Thank you for your response. I have used the suggested code and made modifications based on the following suggestions. I successfully ran the evaluation code, but the MOTA value is still negative.
I removed objects with fewer than 5 radar points (both in the ground truth and model predictions).
I set the confidence threshold to 0.078483.
I merged the labels for bicycles and the person riding them together (following the suggested method).
Additionally, I made a video my video to show the ground truth and model detection results. In the video, the ground truth is displayed as bounding boxes (for visualization purposes only; in the evaluation code, the calculations are still based on radar points), and the model predictions are represented using different colors.
I compared this video with the one you provided RaTrack video and I noticed that in my video, there are a lot of false positives compares to yours, for example, between the 0:14 and 0:31 minute marks,, whereas in your video, between the 0:24 and 0:30 minute marks, there aren’t as many false positives.
Would it be possible to share the detection results used in your video? This could help me pinpoint where the discrepancies are arising.
Thank you for your response. I have used the suggested code and made modifications based on the following suggestions. I successfully ran the evaluation code, but the MOTA value is still negative.
I removed objects with fewer than 5 radar points (both in the ground truth and model predictions). I set the confidence threshold to 0.078483. I merged the labels for bicycles and the person riding them together (following the suggested method). Additionally, I made a video my video to show the ground truth and model detection results. In the video, the ground truth is displayed as bounding boxes (for visualization purposes only; in the evaluation code, the calculations are still based on radar points), and the model predictions are represented using different colors.
I compared this video with the one you provided RaTrack video and I noticed that in my video, there are a lot of false positives compares to yours, for example, between the 0:14 and 0:31 minute marks,, whereas in your video, between the 0:24 and 0:30 minute marks, there aren’t as many false positives.
Would it be possible to share the detection results used in your video? This could help me pinpoint where the discrepancies are arising.
Thank you for your continued assistance.
my email: jiawunliaw@gmail.com