class_docstr: FiftyOne wrapper around YOLO-NAS from
  https://github.com/Deci-AI/super-gradients.
  
  Args:
      config: a :class:`TorchYoloNasModelConfig`
class_docstr_tok: ["FiftyOne","wrapper","around","YOLO-NAS","from","https",":","\/\/github.com\/Deci-AI\/super-gradients",".","Args",":","config",":","a",":","class",":","`","TorchYoloNasModelConfig","`"]
code: def _convert_bboxes(self, bboxes, w, h):
      tmp = np.copy(bboxes[:, 1])
      bboxes[:, 1] = h - bboxes[:, 3]
      bboxes[:, 3] = h - tmp
      bboxes[:, 0] /= w
      bboxes[:, 2] /= w
      bboxes[:, 1] /= h
      bboxes[:, 3] /= h
      bboxes[:, 2] -= bboxes[:, 0]
      bboxes[:, 3] -= bboxes[:, 1]
      bboxes[:, 1] = 1 - (bboxes[:, 1] + bboxes[:, 3])
      return bboxes
  
file_path: fiftyone/fiftyone/utils/super_gradients.py
imports: import logging
  import fiftyone
  import fiftyone.core.utils
  import fiftyone.utils.torch
  import fiftyone.zoo.models
  import torch
  import numpy
label_desc: Use image node_id 2 for calling the TorchYoloNasModel obj's underlying member method code with example usage: obj._convert_bboxes(bboxes, w, h) and returns: bboxes