This class implements a layer that transforms a set of two-dimensional multi-channel images into a set of images of smaller size but with more channels. This operation is used in YOLO architecture.
void SetStride( int stride );
Sets the value by which the image size will be divided in the final result. The image size along either dimension should be a multiple of this value. The value should be greater than 1
.
The layer has no trainable parameters.
The single input accepts a blob with the images, of the dimensions:
BatchLength * BatchWidth * ListSize
is equal to the number of imagesHeight
is the image height; should be a multiple ofGetStride()
Width
is the image width; should be a multiple ofGetStride()
Depth
is equal to1
Channels
is the number of channels in the image format
The single output contains a blob with the resulting images, of the dimensions:
BatchLength
is equal to the inputBatchLength
BatchWidth
is equal to the inputBatchWidth
ListSize
is equal to the inputListSize
Height
is equal to the inputHeight / GetStride()
Width
is equal to the inputWidth / GetStride()
Depth
is equal to1
Channels
is equal to the inputChannels * GetStride() * GetStride()
Each image in the set is split in the same way as the following sample.
Assume we have a 2-channel image 4
by 6
, and GetStride()
is 2
. The image pixel values are:
// First channel contents
1, 2, 3, 4, 5, 6,
7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18,
19, 20, 21, 22, 23, 24,
// Second channel contents
25, 26, 27, 28, 29, 30,
31, 32, 33, 34, 35, 36,
37, 38, 39, 40, 41, 42,
43, 44, 45, 46, 47, 48
This image will be transformed into a 8-channel image 2
by 3
, with the contents:
// First channel contents
1, 3, 5,
7, 9, 11,
// Second channel contents
25, 27, 29,
31, 33, 35,
// Third channel contents
13, 15, 17,
19, 21, 23,
// Fourth channel contents
37, 39, 41,
43, 45, 47
// Fifth channel contents
2, 4, 6,
8, 10, 12,
// Sixth channel contents
26, 28, 30,
32, 34, 36,
// Seventh channel contents
14, 16, 18,
20, 22, 24,
// Eighth channel contents
38, 40, 42,
44, 46, 48