`isaac_ros_triton`

Source code on GitHub.

Quickstart

Note

This quickstart demonstrates setting up isaac_ros_triton. It is often used with an encoder and decoder node to perform pre-processing and post-processing respectively to form an application.

To use the packages in useful contexts, please refer here.

Set Up Development Environment

Set up your development environment by following the instructions in getting started.

Clone isaac_ros_common under ${ISAAC_ROS_WS}/src.

cd ${ISAAC_ROS_WS}/src && \
   git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git

(Optional) Install dependencies for any sensors you want to use by following the sensor-specific guides.

Warning

We strongly recommend installing all sensor dependencies before starting any quickstarts. Some sensor dependencies require restarting the Isaac ROS Dev container during installation, which will interrupt the quickstart process.

Build `isaac_ros_triton`

Launch the Docker container using the run_dev.sh script:

cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
./scripts/run_dev.sh

Install the prebuilt Debian package:

sudo apt-get install -y ros-humble-isaac-ros-triton

Clone this repository under ${ISAAC_ROS_WS}/src:

cd ${ISAAC_ROS_WS}/src && \
   git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_dnn_inference.git

Launch the Docker container using the run_dev.sh script:

cd ${ISAAC_ROS_WS}/src/isaac_ros_common && \
./scripts/run_dev.sh

Use rosdep to install the package’s dependencies:

rosdep install --from-paths ${ISAAC_ROS_WS}/src/isaac_ros_dnn_inference/isaac_ros_triton --ignore-src -y

Build the package from source:

cd ${ISAAC_ROS_WS}/ && \
   colcon build --symlink-install --packages-up-to isaac_ros_triton

Source the ROS workspace:

Note

Make sure to repeat this step in every terminal created inside the Docker container.

Since this package was built from source, the enclosing workspace must be sourced for ROS to be able to find the package’s contents.
```
source install/setup.bash
```

Troubleshooting

Isaac ROS Troubleshooting

For solutions to problems with Isaac ROS, please check here.

Deep Learning Troubleshooting

For solutions to problems with using DNN models, please check here.

API

Usage

This package contains a launch file that solely launches isaac_ros_triton.

Warning

For your specific application, these launch files may need to be modified. Please consult the available components to see the configurable parameters.

Additionally, for most applications, an encoder node for pre-processing your data source and decoder for post-processing the inference output is required.

Launch File	Components Used
`isaac_ros_triton.launch.py`	TritonNode

TritonNode

ROS Parameters

ROS Parameter	Type	Default	Description
`model_repository_paths`	`string list`	`['']`	The absolute paths to your model repositories in your local file system (the structure should follow Triton requirements) E.g. `['/tmp/models']`
`model_name`	`string`	`''`	The name of your model. Under `model_repository_paths`, there should be a directory with this name, and it should align with the model name in the model configuration under this directory E.g. `peoplesemsegnet_shuffleseg`
`max_batch_size`	`uint16_t`	`8`	The maximum batch size allowed for the model. It should align with the model configuration
`num_concurrent_requests`	`uint16_t`	`10`	The number of requests the Triton server can take at a time. This should be set according to the tensor publisher frequency
`input_tensor_names`	`string list`	`['input_tensor']`	A list of tensor names to be bound to specified input bindings names. Bindings occur in sequential order, so the first name here will be mapped to the first name in input_binding_names
`input_binding_names`	`string list`	`['']`	A list of input tensor binding names specified by model E.g. `['input_2:0']`
`input_tensor_formats`	`string list`	`['']`	A list of input tensor NITROS formats. This should be given in sequential order E.g. `['nitros_tensor_list_nchw_rgb_f32']`
`output_tensor_names`	`string list`	`['output_tensor']`	A list of tensor names to be bound to specified output binding names
`output_binding_names`	`string list`	`['']`	A list of tensor names to be bound to specified output binding names E.g. `['argmax_1']`
`output_tensor_formats`	`string list`	`['']`	A list of input tensor NITROS formats. This should be given in sequential order E.g. `[nitros_tensor_list_nchw_rgb_f32]`

ROS Topics Subscribed

ROS Topic	Type	Description
`tensor_pub`	isaac_ros_tensor_list_interfaces/TensorList	The input tensor stream

ROS Topics Published

ROS Topic	Type	Description
`tensor_sub`	isaac_ros_tensor_list_interfaces/TensorList	The tensor list of output tensors from the model inference

isaac_ros_triton