The changes made to this copy of YOLOv5 are intended primarily to get rid of post-processing on the device after export.
Additionally, a simple sorting of results was added to work with ordered recognized objects, such as numerical sequences.

Changelog:

• models/experimental.py
  line 118 add:

  #sort ordered recognized objects
    def new_sorter

  line 126 add:

  #nms from main model with little changes that solve the problem with the occurrence of errors when exporting using torch.jit.trace
    def nms_lite

• models/yolo.py
  line 169 add:

  #flag for add postprocessing to export. when True on device u got only detections
    is_export=False

  line 172 add:

  #defoult treshhold for experimental.py/new_sort (sort detected digits on axis X)
    treshhold=0.8

  line 214 (def forward) change:

   if augment to if augment and not self.is_export 

  line 216 change:

  return self._forward_once(x, profile, visualize)

  to (our outputs)

    out=self._forward_once(x, profile, visualize)    
    if self.is_export:      
      return new_sorter(nms_lite(out)[0], self.treshhold)      
    else:
      return out

• export.py
  line 120 change:

  f = file.with_suffix('.torchscript')

  to

  f = file.with_suffix('.torchscript.ptl')

  line 542 add:

  model.is_export=True

By default, the flag is set to false in order to avoid affecting the training process of the model.
Changes are relevant only for the exported model, therefore the truth is set only when exporting

The results can be seen:
Jupyter Notebook
Android App