Object Detection Node/s

[Jquinny]

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We use the ZED ROS2 wrapper for handling a lot of the vision pipeline, but as of right now (though this may have changed or will change soon), the wrapper doesn't handle custom object detection.

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We need to write some nodes for interfacing with the output's of the ROS2 wrapper, and then for sending results back into it so it can integrate it into the wrapper's built in visual SLAM. We should try inter-process setup and intra-process (composable ROS2 nodes) to see which is faster. We will have to take images from the correct topics, run them through the object detector (ideally it is optimized using tensorrt), and then send the results back into the wrapper.

If the wrapper still doesn't have capabilities to handle custom object detections, we might have to change some of the wrapper codebase to implement it ourselves, or implement our own custom algorithms for 3D localization from the 2D detection results. This will have to be looked into.

Here is some task's to follow through with:

• rebuild ROS2 wrapper to make sure everything is up to date
• add a directory somewhere in perception folder where we store .pt and tensorrt model files
• write mock data generator that just samples an image from a sample of the dataset and resizes it to 1280x720, then sends it on a topic
  • this is for testing the object detector's within ROS framework
  • will need to throw a sample of the dataset somewhere in the codebase as well for testing
• write object detector node in python that reads images from mock data generator topics
  • just use .pt files and ultralytics for now, test inference results and speeds
• optimize the models using tensorrt and compare the results with the .pt pipeline
• start working on c++ implementation that interfaces directly with the wrapper code (this will be the most involved part probably)

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Some potentially helpful links:

• how to implement custom object detection in wrapper
• stale pr with a potential partial implementation to build off of