fft-c | Elegant Fast Fourier Transform in C. Making fft | Video Utils library

by adis300 C Version: Current License: MIT

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kandi X-RAY | fft-c Summary

fft-c is a C library typically used in Video, Video Utils applications. fft-c has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Elegant Fast Fourier Transform in C. Making fft.c from fftpack user-friendly.

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fft-c has a low active ecosystem.

It has 20 star(s) with 3 fork(s). There are 4 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of fft-c is current.

Quality

fft-c has 0 bugs and 0 code smells.

Security

fft-c has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

fft-c code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

fft-c is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

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fft-c releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

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fft-c Key Features

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fft-c Examples and Code Snippets

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Community Discussions

Trending Discussions on fft-c

C++ static object does not save array attribute value

torch.rfft - fft-based convolution creating different output than spatial convolution

QUESTION

C++ static object does not save array attribute value

Asked 2021-Jul-01 at 13:58

I am working in C++ inside Vitis HLS from Xilinx. I am writing a simple buffer to perform the well know overlap and add algorithm (https://www.eetimes.com/fft-convolution-and-the-overlap-add-method/)

My code creates a static object (my buffer) and then works with a "sample-wise" approach.

The code I am using is the following (header + function to be synthesized + testbench):

Overlapper_HLS.hpp:

...

ANSWER

Answered 2021-Jul-01 at 13:58

The main problem was the usage of my #define BUFFER IFFT_LENGTH - INPUT_WINDOW_LENGTH inside the indexing of the following code snippet:

Source https://stackoverflow.com/questions/68208152

QUESTION

torch.rfft - fft-based convolution creating different output than spatial convolution

Asked 2020-Jun-08 at 14:53

I implemented FFT-based convolution in Pytorch and compared the result with spatial convolution via conv2d() function. The convolution filter used is an average filter. The conv2d() function produced smoothened output due to average filtering as expected but the fft-based convolution returned a more blurry output. I have attached the code and outputs here -

spatial convolution -

...

ANSWER

Answered 2020-Jun-08 at 14:53

The main problem with your code is that Torch doesn't do complex numbers, the output of its FFT is a 3D array, with the 3rd dimension having two values, one for the real component and one for the imaginary. Consequently, the multiplication does not do a complex multiplication.

There currently is no complex multiplication defined in Torch (see this issue), we'll have to define our own.

A minor issue, but also important if you want to compare the two convolution operations, is the following:

The FFT takes the origin of its input in the first element (top-left pixel for an image). To avoid a shifted output, you need to generate a padded kernel where the origin of the kernel is the top-left pixel. This is quite tricky, actually...

Your current code:

Source https://stackoverflow.com/questions/62246089

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

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