Fixing installation.

ros/README-Jetson-Setup.md

@@ -1,42 +0,0 @@
-# ROS
-
-<br>
-
-## Build
-
-- Install system: \
-  (https://developer.nvidia.com/embedded/learn/get-started-jetson-agx-orin-devkit)
-
-- Install _docker_: \
-  (https://docs.docker.com/engine/install/ubuntu/#install-using-the-convenience-script)
-
-- Install _nvidia-container-toolkit_: \
-  (https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/latest/install-guide.html)
-
-- Enable GPU-access for docker building:
-
-  Run `sudo nano /etc/docker/daemon.json` and add:
-
-  ```json
-  {
-    "runtimes": {
-      "nvidia": {
-        "path": "nvidia-container-runtime",
-        "runtimeArgs": []
-      }
-    },
-    "default-runtime": "nvidia"
-  }
-  ```
-
-  Restart docker: `sudo systemctl restart docker`
-
-- Install _vs-code_: \
-  (https://code.visualstudio.com/docs/setup/linux)
-
-
-- Test docker is working: \
-  ```bash
-  sudo docker run -it --rm --net=host --runtime nvidia -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix nvcr.io/nvidia/l4t-base:35.4.1
-  sudo docker run --runtime nvidia -it --rm --network=host nvcr.io/nvidia/l4t-pytorch:r35.1.0-pth1.11-py3
-  ```

ros/README-JetsonOrin-Setup.md

@@ -0,0 +1,84 @@
+# Setup with Nvidia-Jetson-Orin
+
+Initial setup and installation of _RapidPoseTriangulation_ on a _Nvidia Jetson_ device. \
+Tested with a _Jetson AGX Orin Developer Kit_ module.
+
+<br>
+
+## Base installation
+
+- Install newest software image: \
+  (https://developer.nvidia.com/sdk-manager)
+
+- Initialize system: \
+  (https://developer.nvidia.com/embedded/learn/get-started-jetson-agx-orin-devkit)
+
+- Install basic tools:
+  ```bash
+  sudo apt install -y curl nano wget git
+  sudo apt install -y terminator
+  ```
+
+- Enable _docker_ without _sudo_: \
+  (https://docs.docker.com/engine/install/linux-postinstall/#manage-docker-as-a-non-root-user)
+
+- Enable GPU-access for docker building:
+
+  Run `sudo nano /etc/docker/daemon.json` and add:
+
+  ```json
+  {
+    "runtimes": {
+      "nvidia": {
+        "args": [],
+        "path": "nvidia-container-runtime"
+      }
+    },
+    "default-runtime": "nvidia"
+  }
+  ```
+
+  Restart docker: `sudo systemctl restart docker`
+
+- Install _vs-code_: \
+  (https://code.visualstudio.com/docs/setup/linux)
+
+
+- Test docker is working:
+
+  ```bash
+  docker run -it --rm --runtime=nvidia --network=host -e DISPLAY=$DISPLAY -v /tmp/.X11-unix/:/tmp/.X11-unix nvcr.io/nvidia/l4t-base:r36.2.0
+  docker run -it --rm --runtime=nvidia --network=host nvcr.io/nvidia/l4t-ml:r36.2.0-py3
+
+
+  docker run -it --rm --runtime=nvidia --network=host dustynv/l4t-pytorch:r36.4.0
+  ```
+
+- Check _cuda_ access in container:
+
+  ```bash
+  python3 -c 'import torch; print(torch.cuda.is_available());'
+  ```
+
+
+<br>
+
+## RPT installation
+
+- Build docker container:
+
+  ```bash
+  docker build --progress=plain -f ros/dockerfile_jetson -t rapidposetriangulation .
+  ./run_container.sh
+  ```
+
+- Build _rpt_ package inside container:
+
+  ```bash
+  cd /RapidPoseTriangulation/swig/ && make all && cd ../tests/ && python3 test_interface.py
+  ```
+
+- Test with samples:
+  ```bash
+  python3 /RapidPoseTriangulation/scripts/test_triangulate.py
+  ```

ros/dockerfile_jetson

@@ -1,4 +1,4 @@
-FROM nvcr.io/nvidia/l4t-pytorch:r35.1.0-pth1.11-py3
+FROM dustynv/l4t-pytorch:r36.4.0
 
 ARG DEBIAN_FRONTEND=noninteractive
 ENV LANG=C.UTF-8
@@ -7,24 +7,20 @@ WORKDIR /
 
 RUN apt-get update && apt-get install -y --no-install-recommends feh
 RUN apt-get update && apt-get install -y --no-install-recommends python3-opencv
-RUN pip uninstall -y opencv-python && pip install --no-cache "opencv-python<4.3"
 
 # Show matplotlib images
 RUN apt-get update && apt-get install -y --no-install-recommends python3-tk
 
-# Update pip to allow installation of skelda in editable mode
-RUN pip3 install --upgrade --no-cache-dir pip
-
 # Install MMPose
-# ENV FORCE_CUDA="1"
-# ENV MMCV_WITH_OPS=1
+ENV FORCE_CUDA="1"
+ENV MMCV_WITH_OPS=1
 RUN pip3 install --upgrade --no-cache-dir openmim
 RUN mim install mmengine
 RUN mim install "mmcv>=2,<2.2.0"
 RUN mim install "mmdet>=3"
 RUN mim install "mmpose>=1.1.0"
 # Fix an error when importing mmpose
-RUN pip3 install --upgrade --no-cache-dir numpy scipy
+RUN pip3 install --upgrade --no-cache-dir "numpy<2" scipy
 RUN git clone --depth=1 --branch=main https://github.com/open-mmlab/mmpose.git
 
 # Download pretrained model
@@ -32,13 +28,10 @@ COPY scripts/utils_2d_pose.py /
 RUN python3 -c "from utils_2d_pose import load_model; load_model();"
 RUN python3 -c "from utils_2d_pose import load_wb_model; load_wb_model();"
 
-# Fix an undefined symbol error with ompi
-RUN echo "ldconfig" >> ~/.bashrc
-
 # Install swig and later 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 apt-get update && apt-get install -y --no-install-recommends libopencv-dev
 
 COPY ./skelda/ /skelda/
 RUN pip3 install --no-cache-dir -e /skelda/