├── .github └── workflows │ └── rust.yml ├── .gitignore ├── Cargo.toml ├── LICENSE ├── README.md ├── src ├── image.rs └── lib.rs └── tests └── stats.rs /.github/workflows/rust.yml: -------------------------------------------------------------------------------- 1 | name: Rust 2 | 3 | on: 4 | push: 5 | branches: [ "main" ] 6 | pull_request: 7 | branches: [ "main" ] 8 | 9 | env: 10 | CARGO_TERM_COLOR: always 11 | 12 | jobs: 13 | build: 14 | 15 | runs-on: ubuntu-latest 16 | 17 | steps: 18 | - uses: actions/checkout@v4 19 | - name: Build 20 | run: cargo build --verbose 21 | - name: Run tests 22 | run: cargo test --verbose 23 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | /target 2 | /Cargo.lock 3 | .idea/ 4 | *.iml 5 | *.jpg 6 | .DS_Store -------------------------------------------------------------------------------- /Cargo.toml: -------------------------------------------------------------------------------- 1 | [package] 2 | name = "image-match" 3 | version = "0.2.4-dev" 4 | edition = "2021" 5 | description = "Derives an image signature to be used in quick image comparisons" 6 | license = "GPL-3.0" 7 | homepage = "https://alt-text.org" 8 | repository = "https://github.com/alt-text-org/image-match-rs" 9 | documentation = "http://www.cs.cmu.edu/~hcwong/Pdfs/icip02.ps" 10 | keywords = ["image", "similarity", "vector", "signature"] 11 | 12 | [dependencies] 13 | image = { version = "0.24.6", optional = true} 14 | num = "0.4.0" 15 | 16 | [features] 17 | img = ["image"] 18 | 19 | [dev-dependencies] 20 | pretty_assertions = "1.4.0" 21 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | The implemented paper is available for free from the location linked 2 | in the README. 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It is safest 637 | to attach them to the start of each source file to most effectively 638 | state the exclusion of warranty; and each file should have at least 639 | the "copyright" line and a pointer to where the full notice is found. 640 | 641 | 642 | Copyright (C) 643 | 644 | This program is free software: you can redistribute it and/or modify 645 | it under the terms of the GNU General Public License as published by 646 | the Free Software Foundation, either version 3 of the License, or 647 | (at your option) any later version. 648 | 649 | This program is distributed in the hope that it will be useful, 650 | but WITHOUT ANY WARRANTY; without even the implied warranty of 651 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 652 | GNU General Public License for more details. 653 | 654 | You should have received a copy of the GNU General Public License 655 | along with this program. If not, see . 656 | 657 | Also add information on how to contact you by electronic and paper mail. 658 | 659 | If the program does terminal interaction, make it output a short 660 | notice like this when it starts in an interactive mode: 661 | 662 | Copyright (C) 663 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 664 | This is free software, and you are welcome to redistribute it 665 | under certain conditions; type `show c' for details. 666 | 667 | The hypothetical commands `show w' and `show c' should show the appropriate 668 | parts of the General Public License. Of course, your program's commands 669 | might be different; for a GUI interface, you would use an "about box". 670 | 671 | You should also get your employer (if you work as a programmer) or school, 672 | if any, to sign a "copyright disclaimer" for the program, if necessary. 673 | For more information on this, and how to apply and follow the GNU GPL, see 674 | . 675 | 676 | The GNU General Public License does not permit incorporating your program 677 | into proprietary programs. If your program is a subroutine library, you 678 | may consider it more useful to permit linking proprietary applications with 679 | the library. If this is what you want to do, use the GNU Lesser General 680 | Public License instead of this License. But first, please read 681 | . 682 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | image-match-rs 2 | ============== 3 | 4 | An implementation of the image matching algorithm described in 5 | [An Image Signature For Any Kind Of Image by H. Chi Wong, Marshall Bern, and David Goldberg](https://www.semanticscholar.org/paper/An-image-signature-for-any-kind-of-image-Wong-Bern/f0d7ae4a781b61dbf1c4fdcdc50dd82cc294d89f) 6 | . The algorithm is designed to detect nearly identical images, not images with the same conceptual content. 7 | 8 | 9 | Usage 10 | ===== 11 | 12 | By default, the library offers two primary functions: `get_buffer_signature(rgba, width)` and `cosine_similarity(a, b)`. 13 | The former takes a pre-processed slice of `u8`s with each chunk of four representing the 8-bit red, green, blue, and 14 | alpha of a pixel, the latter two result vectors to compute their similarity. Per the source paper and our experiments 15 | in [this research](https://github.com/alt-text-org/image-algo-testing) images with a similarity greater than `0.6` can 16 | be considered likely matches. If the tuning methods described below are used, additional research will likely be needed 17 | to assess a new cutoff. 18 | 19 | If the `img` feature is used, also provided are `get_image_signature(image)` and `get_file_signature(path)` which use 20 | the [image library](https://crates.io/crates/image) to handle unpacking the image into an rgba buffer. All signature 21 | functions also expose `tuned` versions which allow tweaking the crop percentage used during the signature computation, 22 | the size of the collection grid which controls the length of the feature vector produced, and the size of the 23 | square around each grid point averaged to produce a value for that point. It's recommended to study the algorithm 24 | closely before embarking on tuning, as the effects of these nobs are not immediately obvious. 25 | 26 | 27 | Future Work 28 | =========== 29 | - Additional unit testing. 30 | - Experimenting with parameter choice is underway in [this repo](https://github.com/alt-text-org/image-match-params). 31 | - Experiment with widening the possible values of each dimension in the produced signature. Presently per the paper they 32 | are all integers in `[-2, 2]`. It will likely require experimentation around a new suggested vector similarity cutoff. -------------------------------------------------------------------------------- /src/image.rs: -------------------------------------------------------------------------------- 1 | use std::cmp::{max, min}; 2 | use std::error::Error; 3 | use std::fmt::{Debug, Display, Formatter}; 4 | use std::io; 5 | use std::path::Path; 6 | 7 | use image::{GenericImageView, ImageError, Pixel}; 8 | use image::io::Reader as ImageReader; 9 | use num::ToPrimitive; 10 | 11 | use ImageReadError::{DecodeError, IoError}; 12 | 13 | use crate::{compute_from_gray, DEFAULT_CROP, DEFAULT_GRID_SIZE, pixel_gray}; 14 | 15 | /// Produces a 544 signed byte signature for a provided image. The result is designed to be compared 16 | /// to other vectors computed by a call to this method using [cosine-similarity(a, b)]. 17 | pub fn get_image_signature(img: I) -> Vec { 18 | let gray = grayscale_image(img); 19 | 20 | let average_square_width_fn = |width, height| { 21 | max( 22 | 2_usize, 23 | (0.5 + min(width, height) as f32 / 20.0).floor() as usize, 24 | ) / 2 25 | }; 26 | 27 | compute_from_gray(gray, DEFAULT_CROP, DEFAULT_GRID_SIZE, average_square_width_fn) 28 | } 29 | 30 | /// Produces a variable length signed byte signature for a provided image. The result is designed to 31 | /// be compared to other vectors computed by a call to this method with identical tuning parameters 32 | /// using [cosine-similarity(a, b)]. `crop` is a value in [0, 0.5] indicating what percentage of the 33 | /// image to crop on all sides before grid placement. Note that this percentage is based not on the 34 | /// raw width but a calculation of color density. `grid_size` indicates how many points to place on 35 | /// the image for measurement in the resulting signature. Changing `grid_size` will alter the length 36 | /// of the signature to `8 * (grid_size - 1)^2 - 12 * (grid_size - 3) - 20`. The 37 | /// `average_square_width_fn` controls the size of the box around each grid point that's averaged 38 | /// to produce that grid point's brightness value. The paper proposes 39 | /// `max(2, floor(0.5 + min(cropped_width, cropped_height) / 20))` but provides no information about 40 | /// how that was chosen. 41 | pub fn get_tuned_image_signature( 42 | img: I, 43 | crop: f32, 44 | grid_size: usize, 45 | average_square_width_fn: fn(width: usize, height: usize) -> usize, 46 | ) -> Vec { 47 | let gray = grayscale_image(img); 48 | compute_from_gray(gray, crop, grid_size, average_square_width_fn) 49 | } 50 | 51 | /// Produces a 544 signed byte signature for a provided image file. The result is designed to be 52 | /// compared to other vectors computed by a call to this method using [cosine-similarity(a, b)]. 53 | pub fn get_file_signature>(path: P) -> Result> { 54 | let image = ImageReader::open(path)?.decode()?; 55 | Ok(get_image_signature(image)) 56 | } 57 | 58 | /// Produces a variable length signed byte signature for a provided image file. The result is 59 | /// designed to be compared to other vectors computed by a call to this method with identical tuning 60 | /// parameters using [cosine-similarity(a, b)]. `crop` is a value in [0, 0.5] indicating what 61 | /// percentage of the image to crop on all sides before grid placement. Note that this percentage is 62 | /// based not on the raw width but a calculation of color density. `grid_size` indicates how many 63 | /// points to place on the image for measurement in the resulting signature. Changing `grid_size` 64 | /// will alter the length of the signature to `8 * (grid_size - 1)^2 - 12 * (grid_size - 3) - 20`. 65 | /// The `average_square_width_fn` controls the size of the box around each grid point that's 66 | /// averaged to produce that grid point's brightness value. The paper proposes 67 | /// `max(2, floor(0.5 + min(cropped_width, cropped_height) / 20))` but provides no information about 68 | /// how that was chosen. 69 | pub fn get_tuned_file_signature>( 70 | path: P, 71 | crop: f32, 72 | grid_size: usize, 73 | average_square_width_fn: fn(width: usize, height: usize) -> usize, 74 | ) -> Result> { 75 | let image = ImageReader::open(path)?.decode()?; 76 | Ok(get_tuned_image_signature(image, crop, grid_size, average_square_width_fn)) 77 | } 78 | 79 | pub enum ImageReadError { 80 | IoError(io::Error), 81 | DecodeError(ImageError), 82 | } 83 | 84 | impl Debug for ImageReadError { 85 | fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result { 86 | match self { 87 | IoError(e) => Debug::fmt(e, f), 88 | DecodeError(e) => Debug::fmt(e, f), 89 | } 90 | } 91 | } 92 | 93 | impl Display for ImageReadError { 94 | fn fmt(&self, f: &mut Formatter<'_>) -> std::fmt::Result { 95 | match self { 96 | IoError(e) => Display::fmt(e, f), 97 | DecodeError(e) => Display::fmt(e, f), 98 | } 99 | } 100 | } 101 | 102 | impl Error for ImageReadError { 103 | fn cause(&self) -> Option<&dyn Error> { 104 | match self { 105 | IoError(e) => Some(e), 106 | DecodeError(e) => Some(e) 107 | } 108 | } 109 | } 110 | 111 | impl From for ImageReadError { 112 | fn from(e: io::Error) -> Self { 113 | IoError(e) 114 | } 115 | } 116 | 117 | impl From for ImageReadError { 118 | fn from(e: ImageError) -> Self { 119 | DecodeError(e) 120 | } 121 | } 122 | 123 | pub type Result = std::result::Result; 124 | 125 | fn grayscale_image(img: I) -> Vec> { 126 | let pixels = img.pixels() 127 | .map(|(_, _, p)| p.to_rgba().0); 128 | 129 | let mut result = Vec::with_capacity(img.width() as usize); 130 | let mut row = Vec::with_capacity(img.height() as usize); 131 | let mut col = 0; 132 | for pixel in pixels { 133 | row.push(pixel_gray( 134 | pixel[0].to_u8().unwrap(), 135 | pixel[1].to_u8().unwrap(), 136 | pixel[2].to_u8().unwrap(), 137 | pixel[3].to_u8().unwrap(), 138 | )); 139 | col += 1; 140 | if col >= img.width() { 141 | result.push(row); 142 | row = Vec::with_capacity(img.height() as usize); 143 | col = 0; 144 | } 145 | } 146 | 147 | result 148 | } 149 | -------------------------------------------------------------------------------- /src/lib.rs: -------------------------------------------------------------------------------- 1 | use std::cmp::{max, min}; 2 | use std::collections::HashMap; 3 | 4 | #[allow(unused_imports)] // It's actually used, I promise 5 | use num::Signed; 6 | 7 | #[cfg(feature = "img")] 8 | pub mod image; 9 | 10 | const DEFAULT_CROP: f32 = 0.05; 11 | const DEFAULT_GRID_SIZE: usize = 10; 12 | 13 | /// Produces a 544 signed byte signature for a provided image that's encoded as an array of 14 | /// conceptually grouped RGBA bytes with the provided width. The result is designed to be compared 15 | /// to other vectors computed by a call to this method using [cosine-similarity(a, b)]. 16 | pub fn get_buffer_signature(rgba_buffer: &[u8], width: usize) -> Vec { 17 | let gray = grayscale_buffer(rgba_buffer, width); 18 | 19 | let average_square_width_fn = |width, height| { 20 | max( 21 | 2_usize, 22 | (0.5 + min(width, height) as f32 / 20.0).floor() as usize, 23 | ) / 2 24 | }; 25 | 26 | compute_from_gray(gray, DEFAULT_CROP, DEFAULT_GRID_SIZE, average_square_width_fn) 27 | } 28 | 29 | /// Produces a variable length signed byte signature for a provided image, encoded as an array of 30 | /// conceptually grouped RGBA bytes with the provided width. The result is designed to be compared 31 | /// to other vectors computed by a call to this method with identical tuning parameters using 32 | /// [cosine-similarity(a, b)]. `crop` is a value in [0, 0.5] indicating what percentage of the image 33 | /// to crop on all sides before grid placement. Note that this percentage is based not on the raw 34 | /// width but a calculation of color density. `grid_size` indicates how many points to place on the 35 | /// image for measurement in the resulting signature. Changing `grid_size` will alter the length of 36 | /// the signature to `8 * (grid_size - 1)^2 - 12 * (grid_size - 3) - 20`.The 37 | /// `average_square_width_fn` controls the size of the box around each grid point that's averaged 38 | /// to produce that grid point's brightness value. The paper proposes 39 | /// `max(2, floor(0.5 + min(cropped_width, cropped_height) / 20))` but provides no information about 40 | /// how that was chosen. 41 | pub fn get_tuned_buffer_signature( 42 | rgba_buffer: &[u8], 43 | width: usize, 44 | crop: f32, 45 | grid_size: usize, 46 | average_square_width_fn: fn(width: usize, height: usize) -> usize, 47 | ) -> Vec { 48 | let gray = grayscale_buffer(rgba_buffer, width); 49 | compute_from_gray(gray, crop, grid_size, average_square_width_fn) 50 | } 51 | 52 | /// Computes the cosine of the angle between two feature vectors. Those vectors must have been both 53 | /// produced by calls to an un-tuned signature function or identical calls to a tuned version. Per 54 | /// the source paper and out own research, when using the un-tuned signature calculation a cosine of 55 | /// 0.6 or greater indicates significant similarity. 56 | /// If either vector is all zeros, 57 | pub fn cosine_similarity(a: &Vec, b: &Vec) -> f64 { 58 | // For our purposes here, unequal lengths are a sign of major issues in client code. 59 | // One of my favorite professors always said "Crash early, crash often." 60 | assert_eq!(a.len(), b.len(), "Compared vectors must be of equal length"); 61 | 62 | let a_length = vector_length(a); 63 | let b_length = vector_length(b); 64 | if a_length == 0.0 || b_length == 0.0 { 65 | if a_length == 0.0 && b_length == 0.0 { 66 | 1.0 67 | } else { 68 | 0.0 69 | } 70 | } else { 71 | let dot_product: f64 = a.iter().zip(b.iter()) 72 | .map(|(av, bv)| *av as f64 * *bv as f64) 73 | .sum(); 74 | 75 | dot_product / (a_length * b_length) 76 | } 77 | } 78 | 79 | fn vector_length(v: &[i8]) -> f64 { 80 | v.iter().map(|vi| *vi as i32).map(|vi| (vi * vi) as f64).sum::().sqrt() 81 | } 82 | 83 | /// Core computation steps of image signatures. Descriptions for each step can be found on the 84 | /// called functions and are pulled directly from the implemented paper. 85 | fn compute_from_gray( 86 | gray: Vec>, 87 | crop: f32, 88 | grid_size: usize, 89 | average_square_width_fn: fn(width: usize, height: usize) -> usize, 90 | ) -> Vec { 91 | let bounds = crop_boundaries(&gray, crop); 92 | let points = grid_points(&bounds, grid_size); 93 | let averages = grid_averages(gray, points, bounds, average_square_width_fn); 94 | compute_signature(averages, grid_size) 95 | } 96 | 97 | /* 98 | Step 1. 99 | "If the image is color, we first convert it to 8-bit grayscale .. Pure white is represented by 255 100 | and pure black by 0." 101 | */ 102 | fn grayscale_buffer(rgba_buffer: &[u8], width: usize) -> Vec> { 103 | let height = (rgba_buffer.len() / 4) / width; 104 | let mut result = Vec::with_capacity(height); 105 | let mut idx: usize = 0; 106 | while idx < rgba_buffer.len() { 107 | let mut row = Vec::with_capacity(width); 108 | for _ in 0..width { 109 | let avg = pixel_gray( 110 | rgba_buffer[idx], 111 | rgba_buffer[idx + 1], 112 | rgba_buffer[idx + 2], 113 | rgba_buffer[idx + 3], 114 | ); 115 | 116 | row.push(avg); 117 | idx += 4; 118 | } 119 | result.push(row); 120 | } 121 | 122 | result 123 | } 124 | 125 | fn pixel_gray(r: u8, g: u8, b: u8, a: u8) -> u8 { 126 | let rgb_avg = (r as u16 + g as u16 + b as u16) / 3; 127 | ((rgb_avg as f32) * (a as f32 / 255.0)) as u8 128 | } 129 | 130 | #[derive(Debug, PartialEq)] 131 | struct Bounds { 132 | lower_x: usize, 133 | upper_x: usize, 134 | lower_y: usize, 135 | upper_y: usize, 136 | } 137 | 138 | /* 139 | Step 2, part 1 140 | We define the grid in a way that is robust to mild cropping, under the assumption that such 141 | cropping usually removes relatively featureless parts of the image, for example, the margins of a 142 | document image or the dark bottom of the Mona Lisa picture. 143 | 144 | For each column of the image, we compute the sum of absolute values of differences 145 | between adjacent pixels in that column. We compute the total of all columns, and crop the image 146 | based on the `crop` parameter, which determines how much of the image to discard. For a `crop` of 147 | 0.05, we crop the image at the 5% and 95% columns, that is, the columns such that 5% of the total 148 | sum of differences lies on either side of the cropped image. We crop the rows of the image the 149 | same way (using the sums of original uncropped rows). 150 | */ 151 | fn crop_boundaries(pixels: &Vec>, crop: f32) -> Bounds { 152 | let row_diff_sums: Vec = (0..pixels.len()).map(|y| 153 | (1..pixels[y].len()).map(|x| 154 | pixels[y][x].abs_diff(pixels[y][x - 1]) as i32).sum() 155 | ).collect(); 156 | 157 | let (top, bottom) = get_bounds(row_diff_sums, crop); 158 | 159 | let col_diff_sums: Vec = (0..pixels[0].len()).map(|x| 160 | (1..pixels.len()).map(|y| 161 | pixels[y][x].abs_diff(pixels[y - 1][x]) as i32).sum() 162 | ).collect(); 163 | 164 | let (left, right) = get_bounds(col_diff_sums, crop); 165 | 166 | Bounds { 167 | lower_x: left, 168 | upper_x: right, 169 | lower_y: top, 170 | upper_y: bottom, 171 | } 172 | } 173 | 174 | /// Returns the max number of contiguous values on each end of `diff_sums` that are, when summed, 175 | /// below `crop` times the total of `diff_sums` 176 | fn get_bounds(diff_sums: Vec, crop: f32) -> (usize, usize) { 177 | let total_diff_sum: i32 = diff_sums.iter().sum(); 178 | let threshold = (total_diff_sum as f32 * crop) as i32; 179 | let mut lower = 0; 180 | let mut upper = diff_sums.len() - 1; 181 | let mut sum = diff_sums[lower]; 182 | 183 | while sum < threshold { 184 | lower += 1; 185 | sum += diff_sums[lower]; 186 | } 187 | sum = diff_sums[upper]; 188 | while sum < threshold { 189 | upper -= 1; 190 | sum += diff_sums[upper]; 191 | } 192 | (lower, upper) 193 | } 194 | 195 | /* 196 | Step 2, part 2 197 | "We next impose a 9x9 grid of points on the image. (For large databases, a bigger grid such as 11x11 198 | would give greater first-stage filtering.) 199 | ... 200 | Conceptually, we then divide the cropped image into a 10x10 grid of blocks. We round each interior 201 | grid point to the closest pixel (that is, integer coordinates), thereby setting a 9x9 grid of 202 | points on the image." 203 | 204 | - grid_size: size of superimposed grid (10 in the above example) 205 | */ 206 | fn grid_points(bounds: &Bounds, grid_size: usize) -> HashMap<(i8, i8), (usize, usize)> { 207 | let x_width = (bounds.upper_x - bounds.lower_x + 1) as f32 / grid_size as f32; 208 | let y_width = (bounds.upper_y - bounds.lower_y + 1) as f32 / grid_size as f32; 209 | 210 | let mut points = HashMap::new(); 211 | for x in 1..grid_size { 212 | for y in 1..grid_size { 213 | points.insert( 214 | (x as i8, y as i8), 215 | ( 216 | bounds.lower_x + (x as f32 * x_width).trunc() as usize, 217 | bounds.lower_y + (y as f32 * y_width).trunc() as usize, 218 | ), 219 | ); 220 | } 221 | } 222 | 223 | points 224 | } 225 | 226 | /* 227 | Step 3 228 | "At each grid point, we compute the average gray level of the PxP square centered at the grid point. 229 | We ran our experiments with P = max(2, floor(0.5 + min(n, m) / 20)) where n and m are the dimensions 230 | of the image in pixels. The squares are slightly soft-edged, meaning that instead of using the 231 | pixel’s gray levels themselves, we use an average of a 3x3 block centered at that pixel." 232 | */ 233 | fn grid_averages( 234 | pixels: Vec>, 235 | points: HashMap<(i8, i8), (usize, usize)>, 236 | bounds: Bounds, 237 | average_square_width_fn: fn(width: usize, height: usize) -> usize, 238 | ) -> HashMap<(i8, i8), u8> { 239 | let width = bounds.upper_x - bounds.lower_x; 240 | let height = bounds.upper_y - bounds.lower_y; 241 | let square_edge = average_square_width_fn(width, height) as i32; 242 | 243 | let mut result = HashMap::new(); 244 | for (grid_coord, (point_x, point_y)) in points { 245 | let mut sum: f32 = 0.0; 246 | for delta_x in -square_edge..=square_edge { 247 | for delta_y in -square_edge..=square_edge { 248 | let average = pixel_average( 249 | &pixels, 250 | (point_x as i32 + delta_x) as usize, 251 | (point_y as i32 + delta_y) as usize, 252 | ); 253 | sum += average; 254 | } 255 | } 256 | 257 | let i = sum / ((square_edge * 2 + 1) * (square_edge * 2 + 1)) as f32; 258 | result.insert(grid_coord, i as u8); 259 | } 260 | 261 | result 262 | } 263 | 264 | /* 265 | Step 4 266 | For each grid point, we compute an 8-element array whose elements give a comparison of the average 267 | gray level of the grid point square with those of its eight neighbors. The result of a comparison 268 | can be “much darker”, “darker”, “same”, “lighter”, or “much lighter”, represented numerically as 269 | -2, -1, 0, 1 and 2, respectively. The “same” values are those averages that differ by no more than 270 | 2 on a scale of 0 to 255. We set the boundary between “much darker” and “darker” so that these two 271 | values are equally popular; we do the same for “lighter” and “much lighter”. The rationale in this 272 | step is that “same” may be very common in images with flat backgrounds (such as text documents), and 273 | hence it should not be included in the histogram equalization applied to the other values. Grid 274 | points in the first or last rows or column have fewer than 8 neighbors..." 275 | 276 | (The authors pad missing neighbors with 0's, we just omit them.) 277 | 278 | Step 5 279 | "The signature of an image is simply the concatenation of the 8-element arrays corresponding to the 280 | grid points, ordered left-to-right, top-to-bottom..." 281 | */ 282 | const GRID_DELTAS: [(i8, i8); 9] = [ 283 | (-1, -1), (0, -1), (1, -1), 284 | (-1, 0), (0, 0), (1, 0), 285 | (-1, 1), (0, 1), (1, 1) 286 | ]; 287 | 288 | fn compute_signature(point_averages: HashMap<(i8, i8), u8>, grid_size: usize) -> Vec { 289 | let mut raw_diffs = Vec::with_capacity(grid_size * grid_size); 290 | for grid_y in 1..(grid_size as i8) { 291 | for grid_x in 1..(grid_size as i8) { 292 | let gray = *point_averages.get(&(grid_x, grid_y)).unwrap(); 293 | let raw_point_diffs: Vec = GRID_DELTAS.iter() 294 | .filter_map(|(delta_x, delta_y)| { 295 | point_averages.get(&(grid_x + delta_x, grid_y + delta_y)) 296 | .map(|other| compute_diff(gray, *other)) 297 | }).collect(); 298 | raw_diffs.push(raw_point_diffs) 299 | } 300 | } 301 | 302 | let (dark_threshold, light_threshold) = get_thresholds(&raw_diffs); 303 | raw_diffs.into_iter().flat_map(|neighbors| 304 | neighbors.into_iter() 305 | .map(|v| { 306 | match v { 307 | v if v > 0 => collapse(v, light_threshold), 308 | v if v < 0 => collapse(v, dark_threshold), 309 | _ => 0 310 | } 311 | })).collect() 312 | } 313 | 314 | 315 | fn get_thresholds(raw_diffs: &[Vec]) -> (i16, i16) { 316 | let (dark, light): (Vec, Vec) = raw_diffs.iter().flatten() 317 | .filter(|d| **d != 0) 318 | .partition(|d| **d < 0); 319 | 320 | let dark_threshold = get_median(dark); 321 | let light_threshold = get_median(light); 322 | 323 | (dark_threshold, light_threshold) 324 | } 325 | 326 | fn collapse(val: i16, threshold: i16) -> i8 { 327 | if val.abs() >= threshold.abs() { 328 | 2 * val.signum() as i8 329 | } else { 330 | val.signum() as i8 331 | } 332 | } 333 | 334 | fn get_median(mut vec: Vec) -> i16 { 335 | vec.sort(); 336 | if vec.len() % 2 == 0 { 337 | if vec.is_empty() { 338 | 0 339 | } else { 340 | (vec[(vec.len() / 2) - 1] + vec[vec.len() / 2]) / 2 341 | } 342 | } else { 343 | vec[vec.len() / 2] 344 | } 345 | } 346 | 347 | fn compute_diff(me: u8, other: u8) -> i16 { 348 | let raw_result = me as i16 - other as i16; 349 | if raw_result.abs() <= 2 { 350 | 0 351 | } else { 352 | raw_result 353 | } 354 | } 355 | 356 | const PIXEL_DELTAS: [(i32, i32); 9] = [ 357 | (-1, -1), (0, -1), (1, -1), 358 | (-1, 0), (0, 0), (1, 0), 359 | (-1, 1), (0, 1), (1, 1) 360 | ]; 361 | 362 | fn pixel_average(pixels: &[Vec], x: usize, y: usize) -> f32 { 363 | let max_y = pixels.len() as i32 - 1; 364 | let max_x = pixels[0].len() as i32 - 1; 365 | 366 | let sum: f32 = PIXEL_DELTAS.iter().map(|(delta_x, delta_y)| { 367 | pixels[(y as i32 + *delta_y).clamp(0, max_y) as usize][(x as i32 + *delta_x).clamp(0, max_x) as usize] as f32 368 | }).sum(); 369 | 370 | sum / 9.0 371 | } 372 | 373 | #[cfg(test)] 374 | mod tests { 375 | use super::*; 376 | use pretty_assertions::{assert_eq}; 377 | use std::collections::BTreeMap; 378 | 379 | macro_rules! assert_map_eq { 380 | ( $actual:expr, $expected:expr ) => { 381 | { 382 | let actual: BTreeMap<_, _> = ($actual).into_iter().collect(); 383 | let expected: BTreeMap<_, _> = ($expected).into_iter().collect(); 384 | assert_eq!(actual, expected) 385 | } 386 | } 387 | } 388 | 389 | fn from_dotgrid(grid: &str) -> Vec> { 390 | grid.split("\n") 391 | .map(|row| row.replace(" ","")) 392 | .filter(|row| row.len() > 0) 393 | .map(|row| row.chars().map(|c| match c { 394 | '.' => 0, 395 | 'o' => 64, 396 | 'O' => 128, 397 | 'x' => 192, 398 | 'X' => 255, 399 | c => panic!("Unexpected dotgrid character '{}'", c) 400 | }).collect()).collect() 401 | } 402 | 403 | #[test] 404 | fn test_pixel_gray() { 405 | assert_eq!(pixel_gray(255,255,255,255), 255); 406 | assert_eq!(pixel_gray(0,0,0,0), 0); 407 | assert_eq!(pixel_gray(255,255,255,0), 0); 408 | assert_eq!(pixel_gray(32, 64, 96, 255), 64); 409 | } 410 | 411 | #[test] 412 | fn test_grayscale_buffer() { 413 | assert_eq!(grayscale_buffer(&[ 414 | 255, 255, 255, 255, 415 | 128, 128, 128, 128, 416 | 0, 0, 0, 0, 417 | 0, 128, 255, 128 418 | ], 2), [ 419 | [255, 64], 420 | [0, 63] 421 | ]); 422 | } 423 | 424 | #[test] 425 | fn test_get_bounds() { 426 | assert_eq!([ 427 | (vec![0,0,50,50,0,0], 0.05), 428 | (vec![0,0,0,50,50,0,0,0], 0.05), 429 | ].map(|(v, c)| get_bounds(v, c)), 430 | [(2, 3), (3, 4)]); 431 | } 432 | 433 | #[test] 434 | fn test_crop_boundaries() { 435 | let pic = from_dotgrid(" 436 | ....... 437 | .oooo.. 438 | .oXxo.. 439 | .oXxo.. 440 | ....... 441 | ....... 442 | "); 443 | 444 | assert_eq!(crop_boundaries(&pic, 0.05), Bounds { 445 | lower_x: 1, 446 | upper_x: 4, 447 | lower_y: 1, 448 | upper_y: 3, 449 | }); 450 | assert_eq!(crop_boundaries(&pic, 0.25), Bounds { 451 | lower_x: 2, 452 | upper_x: 3, 453 | lower_y: 2, 454 | upper_y: 3, 455 | }); 456 | assert_eq!(crop_boundaries(&pic, 0.5), Bounds { 457 | lower_x: 2, 458 | upper_x: 2, 459 | lower_y: 2, 460 | upper_y: 2, 461 | }); 462 | } 463 | 464 | #[test] 465 | fn test_grid_points() { 466 | assert_map_eq!(grid_points(&Bounds { 467 | lower_x: 5, 468 | upper_x: 15, 469 | lower_y: 10, 470 | upper_y: 30, 471 | }, 2), [ 472 | ((1, 1), (10, 20)) 473 | ]); 474 | 475 | assert_map_eq!(grid_points(&Bounds { 476 | lower_x: 5, 477 | upper_x: 15, 478 | lower_y: 10, 479 | upper_y: 30, 480 | }, 3), [ 481 | ((1, 1), (8, 17)), 482 | ((2, 1), (12, 17)), 483 | ((1, 2), (8, 24)), 484 | ((2, 2), (12, 24)), 485 | ]); 486 | } 487 | 488 | #[test] 489 | fn test_grid_points_extreme() { 490 | assert_map_eq!(grid_points(&Bounds { 491 | lower_x: 0, 492 | upper_x: 100, 493 | lower_y: 1, 494 | upper_y: 1, 495 | }, 6), [ 496 | ((1, 1), (16, 1)), 497 | ((2, 1), (33, 1)), 498 | ((3, 1), (50, 1)), 499 | ((4, 1), (67, 1)), 500 | ((5, 1), (84, 1)), 501 | 502 | ((1, 2), (16, 1)), 503 | ((2, 2), (33, 1)), 504 | ((3, 2), (50, 1)), 505 | ((4, 2), (67, 1)), 506 | ((5, 2), (84, 1)), 507 | 508 | ((1, 3), (16, 1)), 509 | ((2, 3), (33, 1)), 510 | ((3, 3), (50, 1)), 511 | ((4, 3), (67, 1)), 512 | ((5, 3), (84, 1)), 513 | 514 | ((1, 4), (16, 1)), 515 | ((2, 4), (33, 1)), 516 | ((3, 4), (50, 1)), 517 | ((4, 4), (67, 1)), 518 | ((5, 4), (84, 1)), 519 | 520 | ((1, 5), (16, 1)), 521 | ((2, 5), (33, 1)), 522 | ((3, 5), (50, 1)), 523 | ((4, 5), (67, 1)), 524 | ((5, 5), (84, 1)), 525 | ]); 526 | } 527 | 528 | #[test] 529 | fn test_grid_points_tiny() { 530 | assert_map_eq!(grid_points(&Bounds { 531 | lower_x: 0, 532 | upper_x: 1, 533 | lower_y: 0, 534 | upper_y: 1, 535 | }, 3), [ 536 | ((1,1), (0,0)), 537 | ((2,1), (1,0)), 538 | ((1,2), (0,1)), 539 | ((2,2), (1,1)), 540 | ]); 541 | } 542 | } 543 | -------------------------------------------------------------------------------- /tests/stats.rs: -------------------------------------------------------------------------------- 1 | #![cfg(feature = "img")] 2 | 3 | use std::collections::HashMap; 4 | use std::ffi::OsString; 5 | use std::fs; 6 | use std::path::Path; 7 | 8 | use image_match::cosine_similarity; 9 | use image_match::image::get_file_signature; 10 | 11 | #[test] 12 | fn check_match_percentages() { 13 | let orig = calc_sigs_for_pic_dir_files("original"); 14 | let cropped = calc_sigs_for_pic_dir_files("cropped"); 15 | let grown = calc_sigs_for_pic_dir_files("grown"); 16 | let shrunk = calc_sigs_for_pic_dir_files("shrunk"); 17 | 18 | evaluate_altered("Cropped", &orig, &cropped); 19 | evaluate_altered("Grown", &orig, &grown); 20 | evaluate_altered("Shrunk", &orig, &shrunk); 21 | evaluate_non_matching(&orig); 22 | } 23 | 24 | fn calc_sigs_for_pic_dir_files(dir: &str) -> HashMap> { 25 | println!("Calculating signatures for {}", dir); 26 | let pics_root = Path::new("./tests/pics").join(Path::new(dir)); 27 | let names: Vec = fs::read_dir(pics_root.clone()).unwrap() 28 | .map(|f| f.unwrap().file_name()) 29 | .collect(); 30 | let mut files = HashMap::with_capacity(names.len()); 31 | for name in names { 32 | let path = pics_root.join(Path::new(&name)); 33 | let signature = get_file_signature(path).unwrap(); 34 | files.insert(name.into_string().unwrap(), signature); 35 | } 36 | 37 | files 38 | } 39 | 40 | fn evaluate_altered(name: &str, orig: &HashMap>, altered: &HashMap>) { 41 | let mut cosines = Vec::with_capacity(orig.len()); 42 | for (file, signature) in orig { 43 | let altered_sig = altered.get(file).unwrap(); 44 | cosines.push(cosine_similarity(signature, altered_sig)); 45 | } 46 | 47 | print_stats(name, cosines); 48 | } 49 | 50 | fn evaluate_non_matching(orig: &HashMap>) { 51 | let mut non_matching = Vec::with_capacity(orig.len() * orig.len()); 52 | for (name, signature) in orig { 53 | orig.iter().filter(|(n, _)| n != &name) 54 | .map(|(_, other_sig)| cosine_similarity(signature, other_sig)) 55 | .for_each(|similarity| non_matching.push(similarity)); 56 | } 57 | 58 | print_stats("Non-Matching", non_matching); 59 | } 60 | 61 | fn print_stats(name: &str, mut cosines: Vec) { 62 | cosines.sort_by(|a, b| a.partial_cmp(b).unwrap()); 63 | 64 | let avg = cosines.iter().sum::() / cosines.len() as f64; 65 | 66 | println!("{}:", name); 67 | println!("Min\tMean\tMax\t30th\t50th\t75th\t90th\t95th\t99th"); 68 | println!("{:.3}\t{:.3}\t{:.3}\t{:.3}\t{:.3}\t{:.3}\t{:.3}\t{:.3}\t{:.3}\n", 69 | cosines.first().unwrap(), 70 | avg, 71 | cosines.last().unwrap(), 72 | prcnt(&cosines, 0.30), 73 | prcnt(&cosines, 0.50), 74 | prcnt(&cosines, 0.75), 75 | prcnt(&cosines, 0.90), 76 | prcnt(&cosines, 0.95), 77 | prcnt(&cosines, 0.99), 78 | ); 79 | } 80 | 81 | fn prcnt(cosines: &Vec, percentile: f64) -> f64 { 82 | let idx = (percentile * cosines.len() as f64).floor() as usize; 83 | *cosines.get(idx).unwrap() 84 | } 85 | --------------------------------------------------------------------------------