box_convert¶
- torchvision.ops.box_convert(boxes: Tensor, in_fmt: str, out_fmt: str) Tensor[source]¶
- Converts - torch.Tensorboxes from a given- in_fmtto- out_fmt.- Note - For converting a - torch.Tensoror a- BoundingBoxesobject between different formats, consider using- convert_bounding_box_format()instead. Or see the corresponding transform- ConvertBoundingBoxFormat().- Supported - in_fmtand- out_fmtstrings are:- 'xyxy': boxes are represented via corners, x1, y1 being top left and x2, y2 being bottom right. This is the format that torchvision utilities expect.- 'xywh': boxes are represented via corner, width and height, x1, y2 being top left, w, h being width and height.- 'cxcywh': boxes are represented via centre, width and height, cx, cy being center of box, w, h being width and height.- 'xywhr': boxes are represented via corner, width and height, x1, y2 being top left, w, h being width and height. r is rotation angle w.r.t to the box center by \(|r|\) degrees counter clock wise in the image plan- 'cxcywhr': boxes are represented via centre, width and height, cx, cy being center of box, w, h being width and height. r is rotation angle w.r.t to the box center by \(|r|\) degrees counter clock wise in the image plan- 'xyxyxyxy': boxes are represented via corners, x1, y1 being top left, x2, y2 top right, x3, y3 bottom right, and x4, y4 bottom left.- Parameters:
- boxes (Tensor[N, K]) – boxes which will be converted. K is the number of coordinates (4 for unrotated bounding boxes, 5 or 8 for rotated bounding boxes) 
- in_fmt (str) – Input format of given boxes. Supported formats are [‘xyxy’, ‘xywh’, ‘cxcywh’, ‘xywhr’, ‘cxcywhr’, ‘xyxyxyxy’]. 
- out_fmt (str) – Output format of given boxes. Supported formats are [‘xyxy’, ‘xywh’, ‘cxcywh’, ‘xywhr’, ‘cxcywhr’, ‘xyxyxyxy’] 
 
- Returns:
- Boxes into converted format. 
- Return type:
- Tensor[N, K]