latest yolov5 and tflite too many detection boxes.
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i've trained yolov5 models in the past that worked well in voxl2s tflite environment
Something changed in maybe the latest Voxl sdk or in the way ultralytics is generating Yolov5 models during training.
which cause the multiple nonsensical detection boxes in the image.i was able to reproduce this error with the yolov8 model by including the wrong number of classes in yolov8_label.txt .
so i assumed the same with yolov5 but no matter what number of classes are in yolov5_labels.txt i get the multiple boxes.
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