Our current calibration tool supports only a single camera setup. To enhance our system's flexibility and utility in environments with multiple cameras (up to four), we need to develop logic that supports calibration and warping for multiple cameras. Each camera may be pointed at different corners of the field. The Python wrapper should allow for selection of both the camera ID and RobotID, which will be used in the naming convention for output files. Additionally, the landmark FCS needs to be dynamically adjusted based on the camera ID and the specific field corner it is targeting.
Objective
To extend the functionality of our calibration tool to handle multiple cameras efficiently, ensuring that each camera can be individually calibrated and its data processed correctly depending on its orientation and specified field corner.
Expected Outcome
Support for selecting up to four different cameras via Camera ID in the Python wrapper.
Integration of RobotID in the selection process and output file naming convention.
Dynamic adjustment of the landmark FCS based on the camera ID and field corner orientation.
Output filenames that reflect the selected Camera ID and RobotID for easier identification and organization.
Ensure that the GUI allows for easy configuration and visualization of settings for multiple cameras.
Make sure args and GUI are alligned
Steps to Achieve
Design Multi-Camera Support: Outline the necessary changes in the GUI to support multiple cameras, including UI elements for selecting Camera ID and RobotID.
Implement Camera and Robot ID Logic: Extend the Python wrapper to handle input arguments for Camera ID and RobotID, affecting the calibration process and output file naming.
Adjust Landmark FCS: Develop a system to modify the landmark frame coordinate system based on the camera's orientation and targeted field corner. This may involve mapping configurations for each corner and camera combination.
Testing: Thoroughly test the tool with multiple cameras to ensure that all features work as expected and that the system can handle different configurations without errors.
Documentation: Update the documentation to include detailed instructions on how to set up and use the tool with multiple cameras, including explanations of how the landmark FCS adjustments work.
Questions & Discussion Points
Should we allow for any camera to be used in any of the four corners, or are there specific cameras designed for specific corners?
How can we ensure that the system remains user-friendly and efficient even with the added complexity of multiple cameras?
Your feedback and contributions to this discussion are invaluable. Please let us know your thoughts, suggestions, or any concerns you might have with the current proposal.
This development is expected to significantly enhance the robustness and versatility of our calibration tool, making it suitable for complex environments with multiple observational points.
Description
Our current calibration tool supports only a single camera setup. To enhance our system's flexibility and utility in environments with multiple cameras (up to four), we need to develop logic that supports calibration and warping for multiple cameras. Each camera may be pointed at different corners of the field. The Python wrapper should allow for selection of both the camera ID and RobotID, which will be used in the naming convention for output files. Additionally, the landmark FCS needs to be dynamically adjusted based on the camera ID and the specific field corner it is targeting.
Objective
To extend the functionality of our calibration tool to handle multiple cameras efficiently, ensuring that each camera can be individually calibrated and its data processed correctly depending on its orientation and specified field corner.
Expected Outcome
Steps to Achieve
Questions & Discussion Points
Your feedback and contributions to this discussion are invaluable. Please let us know your thoughts, suggestions, or any concerns you might have with the current proposal.
This development is expected to significantly enhance the robustness and versatility of our calibration tool, making it suitable for complex environments with multiple observational points.