No version for distro humble showing github. Known supported distros are highlighted in the buttons above.
Package symbol

ros2_nanoowl package from ros2-nanoowl repo

ros2_nanoowl

ROS Distro
github

Package Summary

Tags No category tags.
Version 0.0.0
License TODO: License declaration
Build type AMENT_PYTHON
Use RECOMMENDED

Repository Summary

Description ROS 2 node for open-vocabulary object detection using NanoOWL.
Checkout URI https://github.com/nvidia-ai-iot/ros2-nanoowl.git
VCS Type git
VCS Version master
Last Updated 2024-03-08
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

ROS 2 package for object detection using NanoOWL on NVIDIA Jetson

Additional Links

No additional links.

Maintainers

  • asawareeb

Authors

No additional authors.

ROS2 NanoOWL

ROS2 node for open-vocabulary object detection using NanoOWL.

NanoOWL optimizes OWL-ViT to run real-time on NVIDIA Jetson Orin with TensorRT. This project provides a ROS 2 package for object detection using NanoOWL.

   

   

Setup

  1. Set up your Isaac ROS development environment following instructions here.
  2. Clone required projects under ${ISAAC_ROS_WS}/src :
cd ${ISAAC_ROS_WS}/src
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git
git clone https://github.com/NVIDIA-AI-IOT/ROS2-NanoOWL.git
git clone https://github.com/NVIDIA-AI-IOT/nanoowl
git clone https://github.com/NVIDIA-AI-IOT/torch2trt
git clone --branch humble https://github.com/ros2/demos.git

  1. Launch the docker container using the run_dev.sh script:
cd ${ISAAC_ROS_WS}/src/isaac_ros_common
./scripts/run_dev.sh

  1. Install dependencies:
    • Pytorch: The Isaac ROS development environment that we set up in step 1 comes with PyTorch preinstalled. Check your PyTorch version using the interactive Python interpreter by running python from terminal, and these commands:
      import torch
      torch.__version__
      
  • NVIDIA TensorRT: If you’re developing on an NVIDIA Jetson, TensorRT is pre installed as part of JetPack. Verify the installation by running python from terminal, and then this command in the interactive Python interpreter: import tensorrt . If it says ‘ModuleNotFound’, try the following command and check again following the steps above:
      sudo apt-get install python3-libnvinfer-dev
      
  If this fails, run the following command and try again:
      sudo apt-get install apt-utils
      
  In case the 'ModuleNotFound' error still shows up - The python bindings to tensorrt are available in  ```dist-packages ```, which may not be visible to your environment. We add  ```dist-packages ``` to  ```PYTHONPATH ``` to make this work:
      export PYTHONPATH=/usr/lib/python3.8/dist-packages:$PYTHONPATH
      
  If  ```tensorrt ``` is still not installed, try the following command:
      pip install pycuda
      
  • Torchvision: Identify which version of torchvision is compatible with your PyTorch version from here. Clone and install that specific version from source in your workspace’s src folder: git clone –-branch <version> https://github.com/pytorch/vision.git . For example:
      cd ${ISAAC_ROS_WS}/src
      git clone --branch v0.13.0 https://github.com/pytorch/vision.git
      cd vision
      pip install .
      
  Verify that torchvision has been installed correctly using the interactive Python interpreter by running python from terminal, and these commands:
      cd ../
      import torchvision
      torchvision.__version__
      
  If it says ‘ModuleNotFound’, try each of the following and check again following the steps above:
      sudo apt install nvidia-cuda-dev
      pip install ninja
      sudo apt-get install ninja-build
      
  • Transformers library:
      pip install transformers
      
  • Matplotlib:
      pip install matplotlib
      
  • torch2trt: Enter the torch2trt repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/torch2trt
      pip install .
      
  • NanoOWL: Enter the NanoOWL repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/nanoowl
      pip install .
      
  • cam2image: We want to use the image_tools package from the demos repository that we cloned to take input from an attached usb camera. Build and source this package from your workspace:

```

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Dependant Packages

No known dependants.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged ros2_nanoowl at Robotics Stack Exchange

No version for distro jazzy showing github. Known supported distros are highlighted in the buttons above.
Package symbol

ros2_nanoowl package from ros2-nanoowl repo

ros2_nanoowl

ROS Distro
github

Package Summary

Tags No category tags.
Version 0.0.0
License TODO: License declaration
Build type AMENT_PYTHON
Use RECOMMENDED

Repository Summary

Description ROS 2 node for open-vocabulary object detection using NanoOWL.
Checkout URI https://github.com/nvidia-ai-iot/ros2-nanoowl.git
VCS Type git
VCS Version master
Last Updated 2024-03-08
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

ROS 2 package for object detection using NanoOWL on NVIDIA Jetson

Additional Links

No additional links.

Maintainers

  • asawareeb

Authors

No additional authors.

ROS2 NanoOWL

ROS2 node for open-vocabulary object detection using NanoOWL.

NanoOWL optimizes OWL-ViT to run real-time on NVIDIA Jetson Orin with TensorRT. This project provides a ROS 2 package for object detection using NanoOWL.

   

   

Setup

  1. Set up your Isaac ROS development environment following instructions here.
  2. Clone required projects under ${ISAAC_ROS_WS}/src :
cd ${ISAAC_ROS_WS}/src
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git
git clone https://github.com/NVIDIA-AI-IOT/ROS2-NanoOWL.git
git clone https://github.com/NVIDIA-AI-IOT/nanoowl
git clone https://github.com/NVIDIA-AI-IOT/torch2trt
git clone --branch humble https://github.com/ros2/demos.git

  1. Launch the docker container using the run_dev.sh script:
cd ${ISAAC_ROS_WS}/src/isaac_ros_common
./scripts/run_dev.sh

  1. Install dependencies:
    • Pytorch: The Isaac ROS development environment that we set up in step 1 comes with PyTorch preinstalled. Check your PyTorch version using the interactive Python interpreter by running python from terminal, and these commands:
      import torch
      torch.__version__
      
  • NVIDIA TensorRT: If you’re developing on an NVIDIA Jetson, TensorRT is pre installed as part of JetPack. Verify the installation by running python from terminal, and then this command in the interactive Python interpreter: import tensorrt . If it says ‘ModuleNotFound’, try the following command and check again following the steps above:
      sudo apt-get install python3-libnvinfer-dev
      
  If this fails, run the following command and try again:
      sudo apt-get install apt-utils
      
  In case the 'ModuleNotFound' error still shows up - The python bindings to tensorrt are available in  ```dist-packages ```, which may not be visible to your environment. We add  ```dist-packages ``` to  ```PYTHONPATH ``` to make this work:
      export PYTHONPATH=/usr/lib/python3.8/dist-packages:$PYTHONPATH
      
  If  ```tensorrt ``` is still not installed, try the following command:
      pip install pycuda
      
  • Torchvision: Identify which version of torchvision is compatible with your PyTorch version from here. Clone and install that specific version from source in your workspace’s src folder: git clone –-branch <version> https://github.com/pytorch/vision.git . For example:
      cd ${ISAAC_ROS_WS}/src
      git clone --branch v0.13.0 https://github.com/pytorch/vision.git
      cd vision
      pip install .
      
  Verify that torchvision has been installed correctly using the interactive Python interpreter by running python from terminal, and these commands:
      cd ../
      import torchvision
      torchvision.__version__
      
  If it says ‘ModuleNotFound’, try each of the following and check again following the steps above:
      sudo apt install nvidia-cuda-dev
      pip install ninja
      sudo apt-get install ninja-build
      
  • Transformers library:
      pip install transformers
      
  • Matplotlib:
      pip install matplotlib
      
  • torch2trt: Enter the torch2trt repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/torch2trt
      pip install .
      
  • NanoOWL: Enter the NanoOWL repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/nanoowl
      pip install .
      
  • cam2image: We want to use the image_tools package from the demos repository that we cloned to take input from an attached usb camera. Build and source this package from your workspace:

```

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Dependant Packages

No known dependants.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged ros2_nanoowl at Robotics Stack Exchange

No version for distro kilted showing github. Known supported distros are highlighted in the buttons above.
Package symbol

ros2_nanoowl package from ros2-nanoowl repo

ros2_nanoowl

ROS Distro
github

Package Summary

Tags No category tags.
Version 0.0.0
License TODO: License declaration
Build type AMENT_PYTHON
Use RECOMMENDED

Repository Summary

Description ROS 2 node for open-vocabulary object detection using NanoOWL.
Checkout URI https://github.com/nvidia-ai-iot/ros2-nanoowl.git
VCS Type git
VCS Version master
Last Updated 2024-03-08
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

ROS 2 package for object detection using NanoOWL on NVIDIA Jetson

Additional Links

No additional links.

Maintainers

  • asawareeb

Authors

No additional authors.

ROS2 NanoOWL

ROS2 node for open-vocabulary object detection using NanoOWL.

NanoOWL optimizes OWL-ViT to run real-time on NVIDIA Jetson Orin with TensorRT. This project provides a ROS 2 package for object detection using NanoOWL.

   

   

Setup

  1. Set up your Isaac ROS development environment following instructions here.
  2. Clone required projects under ${ISAAC_ROS_WS}/src :
cd ${ISAAC_ROS_WS}/src
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git
git clone https://github.com/NVIDIA-AI-IOT/ROS2-NanoOWL.git
git clone https://github.com/NVIDIA-AI-IOT/nanoowl
git clone https://github.com/NVIDIA-AI-IOT/torch2trt
git clone --branch humble https://github.com/ros2/demos.git

  1. Launch the docker container using the run_dev.sh script:
cd ${ISAAC_ROS_WS}/src/isaac_ros_common
./scripts/run_dev.sh

  1. Install dependencies:
    • Pytorch: The Isaac ROS development environment that we set up in step 1 comes with PyTorch preinstalled. Check your PyTorch version using the interactive Python interpreter by running python from terminal, and these commands:
      import torch
      torch.__version__
      
  • NVIDIA TensorRT: If you’re developing on an NVIDIA Jetson, TensorRT is pre installed as part of JetPack. Verify the installation by running python from terminal, and then this command in the interactive Python interpreter: import tensorrt . If it says ‘ModuleNotFound’, try the following command and check again following the steps above:
      sudo apt-get install python3-libnvinfer-dev
      
  If this fails, run the following command and try again:
      sudo apt-get install apt-utils
      
  In case the 'ModuleNotFound' error still shows up - The python bindings to tensorrt are available in  ```dist-packages ```, which may not be visible to your environment. We add  ```dist-packages ``` to  ```PYTHONPATH ``` to make this work:
      export PYTHONPATH=/usr/lib/python3.8/dist-packages:$PYTHONPATH
      
  If  ```tensorrt ``` is still not installed, try the following command:
      pip install pycuda
      
  • Torchvision: Identify which version of torchvision is compatible with your PyTorch version from here. Clone and install that specific version from source in your workspace’s src folder: git clone –-branch <version> https://github.com/pytorch/vision.git . For example:
      cd ${ISAAC_ROS_WS}/src
      git clone --branch v0.13.0 https://github.com/pytorch/vision.git
      cd vision
      pip install .
      
  Verify that torchvision has been installed correctly using the interactive Python interpreter by running python from terminal, and these commands:
      cd ../
      import torchvision
      torchvision.__version__
      
  If it says ‘ModuleNotFound’, try each of the following and check again following the steps above:
      sudo apt install nvidia-cuda-dev
      pip install ninja
      sudo apt-get install ninja-build
      
  • Transformers library:
      pip install transformers
      
  • Matplotlib:
      pip install matplotlib
      
  • torch2trt: Enter the torch2trt repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/torch2trt
      pip install .
      
  • NanoOWL: Enter the NanoOWL repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/nanoowl
      pip install .
      
  • cam2image: We want to use the image_tools package from the demos repository that we cloned to take input from an attached usb camera. Build and source this package from your workspace:

```

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Dependant Packages

No known dependants.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged ros2_nanoowl at Robotics Stack Exchange

No version for distro rolling showing github. Known supported distros are highlighted in the buttons above.
Package symbol

ros2_nanoowl package from ros2-nanoowl repo

ros2_nanoowl

ROS Distro
github

Package Summary

Tags No category tags.
Version 0.0.0
License TODO: License declaration
Build type AMENT_PYTHON
Use RECOMMENDED

Repository Summary

Description ROS 2 node for open-vocabulary object detection using NanoOWL.
Checkout URI https://github.com/nvidia-ai-iot/ros2-nanoowl.git
VCS Type git
VCS Version master
Last Updated 2024-03-08
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

ROS 2 package for object detection using NanoOWL on NVIDIA Jetson

Additional Links

No additional links.

Maintainers

  • asawareeb

Authors

No additional authors.

ROS2 NanoOWL

ROS2 node for open-vocabulary object detection using NanoOWL.

NanoOWL optimizes OWL-ViT to run real-time on NVIDIA Jetson Orin with TensorRT. This project provides a ROS 2 package for object detection using NanoOWL.

   

   

Setup

  1. Set up your Isaac ROS development environment following instructions here.
  2. Clone required projects under ${ISAAC_ROS_WS}/src :
cd ${ISAAC_ROS_WS}/src
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git
git clone https://github.com/NVIDIA-AI-IOT/ROS2-NanoOWL.git
git clone https://github.com/NVIDIA-AI-IOT/nanoowl
git clone https://github.com/NVIDIA-AI-IOT/torch2trt
git clone --branch humble https://github.com/ros2/demos.git

  1. Launch the docker container using the run_dev.sh script:
cd ${ISAAC_ROS_WS}/src/isaac_ros_common
./scripts/run_dev.sh

  1. Install dependencies:
    • Pytorch: The Isaac ROS development environment that we set up in step 1 comes with PyTorch preinstalled. Check your PyTorch version using the interactive Python interpreter by running python from terminal, and these commands:
      import torch
      torch.__version__
      
  • NVIDIA TensorRT: If you’re developing on an NVIDIA Jetson, TensorRT is pre installed as part of JetPack. Verify the installation by running python from terminal, and then this command in the interactive Python interpreter: import tensorrt . If it says ‘ModuleNotFound’, try the following command and check again following the steps above:
      sudo apt-get install python3-libnvinfer-dev
      
  If this fails, run the following command and try again:
      sudo apt-get install apt-utils
      
  In case the 'ModuleNotFound' error still shows up - The python bindings to tensorrt are available in  ```dist-packages ```, which may not be visible to your environment. We add  ```dist-packages ``` to  ```PYTHONPATH ``` to make this work:
      export PYTHONPATH=/usr/lib/python3.8/dist-packages:$PYTHONPATH
      
  If  ```tensorrt ``` is still not installed, try the following command:
      pip install pycuda
      
  • Torchvision: Identify which version of torchvision is compatible with your PyTorch version from here. Clone and install that specific version from source in your workspace’s src folder: git clone –-branch <version> https://github.com/pytorch/vision.git . For example:
      cd ${ISAAC_ROS_WS}/src
      git clone --branch v0.13.0 https://github.com/pytorch/vision.git
      cd vision
      pip install .
      
  Verify that torchvision has been installed correctly using the interactive Python interpreter by running python from terminal, and these commands:
      cd ../
      import torchvision
      torchvision.__version__
      
  If it says ‘ModuleNotFound’, try each of the following and check again following the steps above:
      sudo apt install nvidia-cuda-dev
      pip install ninja
      sudo apt-get install ninja-build
      
  • Transformers library:
      pip install transformers
      
  • Matplotlib:
      pip install matplotlib
      
  • torch2trt: Enter the torch2trt repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/torch2trt
      pip install .
      
  • NanoOWL: Enter the NanoOWL repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/nanoowl
      pip install .
      
  • cam2image: We want to use the image_tools package from the demos repository that we cloned to take input from an attached usb camera. Build and source this package from your workspace:

```

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Dependant Packages

No known dependants.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged ros2_nanoowl at Robotics Stack Exchange

Package symbol

ros2_nanoowl package from ros2-nanoowl repo

ros2_nanoowl

ROS Distro
github

Package Summary

Tags No category tags.
Version 0.0.0
License TODO: License declaration
Build type AMENT_PYTHON
Use RECOMMENDED

Repository Summary

Description ROS 2 node for open-vocabulary object detection using NanoOWL.
Checkout URI https://github.com/nvidia-ai-iot/ros2-nanoowl.git
VCS Type git
VCS Version master
Last Updated 2024-03-08
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

ROS 2 package for object detection using NanoOWL on NVIDIA Jetson

Additional Links

No additional links.

Maintainers

  • asawareeb

Authors

No additional authors.

ROS2 NanoOWL

ROS2 node for open-vocabulary object detection using NanoOWL.

NanoOWL optimizes OWL-ViT to run real-time on NVIDIA Jetson Orin with TensorRT. This project provides a ROS 2 package for object detection using NanoOWL.

   

   

Setup

  1. Set up your Isaac ROS development environment following instructions here.
  2. Clone required projects under ${ISAAC_ROS_WS}/src :
cd ${ISAAC_ROS_WS}/src
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git
git clone https://github.com/NVIDIA-AI-IOT/ROS2-NanoOWL.git
git clone https://github.com/NVIDIA-AI-IOT/nanoowl
git clone https://github.com/NVIDIA-AI-IOT/torch2trt
git clone --branch humble https://github.com/ros2/demos.git

  1. Launch the docker container using the run_dev.sh script:
cd ${ISAAC_ROS_WS}/src/isaac_ros_common
./scripts/run_dev.sh

  1. Install dependencies:
    • Pytorch: The Isaac ROS development environment that we set up in step 1 comes with PyTorch preinstalled. Check your PyTorch version using the interactive Python interpreter by running python from terminal, and these commands:
      import torch
      torch.__version__
      
  • NVIDIA TensorRT: If you’re developing on an NVIDIA Jetson, TensorRT is pre installed as part of JetPack. Verify the installation by running python from terminal, and then this command in the interactive Python interpreter: import tensorrt . If it says ‘ModuleNotFound’, try the following command and check again following the steps above:
      sudo apt-get install python3-libnvinfer-dev
      
  If this fails, run the following command and try again:
      sudo apt-get install apt-utils
      
  In case the 'ModuleNotFound' error still shows up - The python bindings to tensorrt are available in  ```dist-packages ```, which may not be visible to your environment. We add  ```dist-packages ``` to  ```PYTHONPATH ``` to make this work:
      export PYTHONPATH=/usr/lib/python3.8/dist-packages:$PYTHONPATH
      
  If  ```tensorrt ``` is still not installed, try the following command:
      pip install pycuda
      
  • Torchvision: Identify which version of torchvision is compatible with your PyTorch version from here. Clone and install that specific version from source in your workspace’s src folder: git clone –-branch <version> https://github.com/pytorch/vision.git . For example:
      cd ${ISAAC_ROS_WS}/src
      git clone --branch v0.13.0 https://github.com/pytorch/vision.git
      cd vision
      pip install .
      
  Verify that torchvision has been installed correctly using the interactive Python interpreter by running python from terminal, and these commands:
      cd ../
      import torchvision
      torchvision.__version__
      
  If it says ‘ModuleNotFound’, try each of the following and check again following the steps above:
      sudo apt install nvidia-cuda-dev
      pip install ninja
      sudo apt-get install ninja-build
      
  • Transformers library:
      pip install transformers
      
  • Matplotlib:
      pip install matplotlib
      
  • torch2trt: Enter the torch2trt repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/torch2trt
      pip install .
      
  • NanoOWL: Enter the NanoOWL repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/nanoowl
      pip install .
      
  • cam2image: We want to use the image_tools package from the demos repository that we cloned to take input from an attached usb camera. Build and source this package from your workspace:

```

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Dependant Packages

No known dependants.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged ros2_nanoowl at Robotics Stack Exchange

No version for distro galactic showing github. Known supported distros are highlighted in the buttons above.
Package symbol

ros2_nanoowl package from ros2-nanoowl repo

ros2_nanoowl

ROS Distro
github

Package Summary

Tags No category tags.
Version 0.0.0
License TODO: License declaration
Build type AMENT_PYTHON
Use RECOMMENDED

Repository Summary

Description ROS 2 node for open-vocabulary object detection using NanoOWL.
Checkout URI https://github.com/nvidia-ai-iot/ros2-nanoowl.git
VCS Type git
VCS Version master
Last Updated 2024-03-08
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

ROS 2 package for object detection using NanoOWL on NVIDIA Jetson

Additional Links

No additional links.

Maintainers

  • asawareeb

Authors

No additional authors.

ROS2 NanoOWL

ROS2 node for open-vocabulary object detection using NanoOWL.

NanoOWL optimizes OWL-ViT to run real-time on NVIDIA Jetson Orin with TensorRT. This project provides a ROS 2 package for object detection using NanoOWL.

   

   

Setup

  1. Set up your Isaac ROS development environment following instructions here.
  2. Clone required projects under ${ISAAC_ROS_WS}/src :
cd ${ISAAC_ROS_WS}/src
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git
git clone https://github.com/NVIDIA-AI-IOT/ROS2-NanoOWL.git
git clone https://github.com/NVIDIA-AI-IOT/nanoowl
git clone https://github.com/NVIDIA-AI-IOT/torch2trt
git clone --branch humble https://github.com/ros2/demos.git

  1. Launch the docker container using the run_dev.sh script:
cd ${ISAAC_ROS_WS}/src/isaac_ros_common
./scripts/run_dev.sh

  1. Install dependencies:
    • Pytorch: The Isaac ROS development environment that we set up in step 1 comes with PyTorch preinstalled. Check your PyTorch version using the interactive Python interpreter by running python from terminal, and these commands:
      import torch
      torch.__version__
      
  • NVIDIA TensorRT: If you’re developing on an NVIDIA Jetson, TensorRT is pre installed as part of JetPack. Verify the installation by running python from terminal, and then this command in the interactive Python interpreter: import tensorrt . If it says ‘ModuleNotFound’, try the following command and check again following the steps above:
      sudo apt-get install python3-libnvinfer-dev
      
  If this fails, run the following command and try again:
      sudo apt-get install apt-utils
      
  In case the 'ModuleNotFound' error still shows up - The python bindings to tensorrt are available in  ```dist-packages ```, which may not be visible to your environment. We add  ```dist-packages ``` to  ```PYTHONPATH ``` to make this work:
      export PYTHONPATH=/usr/lib/python3.8/dist-packages:$PYTHONPATH
      
  If  ```tensorrt ``` is still not installed, try the following command:
      pip install pycuda
      
  • Torchvision: Identify which version of torchvision is compatible with your PyTorch version from here. Clone and install that specific version from source in your workspace’s src folder: git clone –-branch <version> https://github.com/pytorch/vision.git . For example:
      cd ${ISAAC_ROS_WS}/src
      git clone --branch v0.13.0 https://github.com/pytorch/vision.git
      cd vision
      pip install .
      
  Verify that torchvision has been installed correctly using the interactive Python interpreter by running python from terminal, and these commands:
      cd ../
      import torchvision
      torchvision.__version__
      
  If it says ‘ModuleNotFound’, try each of the following and check again following the steps above:
      sudo apt install nvidia-cuda-dev
      pip install ninja
      sudo apt-get install ninja-build
      
  • Transformers library:
      pip install transformers
      
  • Matplotlib:
      pip install matplotlib
      
  • torch2trt: Enter the torch2trt repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/torch2trt
      pip install .
      
  • NanoOWL: Enter the NanoOWL repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/nanoowl
      pip install .
      
  • cam2image: We want to use the image_tools package from the demos repository that we cloned to take input from an attached usb camera. Build and source this package from your workspace:

```

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Dependant Packages

No known dependants.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged ros2_nanoowl at Robotics Stack Exchange

No version for distro iron showing github. Known supported distros are highlighted in the buttons above.
Package symbol

ros2_nanoowl package from ros2-nanoowl repo

ros2_nanoowl

ROS Distro
github

Package Summary

Tags No category tags.
Version 0.0.0
License TODO: License declaration
Build type AMENT_PYTHON
Use RECOMMENDED

Repository Summary

Description ROS 2 node for open-vocabulary object detection using NanoOWL.
Checkout URI https://github.com/nvidia-ai-iot/ros2-nanoowl.git
VCS Type git
VCS Version master
Last Updated 2024-03-08
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

ROS 2 package for object detection using NanoOWL on NVIDIA Jetson

Additional Links

No additional links.

Maintainers

  • asawareeb

Authors

No additional authors.

ROS2 NanoOWL

ROS2 node for open-vocabulary object detection using NanoOWL.

NanoOWL optimizes OWL-ViT to run real-time on NVIDIA Jetson Orin with TensorRT. This project provides a ROS 2 package for object detection using NanoOWL.

   

   

Setup

  1. Set up your Isaac ROS development environment following instructions here.
  2. Clone required projects under ${ISAAC_ROS_WS}/src :
cd ${ISAAC_ROS_WS}/src
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git
git clone https://github.com/NVIDIA-AI-IOT/ROS2-NanoOWL.git
git clone https://github.com/NVIDIA-AI-IOT/nanoowl
git clone https://github.com/NVIDIA-AI-IOT/torch2trt
git clone --branch humble https://github.com/ros2/demos.git

  1. Launch the docker container using the run_dev.sh script:
cd ${ISAAC_ROS_WS}/src/isaac_ros_common
./scripts/run_dev.sh

  1. Install dependencies:
    • Pytorch: The Isaac ROS development environment that we set up in step 1 comes with PyTorch preinstalled. Check your PyTorch version using the interactive Python interpreter by running python from terminal, and these commands:
      import torch
      torch.__version__
      
  • NVIDIA TensorRT: If you’re developing on an NVIDIA Jetson, TensorRT is pre installed as part of JetPack. Verify the installation by running python from terminal, and then this command in the interactive Python interpreter: import tensorrt . If it says ‘ModuleNotFound’, try the following command and check again following the steps above:
      sudo apt-get install python3-libnvinfer-dev
      
  If this fails, run the following command and try again:
      sudo apt-get install apt-utils
      
  In case the 'ModuleNotFound' error still shows up - The python bindings to tensorrt are available in  ```dist-packages ```, which may not be visible to your environment. We add  ```dist-packages ``` to  ```PYTHONPATH ``` to make this work:
      export PYTHONPATH=/usr/lib/python3.8/dist-packages:$PYTHONPATH
      
  If  ```tensorrt ``` is still not installed, try the following command:
      pip install pycuda
      
  • Torchvision: Identify which version of torchvision is compatible with your PyTorch version from here. Clone and install that specific version from source in your workspace’s src folder: git clone –-branch <version> https://github.com/pytorch/vision.git . For example:
      cd ${ISAAC_ROS_WS}/src
      git clone --branch v0.13.0 https://github.com/pytorch/vision.git
      cd vision
      pip install .
      
  Verify that torchvision has been installed correctly using the interactive Python interpreter by running python from terminal, and these commands:
      cd ../
      import torchvision
      torchvision.__version__
      
  If it says ‘ModuleNotFound’, try each of the following and check again following the steps above:
      sudo apt install nvidia-cuda-dev
      pip install ninja
      sudo apt-get install ninja-build
      
  • Transformers library:
      pip install transformers
      
  • Matplotlib:
      pip install matplotlib
      
  • torch2trt: Enter the torch2trt repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/torch2trt
      pip install .
      
  • NanoOWL: Enter the NanoOWL repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/nanoowl
      pip install .
      
  • cam2image: We want to use the image_tools package from the demos repository that we cloned to take input from an attached usb camera. Build and source this package from your workspace:

```

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Dependant Packages

No known dependants.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged ros2_nanoowl at Robotics Stack Exchange

No version for distro melodic showing github. Known supported distros are highlighted in the buttons above.
Package symbol

ros2_nanoowl package from ros2-nanoowl repo

ros2_nanoowl

ROS Distro
github

Package Summary

Tags No category tags.
Version 0.0.0
License TODO: License declaration
Build type AMENT_PYTHON
Use RECOMMENDED

Repository Summary

Description ROS 2 node for open-vocabulary object detection using NanoOWL.
Checkout URI https://github.com/nvidia-ai-iot/ros2-nanoowl.git
VCS Type git
VCS Version master
Last Updated 2024-03-08
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

ROS 2 package for object detection using NanoOWL on NVIDIA Jetson

Additional Links

No additional links.

Maintainers

  • asawareeb

Authors

No additional authors.

ROS2 NanoOWL

ROS2 node for open-vocabulary object detection using NanoOWL.

NanoOWL optimizes OWL-ViT to run real-time on NVIDIA Jetson Orin with TensorRT. This project provides a ROS 2 package for object detection using NanoOWL.

   

   

Setup

  1. Set up your Isaac ROS development environment following instructions here.
  2. Clone required projects under ${ISAAC_ROS_WS}/src :
cd ${ISAAC_ROS_WS}/src
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git
git clone https://github.com/NVIDIA-AI-IOT/ROS2-NanoOWL.git
git clone https://github.com/NVIDIA-AI-IOT/nanoowl
git clone https://github.com/NVIDIA-AI-IOT/torch2trt
git clone --branch humble https://github.com/ros2/demos.git

  1. Launch the docker container using the run_dev.sh script:
cd ${ISAAC_ROS_WS}/src/isaac_ros_common
./scripts/run_dev.sh

  1. Install dependencies:
    • Pytorch: The Isaac ROS development environment that we set up in step 1 comes with PyTorch preinstalled. Check your PyTorch version using the interactive Python interpreter by running python from terminal, and these commands:
      import torch
      torch.__version__
      
  • NVIDIA TensorRT: If you’re developing on an NVIDIA Jetson, TensorRT is pre installed as part of JetPack. Verify the installation by running python from terminal, and then this command in the interactive Python interpreter: import tensorrt . If it says ‘ModuleNotFound’, try the following command and check again following the steps above:
      sudo apt-get install python3-libnvinfer-dev
      
  If this fails, run the following command and try again:
      sudo apt-get install apt-utils
      
  In case the 'ModuleNotFound' error still shows up - The python bindings to tensorrt are available in  ```dist-packages ```, which may not be visible to your environment. We add  ```dist-packages ``` to  ```PYTHONPATH ``` to make this work:
      export PYTHONPATH=/usr/lib/python3.8/dist-packages:$PYTHONPATH
      
  If  ```tensorrt ``` is still not installed, try the following command:
      pip install pycuda
      
  • Torchvision: Identify which version of torchvision is compatible with your PyTorch version from here. Clone and install that specific version from source in your workspace’s src folder: git clone –-branch <version> https://github.com/pytorch/vision.git . For example:
      cd ${ISAAC_ROS_WS}/src
      git clone --branch v0.13.0 https://github.com/pytorch/vision.git
      cd vision
      pip install .
      
  Verify that torchvision has been installed correctly using the interactive Python interpreter by running python from terminal, and these commands:
      cd ../
      import torchvision
      torchvision.__version__
      
  If it says ‘ModuleNotFound’, try each of the following and check again following the steps above:
      sudo apt install nvidia-cuda-dev
      pip install ninja
      sudo apt-get install ninja-build
      
  • Transformers library:
      pip install transformers
      
  • Matplotlib:
      pip install matplotlib
      
  • torch2trt: Enter the torch2trt repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/torch2trt
      pip install .
      
  • NanoOWL: Enter the NanoOWL repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/nanoowl
      pip install .
      
  • cam2image: We want to use the image_tools package from the demos repository that we cloned to take input from an attached usb camera. Build and source this package from your workspace:

```

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Dependant Packages

No known dependants.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged ros2_nanoowl at Robotics Stack Exchange

No version for distro noetic showing github. Known supported distros are highlighted in the buttons above.
Package symbol

ros2_nanoowl package from ros2-nanoowl repo

ros2_nanoowl

ROS Distro
github

Package Summary

Tags No category tags.
Version 0.0.0
License TODO: License declaration
Build type AMENT_PYTHON
Use RECOMMENDED

Repository Summary

Description ROS 2 node for open-vocabulary object detection using NanoOWL.
Checkout URI https://github.com/nvidia-ai-iot/ros2-nanoowl.git
VCS Type git
VCS Version master
Last Updated 2024-03-08
Dev Status UNKNOWN
Released UNRELEASED
Tags No category tags.
Contributing Help Wanted (-)
Good First Issues (-)
Pull Requests to Review (-)

Package Description

ROS 2 package for object detection using NanoOWL on NVIDIA Jetson

Additional Links

No additional links.

Maintainers

  • asawareeb

Authors

No additional authors.

ROS2 NanoOWL

ROS2 node for open-vocabulary object detection using NanoOWL.

NanoOWL optimizes OWL-ViT to run real-time on NVIDIA Jetson Orin with TensorRT. This project provides a ROS 2 package for object detection using NanoOWL.

   

   

Setup

  1. Set up your Isaac ROS development environment following instructions here.
  2. Clone required projects under ${ISAAC_ROS_WS}/src :
cd ${ISAAC_ROS_WS}/src
git clone https://github.com/NVIDIA-ISAAC-ROS/isaac_ros_common.git
git clone https://github.com/NVIDIA-AI-IOT/ROS2-NanoOWL.git
git clone https://github.com/NVIDIA-AI-IOT/nanoowl
git clone https://github.com/NVIDIA-AI-IOT/torch2trt
git clone --branch humble https://github.com/ros2/demos.git

  1. Launch the docker container using the run_dev.sh script:
cd ${ISAAC_ROS_WS}/src/isaac_ros_common
./scripts/run_dev.sh

  1. Install dependencies:
    • Pytorch: The Isaac ROS development environment that we set up in step 1 comes with PyTorch preinstalled. Check your PyTorch version using the interactive Python interpreter by running python from terminal, and these commands:
      import torch
      torch.__version__
      
  • NVIDIA TensorRT: If you’re developing on an NVIDIA Jetson, TensorRT is pre installed as part of JetPack. Verify the installation by running python from terminal, and then this command in the interactive Python interpreter: import tensorrt . If it says ‘ModuleNotFound’, try the following command and check again following the steps above:
      sudo apt-get install python3-libnvinfer-dev
      
  If this fails, run the following command and try again:
      sudo apt-get install apt-utils
      
  In case the 'ModuleNotFound' error still shows up - The python bindings to tensorrt are available in  ```dist-packages ```, which may not be visible to your environment. We add  ```dist-packages ``` to  ```PYTHONPATH ``` to make this work:
      export PYTHONPATH=/usr/lib/python3.8/dist-packages:$PYTHONPATH
      
  If  ```tensorrt ``` is still not installed, try the following command:
      pip install pycuda
      
  • Torchvision: Identify which version of torchvision is compatible with your PyTorch version from here. Clone and install that specific version from source in your workspace’s src folder: git clone –-branch <version> https://github.com/pytorch/vision.git . For example:
      cd ${ISAAC_ROS_WS}/src
      git clone --branch v0.13.0 https://github.com/pytorch/vision.git
      cd vision
      pip install .
      
  Verify that torchvision has been installed correctly using the interactive Python interpreter by running python from terminal, and these commands:
      cd ../
      import torchvision
      torchvision.__version__
      
  If it says ‘ModuleNotFound’, try each of the following and check again following the steps above:
      sudo apt install nvidia-cuda-dev
      pip install ninja
      sudo apt-get install ninja-build
      
  • Transformers library:
      pip install transformers
      
  • Matplotlib:
      pip install matplotlib
      
  • torch2trt: Enter the torch2trt repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/torch2trt
      pip install .
      
  • NanoOWL: Enter the NanoOWL repository cloned in step 2 and install the package:
      cd ${ISAAC_ROS_WS}/src/nanoowl
      pip install .
      
  • cam2image: We want to use the image_tools package from the demos repository that we cloned to take input from an attached usb camera. Build and source this package from your workspace:

```

File truncated at 100 lines see the full file

CHANGELOG
No CHANGELOG found.

Dependant Packages

No known dependants.

Launch files

No launch files found

Messages

No message files found.

Services

No service files found

Plugins

No plugins found.

Recent questions tagged ros2_nanoowl at Robotics Stack Exchange