Posts made by Daniel Rincon

we have a model trained in YoloV8, starting from Yolo8M, we did all the conversion process according to the documentation, starting from an ONNX, we did everything following the documentation but at the time of running the model we get this:
Jul 09 18:41:59 m0054 bash[4052]: Fault thread: voxl-tflite-ser(tid: 6348)
Jul 09 18:41:59 m0054 bash[4052]: Fault address: (nil)
Jul 09 18:41:59 m0054 bash[4052]: Unknown reason.
Jul 09 18:41:59 m0054 systemd[1]: voxl-tflite-server.service: Main process exited, code=killed, status=11/SEGV
Jul 09 18:41:59 m0054 systemd[1]: voxl-tflite-server.service: Failed with result 'signal'.
Jul 09 18:41:59 m0054 systemd[1]: voxl-tflite-server.service: Service hold-off time over, scheduling restart.
Jul 09 18:41:59 m0054 systemd[1]: voxl-tflite-server.service: Scheduled restart job, restart counter is at 53.
Jul 09 18:41:59 m0054 systemd[1]: Stopped voxl-tflite-server.
Jul 09 18:41:59 m0054 systemd[1]: Started voxl-tflite-server.
Jul 09 18:42:00 m0054 bash[6590]: INFO: Created TensorFlow Lite delegate for GPU.
Jul 09 18:42:12 m0054 bash[6590]: INFO: Initialized OpenCL-based API.
Jul 09 18:42:12 m0054 bash[6590]: INFO: Created 1 GPU delegate kernels.
Jul 09 18:42:12 m0054 bash[6590]: ------VOXL TFLite Server------
Jul 09 18:42:12 m0054 bash[6590]: Segmentation fault:
Jul 09 18:42:12 m0054 bash[6590]: Fault thread: voxl-tflite-ser(tid: 8954)
Jul 09 18:42:12 m0054 bash[6590]: Fault address: (nil)
Jul 09 18:42:12 m0054 bash[6590]: Unknown reason.
Jul 09 18:42:12 m0054 systemd[1]: voxl-tflite-server.service: Main process exited, code=killed, status=11/SEGV
Jul 09 18:42:12 m0054 systemd[1]: voxl-tflite-server.service: Failed with result 'signal'.
Jul 09 18:42:12 m0054 systemd[1]: voxl-tflite-server.service: Service hold-off time over, scheduling restart.
Jul 09 18:42:12 m0054 systemd[1]: voxl-tflite-server.service: Scheduled restart job, restart counter is at 54.
Jul 09 18:42:12 m0054 systemd[1]: Stopped voxl-tflite-server.
Jul 09 18:42:12 m0054 systemd[1]: Started voxl-tflite-server.
Jul 09 18:42:13 m0054 bash[9299]: INFO: Created TensorFlow Lite delegate for GPU.
Jul 09 18:42:24 m0054 bash[9299]: INFO: Initialized OpenCL-based API.
Jul 09 18:42:24 m0054 bash[9299]: INFO: Created 1 GPU delegate kernels.

we have tried with the quantification proposed in the documentation and nothing, we are stuck with this, what can we do?

voxl-suite: 1.4.5

p.s. we also found an error in the voxl-configure-tfliteserver code, where this was shown when setting the custom model: set_param_bool expected 2 args, we corrected it this way: set_param_bool requires_labels true

Hi! I am trying to adapt Starling 2 to the operations I have with my clients.

For this I need to know first if the front camera is a camera that is used for the obstacle avoidance system and VIO, or if it is just a RGB camera that I can point downwards, so that I can run my own models on this camera, of course without affecting the obstacle avoidance system.

If not, can I put an additional camera pointing downwards, so I can run my own YOLO model on it?

I also need to know if I can put two lidars or ragefinders to be able to know the precise height up and down of the drone.

Finally, I also need to protect the drone from the conditions in which it operates, can I build a case to wrap all the electronics, besides that, protect it from humidity and other factors, is this possible, is there a case I can buy for this?

The idea is to be able to have a final product, adapting this great drone for these needs.

thank you very much in advance