Hi everyone,
I was working on a people detection model deployed on a Jetson Nano using FOMO and I’ve come across some issues and doubts. I will list all my doubts and give a brief explanation:
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Bounding boxes
I tested some images using the classify-image.py from linux-sdk-python repo and I expected to have centroids as the output so why are bounding boxes displayed, alongside information about them? Has that anything to do with centroid calculations? I meant to perform a comparison between YOLO and FOMO. -
Image datasets
I was wondering if there was a way to import COCO dataset in Edge Impulse, to be able to detect multiple classes. Another issue would be to import the labels directly instead of labelling all the images manually. -
example-standalone-inferencing-linux
I’ve followed the necessary steps to build the project on a Jetson Nano but everytime I execute
{ APP_CUSTOM=1 TARGET_LINUX_AARCH64=1 USE_FULL_TFLITE=1 CC=clang CXX=clang++ make -j } my Jetson Nano gets frozen and stuck. Down below in the same README.md, there is a brief annotation saying object detection models are not actually supported. Does somebody know if the re are any updates coming on the subject?
Thank you everyone in advance,
Iker Arrizabalaga