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// Copyright 2016 Drew Short <drew@sothr.com>.
//
// Licensed under the MIT license<LICENSE-MIT or http://opensource.org/licenses/MIT>.
// This file may not be copied, modified, or distributed except according to those terms.
extern crate image;
use std::path::Path;
use cache::Cache;
use super::{HashType, PerceptualHash, Precision, PreparedImage};
use super::dft;
use super::dft::Transform;
use super::image::Pixel;
use super::prepare_image;
use self::image::{DynamicImage, GenericImage, GenericImageView};
pub struct PHash<'a> {
prepared_image: Box<PreparedImage<'a>>,
}
impl<'a> PHash<'a> {
pub fn new(path: &'a Path, precision: &Precision, cache: &Option<Cache>) -> Self {
PHash {
prepared_image: Box::new(prepare_image(&path, &HashType::PHash, &precision, cache)),
}
}
}
impl<'a> PerceptualHash for PHash<'a> {
/**
* Calculate the phash of the provided prepared image
*
* # Return
*
* Returns a u64 representing the value of the hash
*/
fn get_hash(&self, cache: &Option<Cache>) -> u64 {
match self.prepared_image.image {
Some(ref image) => {
// Get the image data into a vector to perform the DFT on.
let (width, height) = image.dimensions();
// Get 2d data to 2d FFT/DFT
// Either from the cache or calculate it
// Pretty fast already, so caching doesn't make a huge difference
// Atleast compared to opening and processing the images
let data_matrix: Vec<Vec<f64>> = match *cache {
Some(ref c) => {
match c.get_matrix_from_cache(&Path::new(self.prepared_image.orig_path),
width as u32) {
Some(matrix) => matrix,
None => {
let matrix = create_data_matrix(width, height, &image);
match c.put_matrix_in_cache(&Path::new(self.prepared_image.orig_path),
width as u32,
&matrix) {
Ok(_) => {}
Err(e) => println!("Unable to store matrix in cache. {}", e),
};
matrix
}
}
}
None => create_data_matrix(width, height, &image),
};
// Only need the top left quadrant
let target_width = (width / 4) as usize;
let target_height = (height / 4) as usize;
let dft_width = (width / 4) as f64;
let dft_height = (height / 4) as f64;
// Calculate the mean
let mut total = 0f64;
for x in 0..target_width {
for y in 0..target_height {
total += data_matrix[x][y];
}
}
let mean = total / (dft_width * dft_height);
// Calculating a hash based on the mean
let mut hash = 0u64;
for x in 0..target_width {
for y in 0..target_height {
if data_matrix[x][y] >= mean {
hash |= 1;
} else {
hash |= 0;
}
hash <<= 1;
}
}
hash
}
None => 0u64,
}
}
}
fn create_data_matrix(width: u32,
height: u32,
image: &DynamicImage)
-> Vec<Vec<f64>> {
let mut data_matrix: Vec<Vec<f64>> = Vec::new();
// Preparing the results
for x in 0..width as usize {
data_matrix.push(Vec::new());
for y in 0..height {
let pos_x = x as u32;
let pos_y = y as u32;
data_matrix[x].push(image.get_pixel(pos_x, pos_y).channels()[0] as f64);
}
}
// Perform the 2D DFT operation on our matrix
calculate_2d_dft(&mut data_matrix);
data_matrix
}
// Use a 1D DFT to cacluate the 2D DFT.
//
// This is achieved by calculating the DFT for each row, then calculating the
// DFT for each column of DFT row data. This means that a 32x32 image with have
// 1024 1D DFT operations performed on it. (Slightly caclulation intensive)
//
// This operation is in place on the data in the provided vector
//
// Inspired by:
// http://www.inf.ufsc.br/~visao/khoros/html-dip/c5/s2/front-page.html
//
// Checked with:
// http://calculator.vhex.net/post/calculator-result/2d-discrete-fourier-transform
//
fn calculate_2d_dft(data_matrix: &mut Vec<Vec<f64>>) {
// println!("{:?}", data_matrix);
let width = data_matrix.len();
let height = data_matrix[0].len();
let mut complex_data_matrix = Vec::with_capacity(width);
// Perform DCT on the columns of data
for x in 0..width {
let mut column: Vec<f64> = Vec::with_capacity(height);
for y in 0..height {
column.push(data_matrix[x][y]);
}
// Perform the DCT on this column
// println!("column[{}] before: {:?}", x, column);
let forward_plan = dft::Plan::new(dft::Operation::Forward, column.len());
column.transform(&forward_plan);
let complex_column = dft::unpack(&column);
// println!("column[{}] after: {:?}", x, complex_column);
complex_data_matrix.push(complex_column);
}
// Perform DCT on the rows of data
for y in 0..height {
let mut row = Vec::with_capacity(width);
for x in 0..width {
row.push(complex_data_matrix[x][y]);
}
// Perform DCT on the row
// println!("row[{}] before: {:?}", y, row);
let forward_plan = dft::Plan::new(dft::Operation::Forward, row.len());
row.transform(&forward_plan);
// println!("row[{}] after: {:?}", y, row);
// Put the row values back
for x in 0..width {
data_matrix[x][y] = round_float(row[x].re);
}
}
}
fn round_float(f: f64) -> f64 {
if f >= super::FLOAT_PRECISION_MAX_1 || f <= super::FLOAT_PRECISION_MIN_1 {
f
} else if f >= super::FLOAT_PRECISION_MAX_2 || f <= super::FLOAT_PRECISION_MIN_2 {
(f * 10_f64).round() / 10_f64
} else if f >= super::FLOAT_PRECISION_MAX_3 || f <= super::FLOAT_PRECISION_MIN_3 {
(f * 100_f64).round() / 100_f64
} else if f >= super::FLOAT_PRECISION_MAX_4 || f <= super::FLOAT_PRECISION_MIN_4 {
(f * 1000_f64).round() / 1000_f64
} else if f >= super::FLOAT_PRECISION_MAX_5 || f <= super::FLOAT_PRECISION_MIN_5 {
(f * 10000_f64).round() / 10000_f64
} else {
(f * 100000_f64).round() / 100000_f64
}
}
#[test]
fn test_2d_dft() {
let mut test_matrix: Vec<Vec<f64>> = Vec::new();
test_matrix.push(vec![1f64, 1f64, 1f64, 3f64]);
test_matrix.push(vec![1f64, 2f64, 2f64, 1f64]);
test_matrix.push(vec![1f64, 2f64, 2f64, 1f64]);
test_matrix.push(vec![3f64, 1f64, 1f64, 1f64]);
println!("{:?}", test_matrix[0]);
println!("{:?}", test_matrix[1]);
println!("{:?}", test_matrix[2]);
println!("{:?}", test_matrix[3]);
println!("Performing 2d DFT");
calculate_2d_dft(&mut test_matrix);
println!("{:?}", test_matrix[0]);
println!("{:?}", test_matrix[1]);
println!("{:?}", test_matrix[2]);
println!("{:?}", test_matrix[3]);
assert!(test_matrix[0][0] == 24_f64);
assert!(test_matrix[0][1] == 0_f64);
assert!(test_matrix[0][2] == 0_f64);
assert!(test_matrix[0][3] == 0_f64);
assert!(test_matrix[1][0] == 0_f64);
assert!(test_matrix[1][1] == 0_f64);
assert!(test_matrix[1][2] == -2_f64);
assert!(test_matrix[1][3] == 2_f64);
assert!(test_matrix[2][0] == 0_f64);
assert!(test_matrix[2][1] == -2_f64);
assert!(test_matrix[2][2] == -4_f64);
assert!(test_matrix[2][3] == -2_f64);
assert!(test_matrix[3][0] == 0_f64);
assert!(test_matrix[3][1] == 2_f64);
assert!(test_matrix[3][2] == -2_f64);
assert!(test_matrix[3][3] == 0_f64);
}
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