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https://github.com/foo123/haarphp
Feature Detection based on Haar Cascades in PHP (Viola-Jones-Lienhart et al Algorithm)
https://github.com/foo123/haarphp
computer-vision object-detection viola-jones
Last synced: about 1 month ago
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Feature Detection based on Haar Cascades in PHP (Viola-Jones-Lienhart et al Algorithm)
- Host: GitHub
- URL: https://github.com/foo123/haarphp
- Owner: foo123
- Created: 2012-02-28T17:30:17.000Z (over 12 years ago)
- Default Branch: master
- Last Pushed: 2023-08-24T07:26:46.000Z (about 1 year ago)
- Last Synced: 2023-08-24T08:39:30.078Z (about 1 year ago)
- Topics: computer-vision, object-detection, viola-jones
- Language: PHP
- Homepage: https://foo123.github.io/
- Size: 1.15 MB
- Stars: 14
- Watchers: 4
- Forks: 8
- Open Issues: 0
-
Metadata Files:
- Readme: readme.md
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README
# HAARPHP
__Feature Detection Library for PHP__
Based on [Viola-Jones Feature Detection Algorithm using Haar Cascades](http://www.cs.cmu.edu/~efros/courses/LBMV07/Papers/viola-cvpr-01.pdf)
and improvement [Viola-Jones-Lienhart et al Feature Detection Algorithm](http://www.multimedia-computing.de/mediawiki//images/5/52/MRL-TR-May02-revised-Dec02.pdf)
This is a port of [OpenCV C++ Haar Detection](https://github.com/opencv/opencv) and of [JViolaJones Java](http://code.google.com/p/jviolajones/)) to PHP.
**there is also a [`javascript` version: HAAR.js](https://github.com/foo123/HAAR.js)**
### Contents
* [How to Use](#how-to-use)
* [Detector Methods](#detector-methods)
* [Haar Cascades](#where-to-find-haar-cascades-xml-files-to-use-for-feature-detection)
* [Todo](#todo)
* [Changelog](#changelog)
### How to Use
You can use the __existing openCV cascades__ to build your detectors.
To do this just transform the __opencv xml file__ to *PHP* format
using the __haartophp__ (php) tool (in cascades folder)
__examples:__
to use opencv's *haarcascades_frontalface_alt.xml* in *php* do:
```bash
haartophp haarcascades_frontalface_alt.xml > haarcascades_frontalface_alt.php
```
this creates a `php` file: `haarcascades_frontalface_alt.php`
which you can include in your `php` application (see examples)
the variable to use in php is similarly: `$haarcascades_frontalface_alt`
#### Detector Methods
__constructor()__
```php
new HaarDetector($haardata);
```
__Explanation of parameters__
* `$haardata` : The actual haardata (as generated by `haartophp` tool), this is specific per feature, openCV haar data can be used.
__clearCache()__
```php
$detector->clearCache();
```
Clear any cached image data and haardata in case space is an issue. Use image method and cascade method (see below) to re-set image and haar data
__cascade()__
```php
$detector->cascade($haardata);
```
Allow to use same detector (with its cached image data), to detect different feature on same image, by using another cascade. This way any image pre-processing is done only once
__Explanation of parameters__
* `$haardata` : The actual haardata (as generated by `haartophp` tool), this is specific per feature, openCV haar data can be used.
__image()__
```php
$detector->image($GDImage, $scale = 1.0);
```
__Explanation of parameters__
* `$GDImage` : an actual `GD` Image object.
* `$scale` : The percent of scaling from the original image, so detection proceeds faster on a smaller image (default __1.0__ ). __NOTE__ scaling might alter the detection results sometimes, if having problems opt towards 1 (slower)
__selection()__
```php
$detector->selection('auto'|array|feature|$x [,$y, $width, $height]);
```
Get/Set a custom region in the image to confine the detection process only in that region (eg detect nose while face already detected)
__Explanation of parameters__
* `1st parameter` : This can be the string `'auto'` which sets the whole image as the selection, or an array ie: `array('x'=>10, 'y'=>'auto', 'width'=>100, 'height'=>'auto')` (every param set as `'auto'` will take the default image value) or a detection rectangle/feature, or a x coordinate (along with rest coordinates).
* `$y` : (Optional) the selection start y coordinate, can be an actual value or `'auto'` (`$y=0`)
* `$width` : (Optional) the selection width, can be an actual value or `'auto'` (`$width=image.width`)
* `$height` : (Optional) the selection height, can be an actual value or `'auto'` (`$height=image.height`)
The actual selection rectangle/feature is available as `$this->selection()` or `$detector->selection()` with no parameters
__cannyThreshold()__
```php
$detector->cannyThreshold(array('low'=> lowThreshold, 'high'=> highThreshold));
```
Set the thresholds when Canny Pruning is used, for extra fine-tuning.
Canny Pruning detects the number/density of edges in a given region. A region with too few or too many edges is unlikely to be a feature.
Default values work fine in most cases, however depending on image size and the specific feature, some fine tuning could be needed
__Explanation of parameters__
* `low` : (Optional) The low threshold (default __20__ ).
* `high` : (Optional) The high threshold (default __100__ ).
__detect()__
```php
$detector->detect($baseScale = 1, $scale_inc = 1.25, $increment = 0.1, $min_neighbors = 1 , $epsilon = 0.2, $doCannyPruning = false);
```
__Explanation of parameters__ ([JViolaJones Parameters](http://code.google.com/p/jviolajones/wiki/Parameters))
* `$baseScale` : The initial ratio between the window size and the Haar classifier size (default __1__ ).
* `$scale_inc` : The scale increment of the window size, at each step (default __1.25__ ).
* `$increment` : The shift of the window at each sub-step, in terms of percentage of the window size (default __0.1__ ).
* `$min_neighbors` : The minimum numbers of similar rectangles needed for the region to be considered as a feature (avoid noise) (default __1__ )
* `$epsilon` : Epsilon value that determines similarity between detected rectangles. `0` means identical (default __0.2__ )
* `$doCannyPruning` : enable Canny Pruning to pre-detect regions unlikely to contain features, in order to speed up the execution (optional default __false__ ).
__Examples included with face detection__
### Where to find Haar Cascades XML files to use for feature detection
* [OpenCV](http://opencv.org/)
* [This resource](http://alereimondo.no-ip.org/OpenCV/34)
* search the web :)
* [Train your own](http://docs.opencv.org/doc/user_guide/ug_traincascade.html) with a little extra help [here](http://note.sonots.com/SciSoftware/haartraining.html) and [here](http://coding-robin.de/2013/07/22/train-your-own-opencv-haar-classifier.html)
#### TODO
- [ ] keep up with the changes in openCV cascades xml format (will try)
#### ChangeLog
__1.0.6__
* correction when selection is used again (revert to previous code)
__1.0.5__
* correction when selection is used, use same version as HAAR.js
* implicit type casting warnings in php 8 handled
__1.0.2__
* port code from latest version of opencv
__1.0.1__
* inline detection routine for further speed
* update test examples with many faces detection
__1.0.0__
* correct detection on custom selection
* refactor code
__0.4__
* refactor code (make smaller)
* add clearCache method, to delete any stored/cached image data in the detector (in case space is an issue)
* add the tilted feature (Lienhart et al, extension)
* make new `haartophp` tool, output format changed, __make sure to re-convert your `.php` haar cascades!!__
* tidy up the repo
* fix some typos, edits
__0.3__
* add new methods (_selection_ , _cascade_ , _cannyThreshold_ )
* use fixed-point arithmetic if possible (eg gray-scale, canny computation)
* optimize array indexing, remove unnecessary multiplications
* reduce unnecessary loops, inline code instead of method calling for speed
* rewrite _merge_ method (features might be slightly different now)
* features are now generic classes not arrays
* code refactor/fixes
* update readme, add method documentation
__0.2__
* add haartophp tool in php (all-php solution)
* optimize array operations, refactor, etc..
__0.1__
* initial release
**see also:**
* [Abacus](https://github.com/foo123/Abacus) advanced Combinatorics and Algebraic Number Theory Symbolic Computation library for JavaScript, Python
* [MOD3](https://github.com/foo123/MOD3) 3D Modifier Library in JavaScript
* [Geometrize](https://github.com/foo123/Geometrize) Computational Geometry and Rendering Library for JavaScript
* [Plot.js](https://github.com/foo123/Plot.js) simple and small library which can plot graphs of functions and various simple charts and can render to Canvas, SVG and plain HTML
* [HAAR.js](https://github.com/foo123/HAAR.js) image feature detection based on Haar Cascades in JavaScript (Viola-Jones-Lienhart et al Algorithm)
* [HAARPHP](https://github.com/foo123/HAARPHP) image feature detection based on Haar Cascades in PHP (Viola-Jones-Lienhart et al Algorithm)
* [FILTER.js](https://github.com/foo123/FILTER.js) video and image processing and computer vision Library in pure JavaScript (browser and node)
* [Xpresion](https://github.com/foo123/Xpresion) a simple and flexible eXpression parser engine (with custom functions and variables support), based on [GrammarTemplate](https://github.com/foo123/GrammarTemplate), for PHP, JavaScript, Python
* [Regex Analyzer/Composer](https://github.com/foo123/RegexAnalyzer) Regular Expression Analyzer and Composer for PHP, JavaScript, Python
* [GrammarTemplate](https://github.com/foo123/GrammarTemplate) grammar-based templating for PHP, JavaScript, Python
* [codemirror-grammar](https://github.com/foo123/codemirror-grammar) transform a formal grammar in JSON format into a syntax-highlight parser for CodeMirror editor
* [ace-grammar](https://github.com/foo123/ace-grammar) transform a formal grammar in JSON format into a syntax-highlight parser for ACE editor
* [prism-grammar](https://github.com/foo123/prism-grammar) transform a formal grammar in JSON format into a syntax-highlighter for Prism code highlighter
* [highlightjs-grammar](https://github.com/foo123/highlightjs-grammar) transform a formal grammar in JSON format into a syntax-highlight mode for Highlight.js code highlighter
* [syntaxhighlighter-grammar](https://github.com/foo123/syntaxhighlighter-grammar) transform a formal grammar in JSON format to a highlight brush for SyntaxHighlighter code highlighter
* [SortingAlgorithms](https://github.com/foo123/SortingAlgorithms) implementations of Sorting Algorithms in JavaScript
* [PatternMatchingAlgorithms](https://github.com/foo123/PatternMatchingAlgorithms) implementations of Pattern Matching Algorithms in JavaScript
* [CanvasLite](https://github.com/foo123/CanvasLite) an html canvas implementation in pure JavaScript
* [Rasterizer](https://github.com/foo123/Rasterizer) stroke and fill lines, rectangles, curves and paths, without canvaσ
* [Gradient](https://github.com/foo123/Gradient) create linear, radial, conic and elliptic gradients and image patterns without canvas
* [css-color](https://github.com/foo123/css-color) simple class to parse and manipulate colors in various formats