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Role: Documentation
Content type: text/markdown
Description: Documentation
Class: HAAR PHP Image Feature Detection Library
Detect features (e.g faces) in images
Author: By
Last change: v.1.0.6
Date: 8 months ago
Size: 10,297 bytes


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__Feature Detection Library for PHP__

Based on Viola-Jones Feature Detection Algorithm using Haar Cascades and improvement Viola-Jones-Lienhart et al Feature Detection Algorithm

This is a port of OpenCV C++ Haar Detection and of JViolaJones Java) to PHP.

there is also a javascript version: HAAR.js



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)


to use opencv's haarcascades_frontalface_alt.xml in php do:

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


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.



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



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.


$detector->image($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)


$detector->selection('auto'|array|feature|$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


$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__ ).


$detector->detect($baseScale = 1, $scale_inc = 1.25, $increment = 0.1, $min_neighbors = 1 , $epsilon = 0.2, $doCannyPruning = false);

__Explanation of parameters__ (JViolaJones 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


  • [ ] keep up with the changes in openCV cascades xml format (will try)


__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:

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  • MOD3 3D Modifier Library in JavaScript
  • Geometrize Computational Geometry and Rendering Library for JavaScript
  • 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 image feature detection based on Haar Cascades in JavaScript (Viola-Jones-Lienhart et al Algorithm)
  • HAARPHP image feature detection based on Haar Cascades in PHP (Viola-Jones-Lienhart et al Algorithm)
  • FILTER.js video and image processing and computer vision Library in pure JavaScript (browser and node)
  • Xpresion a simple and flexible eXpression parser engine (with custom functions and variables support), based on GrammarTemplate, for PHP, JavaScript, Python
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  • highlightjs-grammar transform a formal grammar in JSON format into a syntax-highlight mode for Highlight.js code highlighter
  • syntaxhighlighter-grammar transform a formal grammar in JSON format to a highlight brush for SyntaxHighlighter code highlighter
  • SortingAlgorithms implementations of Sorting Algorithms in JavaScript
  • PatternMatchingAlgorithms implementations of Pattern Matching Algorithms in JavaScript
  • CanvasLite an html canvas implementation in pure JavaScript
  • Rasterizer stroke and fill lines, rectangles, curves and paths, without canva?
  • Gradient create linear, radial, conic and elliptic gradients and image patterns without canvas
  • css-color simple class to parse and manipulate colors in various formats