Computer Vision: Transposed Convolution

Transposed convolution Article directory transposed convolution basic operation Padding, Striding, and Multipass nature Transposed Convolution (Transposed Convolution), also known as Deconvolution (Deconvolution), is an operation in a convolutional neural network (CNN), which can convert a low-dimensional feature map (such as the output of a convolutional layer) Convert to a higher-dimensional feature map (like the input […]

Head SongArray-Transpose of Sparse Matrix

Array – transpose of sparse matrix Level 1: General transposition algorithm Task Description The task of this level: realize the transpose operation of the sparse matrix (using the general transpose algorithm, that is, transpose in column order). Related knowledge In order to complete the task of this level, you need to understand: 1. Compressed storage […]

Image matrix transpose performance optimization example

Example of image matrix transposition performance optimization Article directory Image matrix transpose performance optimization example 1. Background 2. main function 3. CPU mode 3.1 Read continuously, write skip 3.2 Read jump, write continuous 3.3 Execution time-consuming 3.4 Conclusion 4. NEON mode 4.1 NEON 8×8 matrix 4.2 NEON 16×8 matrix 4.3 NEON 16×8 matrix prefetching 4.4 […]

PyTorch’s two transpose functions transpose() and permute() and view() and resize()

Article directory 1. Official Documentation transpose() permute() 2. Similarities 3. Differences legality is different example: 4. About continuous contiguous() 5. Summary 6.view() 7. reshape() The only functions used for transposition in pytorch are these two 1.transpose() 2.permute() Note that only transpose() has a suffix format: transpose_(): The function of the suffix function is to simplify […]

Opencv geometric space transformation: resize(), transpose(), flip(), warpAffine(), rotate(), warpPerspective()

1. Zoom resize() resize() can reduce or enlarge the image size dst=cv2.resize(src, dsize[, dst[, fx[, fy[, interpolation]]]]) src: source image; dsize: The size of the target image after zooming. If it is set to 0, the target image will be obtained by multiplying the size of the source image by fx and fy; dsize has […]

[Solved] Bug fix – TypeError: transpose() received an invalid combination of arguments – got (int, int, int, int)

Bug: TypeError: transpose() received an invalid combination of arguments – got (int, int, int, int), but expected one of: * (name dim0, name dim1) * (int dim0, int dim1) Solution: The wrong number of parameters are passed to transpose, transpose can only exchange two dimensions at a time import torch x=torch.rand(2,3,4,5) torch.transpose(x,0,3) #or x.transpose(0,3) To […]