Plotting Centroid with CUDA on Nvidia Jetson Orin Nano

Issue Overview

Users are attempting to enhance their custom object detection projects by plotting centroids of detected objects on the Nvidia Jetson Orin Nano. The specific points of concern include:

• Symptoms: Users successfully draw bounding boxes around detected objects but face challenges in calculating and plotting the centroid of these boxes as circles.

• Context: The issue arises during the development of a custom object detection application, specifically when modifying the source code (detectNet.cpp) from the Jetson Inference library.

• Hardware/Software Specifications: The discussion references the use of CUDA for processing and involves modifications to C++ code in the Jetson Inference library.

• Frequency: This issue appears to be a common challenge among users working with custom object detection implementations.

• Impact on User Experience: The inability to visualize centroids can limit the effectiveness of object detection applications, particularly in scenarios where precise object localization is crucial.

Possible Causes

Several factors may contribute to difficulties in plotting centroids:

• Code Modifications: Changes made to detectNet.cpp may not correctly calculate or render the centroid positions, leading to errors or no output.

• CUDA Function Failures: If CUDA functions responsible for drawing overlays fail, it could prevent centroids from being displayed.

• Detection Results: If no detections are made (i.e., numDetections <= 0), the code will skip any overlay rendering, including centroids.

• Incorrect Coordinates: Errors in calculating the centroid coordinates based on bounding box dimensions could lead to incorrect placements or failures in rendering.

Troubleshooting Steps, Solutions & Fixes

To resolve issues related to plotting centroids in a custom object detection application using CUDA, follow these steps:

1. Review Code Modifications:

   • Ensure that any changes made to detectNet.cpp correctly calculate the centroid based on bounding box coordinates. The centroid can be calculated as:
     $$ \text{centroid}x = \frac{x{\text{min}} + x_{\text{max}}}{2} $$
     $$ \text{centroid}y = \frac{y{\text{min}} + y_{\text{max}}}{2} $$

2. Check for Successful Detections:

   • Before attempting to plot centroids, confirm that detections are being made. Add debug statements or logging to verify that numDetections is greater than zero.

3. Implement Centroid Drawing Logic:

   • After confirming successful detections, implement logic to draw the centroid using CUDA. This can be done after drawing bounding boxes:

     // Example pseudocode for drawing centroid
     if (flags & OVERLAY_CENTROID) {
         for (uint32_t n = 0; n < numDetections; n++) {
             float centerX = (detections[n].left + detections[n].right) / 2;
             float centerY = (detections[n].top + detections[n].bottom) / 2;
             drawCircle(output, centerX, centerY, radius, color);
         }
     }
     

4. Test CUDA Functionality:

   • Ensure that all CUDA functions used for drawing overlays are functioning correctly. Check for any error codes returned by CUDA calls.

5. Consult Documentation and Examples:

   • Refer to the Jetson Inference documentation and existing examples on GitHub for guidance on implementing overlay features. The specific line of code mentioned in the discussion can be found here.

6. Seek Community Support:

   • If issues persist after following these steps, consider reaching out to community forums or GitHub issues related to Jetson Inference for additional insights or solutions from other developers facing similar challenges.

7. Unresolved Aspects:

   • Users may still encounter unique issues based on specific implementations or configurations not covered in common solutions. Further investigation may be needed if standard troubleshooting does not resolve the problem.

By following these steps, users should be able to effectively troubleshoot and implement centroid plotting in their custom object detection applications using CUDA on the Nvidia Jetson Orin Nano.