code: def create(cls, h:int, w:int, bboxes:Collection[Collection[int]], labels:Collection=None, classes:dict=None,
                 pad_idx:int=0, scale:bool=True)->'ImageBBox':
          "Create an ImageBBox object from `bboxes`."
          if isinstance(bboxes, np.ndarray) and bboxes.dtype == np.object: bboxes = np.array([bb for bb in bboxes])
          bboxes = tensor(bboxes).float()
          tr_corners = torch.cat([bboxes[:,0][:,None], bboxes[:,3][:,None]], 1)
          bl_corners = bboxes[:,1:3].flip(1)
          bboxes = torch.cat([bboxes[:,:2], tr_corners, bl_corners, bboxes[:,2:]], 1)
          flow = FlowField((h,w), bboxes.view(-1,2))
          return cls(flow, labels=labels, classes=classes, pad_idx=pad_idx, y_first=True, scale=scalef create(cls, h:int, w:int, bboxes:Collection[Collection[int]], labels:Collection=None, classes:dict=None,
                 pad_idx:int=0, scale:bool=True)->'ImageBBox':
          "Create an ImageBBox object from `bboxes`."
          if isinstance(bboxes, np.ndarray) and bboxes.dtype == np.object: bboxes = np.array([bb for bb in bboxes])
          bboxes = tensor(bboxes).float()
          tr_corners = torch.cat([bboxes[:,0][:,None], bboxes[:,3][:,None]], 1)
          bl_corners = bboxes[:,1:3].flip(1)
          bboxes = torch.cat([bboxes[:,:2], tr_corners, bl_corners, bboxes[:,2:]], 1)
          flow = FlowField((h,w), bboxes.view(-1,2))
          return cls(flow, labels=labels, classes=classes, pad_idx=pad_idx, y_first=True, scale=scale)
docs: Create an ImageBBox object from `bboxes`.