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Proposal

Versioned name : Proposal-1

Category : Object detection

Short description : Proposal operation filters bounding boxes and outputs only those with the highest prediction confidence.

Detailed description

Proposal has three inputs: a tensor with probabilities whether particular bounding box corresponds to background and foreground, a tensor with bbox_deltas for each of the bounding boxes, a tensor with input image size in the [image_height, image_width, scale_height_and_width] or [image_height, image_width, scale_height, scale_width] format. The produced tensor has two dimensions [batch_size \* post_nms_topn, 5], and for each output box contains batch index and box coordinates. Proposal layer does the following with the input tensor:

1. Generates initial anchor boxes. Left top corner of all boxes is at (0, 0). Width and height of boxes are calculated from base_size with scale and ratio attributes.

2. For each point in the first input tensor:

   • pins anchor boxes to the image according to the second input tensor that contains four deltas for each box: for x and y of center, for width and for height

   • finds out score in the first input tensor

3. Filters out boxes with size less than min_size

4. Sorts all proposals (box, score) by score from highest to lowest

5. Takes top pre_nms_topn proposals

6. Calculates intersections for boxes and filter out all boxes with \(intersection/union > nms\_thresh\)

7. Takes top post_nms_topn proposals

8. Returns top proposals, if there is not enough proposals to fill the whole output tensor, the valid proposals will be terminated with a single -1.

Attributes :

• base_size

  • Description : base_size is the size of the anchor to which scale and ratio attributes are applied.

  • Range of values : a positive integer number

  • Type : int

  • Required : yes

• pre_nms_topn

  • Description : pre_nms_topn is the number of bounding boxes before the NMS operation. For example, pre_nms_topn equal to 15 means to take top 15 boxes with the highest scores.

  • Range of values : a positive integer number

  • Type : int

  • Required : yes

• post_nms_topn

  • Description : post_nms_topn is the number of bounding boxes after the NMS operation. For example, post_nms_topn equal to 15 means to take after NMS top 15 boxes with the highest scores.

  • Range of values : a positive integer number

  • Type : int

  • Required : yes

• nms_thresh

  • Description : nms_thresh is the minimum value of the proposal to be taken into consideration. For example, nms_thresh equal to 0.5 means that all boxes with prediction probability less than 0.5 are filtered out.

  • Range of values : a positive floating-point number

  • Type : float

  • Required : yes

• feat_stride

  • Description : feat_stride is the step size to slide over boxes (in pixels). For example, feat_stride equal to 16 means that all boxes are analyzed with the slide 16.

  • Range of values : a positive integer

  • Type : int

  • Required : yes

• min_size

  • Description : min_size is the minimum size of box to be taken into consideration. For example, min_size equal 35 means that all boxes with box size less than 35 are filtered out.

  • Range of values : a positive integer number

  • Type : int

  • Required : yes

• ratio

  • Description : ratio is the ratios for anchor generation.

  • Range of values : a list of floating-point numbers

  • Type : float[]

  • Required : yes

• scale

  • Description : scale is the scales for anchor generation.

  • Range of values : a list of floating-point numbers

  • Type : float[]

  • Required : yes

• clip_before_nms

  • Description : clip_before_nms flag that specifies whether to perform clip bounding boxes before non-maximum suppression or not.

  • Range of values : true or false

  • Type : boolean

  • Default value : true

  • Required : no

• clip_after_nms

  • Description : clip_after_nms is a flag that specifies whether to perform clip bounding boxes after non-maximum suppression or not.

  • Range of values : true or false

  • Type : boolean

  • Default value : false

  • Required : no

• normalize

  • Description : normalize is a flag that specifies whether to perform normalization of output boxes to [0,1] interval or not.

  • Range of values : true or false

  • Type : boolean

  • Default value : false

  • Required : no

• box_size_scale

  • Description : box_size_scale specifies the scale factor applied to bbox_deltas of box sizes before decoding.

  • Range of values : a positive floating-point number

  • Type : float

  • Default value : 1.0

  • Required : no

• box_coordinate_scale

  • Description : box_coordinate_scale specifies the scale factor applied to bbox_deltas of box coordinates before decoding.

  • Range of values : a positive floating-point number

  • Type : float

  • Default value : 1.0

  • Required : no

• framework

  • Description : framework specifies how the box coordinates are calculated.

  • Range of values :

    • “” (empty string) - calculate box coordinates like in Caffe*

    • tensorflow - calculate box coordinates like in the TensorFlow* Object Detection API models

  • Type : string

  • Default value : “” (empty string)

  • Required : no

Inputs :

• 1 : 4D tensor of type T and shape [batch_size, 2\*K, H, W] with class prediction scores. Required.

• 2 : 4D tensor of type T and shape [batch_size, 4\*K, H, W] with deltas for each bounding box. Required.

• 3 : 1D tensor of type T with 3 or 4 elements: [image_height, image_width, scale_height_and_width] or [image_height, image_width, scale_height, scale_width]. Required.

Outputs :

• 1 : Tensor of type T and shape [batch_size \* post_nms_topn, 5].

Types

• T : floating-point type.

Example

<layer ... type="Proposal" ... >
    <data base_size="16" feat_stride="16" min_size="16" nms_thresh="0.6" post_nms_topn="200" pre_nms_topn="6000"
     ratio="2.67" scale="4.0,6.0,9.0,16.0,24.0,32.0"/>
    <input> ... </input>
    <output> ... </output>
</layer>

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