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Refine the doc in detection_output API. #8689
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@@ -54,11 +54,12 @@ def detection_output(loc, | |
score_threshold=0.01, | ||
nms_eta=1.0): | ||
""" | ||
**Detection Output Layer** | ||
**Detection Output Layer for SSD.** | ||
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This layer applies the NMS to the output of network and computes the | ||
predict bounding box location. The output's shape of this layer could | ||
be zero if there is no valid bounding box. | ||
This operation decode the predicted bboxes according to the prior bboxes | ||
at first, then applying multi-class non maximum suppression (NMS) on the | ||
decoded boxes and scores to get the detected bounding boxed. The output | ||
layout is described as follows. | ||
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Args: | ||
loc(Variable): A 3-D Tensor with shape [N, M, 4] represents the | ||
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@@ -91,7 +92,14 @@ class number, M is number of bounding boxes. For each category | |
nms_eta(float): The parameter for adaptive NMS. | ||
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Returns: | ||
The detected bounding boxes which are a Tensor. | ||
Variable: The detection outputs which is a LoDTensor with shape [No, 6]. | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. There should be a comma (,) before "which". There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Re-write the doc. Thanks! |
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Each row has 6 values: [label, confidence, xmin, ymin, xmax, ymax], | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Use six instead 6. There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Done. Thanks! |
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No is the total number of detections in this mini-batch. For each | ||
instance, the offsets in first dimension are called LoD, the number | ||
offset is N + 1, N is the batch size. If LoD[i + 1] - LoD[i] == 0, | ||
means there is no detected bboxes for for i-th image. If there is | ||
no detected boxes for all images, all the elements in LoD are 0, | ||
and the Out only contains one value which is -1. | ||
There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. the Out => Out There was a problem hiding this comment. Choose a reason for hiding this commentThe reason will be displayed to describe this comment to others. Learn more. Re-write the doc. Thanks! |
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Examples: | ||
.. code-block:: python | ||
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Re-write the doc. Thanks!