未验证 提交 fb87df66 编写于 作者: R RichardWooSJTU 提交者: GitHub

Fix nms op docs (#41792)

* fix nms op doc missing default value
上级 9db6c762
...@@ -1399,26 +1399,27 @@ def nms(boxes, ...@@ -1399,26 +1399,27 @@ def nms(boxes,
IoU = \frac{intersection\_area(box1, box2)}{union\_area(box1, box2)} IoU = \frac{intersection\_area(box1, box2)}{union\_area(box1, box2)}
If scores are provided, input boxes will be sorted by their scores firstly. If scores are provided, input boxes will be sorted by their scores firstly.
If category_idxs and categories are provided, NMS will be performed with a batched style, If category_idxs and categories are provided, NMS will be performed with a batched style,
which means NMS will be applied to each category respectively and results of each category which means NMS will be applied to each category respectively and results of each category
will be concated and sorted by scores. will be concated and sorted by scores.
If K is provided, only the first k elements will be returned. Otherwise, all box indices sorted by scores will be returned. If K is provided, only the first k elements will be returned. Otherwise, all box indices sorted by scores will be returned.
Args: Args:
boxes(Tensor): The input boxes data to be computed, it's a 2D-Tensor with boxes(Tensor): The input boxes data to be computed, it's a 2D-Tensor with
the shape of [num_boxes, 4] and boxes should be sorted by their the shape of [num_boxes, 4]. The data type is float32 or float64.
confidence scores. The data type is float32 or float64.
Given as [[x1, y1, x2, y2], …], (x1, y1) is the top left coordinates, Given as [[x1, y1, x2, y2], …], (x1, y1) is the top left coordinates,
and (x2, y2) is the bottom right coordinates. and (x2, y2) is the bottom right coordinates.
Their relation should be ``0 <= x1 < x2 && 0 <= y1 < y2``. Their relation should be ``0 <= x1 < x2 && 0 <= y1 < y2``.
iou_threshold(float32): IoU threshold for determine overlapping boxes. Default value: 0.3. iou_threshold(float32, optional): IoU threshold for determine overlapping boxes. Default value: 0.3.
scores(Tensor, optional): Scores corresponding to boxes, it's a 1D-Tensor with scores(Tensor, optional): Scores corresponding to boxes, it's a 1D-Tensor with
shape of [num_boxes]. The data type is float32 or float64. shape of [num_boxes]. The data type is float32 or float64. Default: None.
category_idxs(Tensor, optional): Category indices corresponding to boxes. category_idxs(Tensor, optional): Category indices corresponding to boxes.
it's a 1D-Tensor with shape of [num_boxes]. The data type is int64. it's a 1D-Tensor with shape of [num_boxes]. The data type is int64. Default: None.
categories(List, optional): A list of unique id of all categories. The data type is int64. categories(List, optional): A list of unique id of all categories. The data type is int64. Default: None.
top_k(int64, optional): The top K boxes who has higher score and kept by NMS preds to top_k(int64, optional): The top K boxes who has higher score and kept by NMS preds to
consider. top_k should be smaller equal than num_boxes. consider. top_k should be smaller equal than num_boxes. Default: None.
Returns: Returns:
Tensor: 1D-Tensor with the shape of [num_boxes]. Indices of boxes kept by NMS. Tensor: 1D-Tensor with the shape of [num_boxes]. Indices of boxes kept by NMS.
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