 install --no-cache-dir uv
 
 RUN pip3 install --no-cache-dir scipy
 COPY ./skelda/ /skelda/

extras/ros/rpt3d_wrapper_cpp/src/rpt3d_wrapper.cpp

@@ -239,8 +239,9 @@ void Rpt3DWrapperNode::call_model()
     // Since the prediction is very fast, parallel callback threads only need to wait a short time
     cams_mutex.lock();
     pose_mutex.lock();
-    const auto poses_3d = tri_model->triangulate_poses(
-        all_poses, all_cameras, roomparams, joint_names);
+    PoseBatch2D pose_batch_2d = PoseBatch2D::from_nested(all_poses);
+    auto poses_3d = tri_model->triangulate_poses(
+        pose_batch_2d, all_cameras, roomparams, joint_names).to_nested();
 
     double min_ts = *std::min_element(all_timestamps.begin(), all_timestamps.end());
     this->all_poses_set = std::vector<bool>(cam_ids.size(), false);