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|
- <?xml version="1.0"?>
- <!--
- A frontal cat face detector using the full set of Haar features, i.e.
- horizontal, vertical, and diagonal features.
-
- Contributed by Joseph Howse (josephhowse@nummist.com).
-
- More information can be found in the following publications and
- presentations:
-
- Joseph Howse. OpenCV for Secret Agents (book). Packt Publishing, January
- 2015.
- Joseph Howse. "Training Detectors and Recognizers in Python and OpenCV"
- (tutorial). ISMAR 2014. September 9, 2014.
- http://nummist.com/opencv/Howse_ISMAR_20140909.pdf
- Joseph Howse. "Training Intelligent Camera Systems with Python and OpenCV"
- (webcast). O’Reilly Media. June 17, 2014.
- http://www.oreilly.com/pub/e/3077
-
- Build scripts and demo applications can be found in the following repository:
- https://bitbucket.org/Joe_Howse/angora-blue
-
- KNOWN LIMITATIONS:
-
- An upright subject is assumed. In situations where the cat's face might be
- sideways or upside down (e.g. the cat is rolling over), try various rotations
- of the input image.
-
- CHANGELOG:
-
- 2016-08-06: Re-trained with more negative samples and more stages. False
- positives are much rarer now. If you tailored your code for the cascade's
- previous version, now you should re-adjust the arguments of
- CascadeClassifier::detectMultiScale. For example, decrease the value of the
- minNeighbors argument. You do not need to use a human face detector to
- cross-check the positives anymore.
- 2014-04-25: First release (at https://bitbucket.org/Joe_Howse/angora-blue)
-
- //////////////////////////////////////////////////////////////////////////
- | Contributors License Agreement
- | IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
- | By downloading, copying, installing or using the software you agree
- | to this license.
- | If you do not agree to this license, do not download, install,
- | copy or use the software.
- |
- | Copyright (c) 2014-2016, Joseph Howse (Nummist Media Corporation Limited,
- | Halifax, Nova Scotia, Canada). All rights reserved.
- |
- | Redistribution and use in source and binary forms, with or without
- | modification, are permitted provided that the following conditions are
- | met:
- |
- | * Redistributions of source code must retain the above copyright
- | notice, this list of conditions and the following disclaimer.
- | * Redistributions in binary form must reproduce the above
- | copyright notice, this list of conditions and the following
- | disclaimer in the documentation and/or other materials provided
- | with the distribution.
- | * The name of Contributor may not used to endorse or promote products
- | derived from this software without specific prior written permission.
- |
- | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
- | "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
- | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
- | A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
- | CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
- | EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
- | PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
- | PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
- | LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
- | NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- | SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Back to
- | Top
- //////////////////////////////////////////////////////////////////////////
- -->
- <opencv_storage>
- <cascade>
- <stageType>BOOST</stageType>
- <featureType>HAAR</featureType>
- <height>24</height>
- <width>24</width>
- <stageParams>
- <boostType>GAB</boostType>
- <minHitRate>9.9500000476837158e-01</minHitRate>
- <maxFalseAlarm>5.0000000000000000e-01</maxFalseAlarm>
- <weightTrimRate>9.4999999999999996e-01</weightTrimRate>
- <maxDepth>1</maxDepth>
- <maxWeakCount>100</maxWeakCount></stageParams>
- <featureParams>
- <maxCatCount>0</maxCatCount>
- <featSize>1</featSize>
- <mode>ALL</mode></featureParams>
- <stageNum>20</stageNum>
- <stages>
- <!-- stage 0 -->
- <_>
- <maxWeakCount>13</maxWeakCount>
- <stageThreshold>-1.4294912815093994e+00</stageThreshold>
- <weakClassifiers>
- <_>
- <internalNodes>
- 0 -1 394 -1.5126220881938934e-02</internalNodes>
- <leafValues>
- 7.5887596607208252e-01 -3.4230688214302063e-01</leafValues></_>
- <_>
- <internalNodes>
- 0 -1 737 3.9337221533060074e-03</internalNodes>
- <leafValues>
- -3.3288389444351196e-01 5.2361363172531128e-01</leafValues></_>
- <_>
- <internalNodes>
- 0 -1 757 -1.5044892206788063e-02</internalNodes>
- <leafValues>
- 5.5565774440765381e-01 -2.2505992650985718e-01</leafValues></_>
- <_>
- <internalNodes>
- 0 -1 450 -1.5777055174112320e-02</internalNodes>
- <leafValues>
- 7.2692525386810303e-01 -1.6206762194633484e-01</leafValues></_>
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- <leafValues>
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- <_>
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