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					## libfastimagehash
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					[](https://www.codefactor.io/repository/github/simon987/fastimagehash/overview/master)
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					[](https://github.com/simon987/fastimagehash/blob/master/LICENSE)
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					*WIP: Not ready for production use!*
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					`libfastimagehash` is a [imagehash](https://github.com/JohannesBuchner/imagehash/) 
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					replacement for C/C++.
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					<p align="center">
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					  <img src="bench/results/phash_large.png"/>
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					</p>
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					*[\*benchmarks](bench/)*
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					### Example usage
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					```C++
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					#include "fastimagehash.h"
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					int main() {
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					    // TODO
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					}
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					```
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					### Build from source
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					// TODO
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					**Built with** 
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					* [opencv](https://github.com/opencv) for image decoding & resizing
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					* [wavelib](https://github.com/rafat/wavelib) for wavelet decomposition in `whash`  (With [additional CFLAGS](https://github.com/simon987/wavelib/commit/8d05b0b7321271b05365d3e89bfb0fd5a26d68a6))
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					* [fftw3](http://fftw.org/) for DCT in `phash`
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					* [google/benchmark](https://github.com/google/benchmark) to measure performance
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					**Disclaimer**: The methods used to compute the image hashes
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					are identical to the `imagehash` python library, however, due to
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					some slight differences in the way OpenCV vs Pillow images are resized,
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					the final image hashes are not always exactly the same. 
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					To run the benchmarks:
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					```bash
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					python run.py
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					```
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					All benchmarks were ran with
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					```
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					i7-7500U CPU @ 2.70GHz x 4
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					gcc version 9.2.0
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					Python 3.8.0
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					imagehash 4.0
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					fastimagehash v0.1
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					```
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					### Results
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					**phash**
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					**dhash**
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					**whash**
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					**ahash**
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