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haarcascade_frontalcatface_extended.xml 374KB

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  1. <?xml version="1.0"?>
  2. <!--
  3. A frontal cat face detector using the full set of Haar features, i.e.
  4. horizontal, vertical, and diagonal features.
  5. Contributed by Joseph Howse (josephhowse@nummist.com).
  6. More information can be found in the following publications and
  7. presentations:
  8. Joseph Howse. OpenCV for Secret Agents (book). Packt Publishing, January
  9. 2015.
  10. Joseph Howse. "Training Detectors and Recognizers in Python and OpenCV"
  11. (tutorial). ISMAR 2014. September 9, 2014.
  12. http://nummist.com/opencv/Howse_ISMAR_20140909.pdf
  13. Joseph Howse. "Training Intelligent Camera Systems with Python and OpenCV"
  14. (webcast). O’Reilly Media. June 17, 2014.
  15. http://www.oreilly.com/pub/e/3077
  16. Build scripts and demo applications can be found in the following repository:
  17. https://bitbucket.org/Joe_Howse/angora-blue
  18. KNOWN LIMITATIONS:
  19. An upright subject is assumed. In situations where the cat's face might be
  20. sideways or upside down (e.g. the cat is rolling over), try various rotations
  21. of the input image.
  22. CHANGELOG:
  23. 2016-08-06: Re-trained with more negative samples and more stages. False
  24. positives are much rarer now. If you tailored your code for the cascade's
  25. previous version, now you should re-adjust the arguments of
  26. CascadeClassifier::detectMultiScale. For example, decrease the value of the
  27. minNeighbors argument. You do not need to use a human face detector to
  28. cross-check the positives anymore.
  29. 2014-04-25: First release (at https://bitbucket.org/Joe_Howse/angora-blue)
  30. //////////////////////////////////////////////////////////////////////////
  31. | Contributors License Agreement
  32. | IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
  33. | By downloading, copying, installing or using the software you agree
  34. | to this license.
  35. | If you do not agree to this license, do not download, install,
  36. | copy or use the software.
  37. |
  38. | Copyright (c) 2014-2016, Joseph Howse (Nummist Media Corporation Limited,
  39. | Halifax, Nova Scotia, Canada). All rights reserved.
  40. |
  41. | Redistribution and use in source and binary forms, with or without
  42. | modification, are permitted provided that the following conditions are
  43. | met:
  44. |
  45. | * Redistributions of source code must retain the above copyright
  46. | notice, this list of conditions and the following disclaimer.
  47. | * Redistributions in binary form must reproduce the above
  48. | copyright notice, this list of conditions and the following
  49. | disclaimer in the documentation and/or other materials provided
  50. | with the distribution.
  51. | * The name of Contributor may not used to endorse or promote products
  52. | derived from this software without specific prior written permission.
  53. |
  54. | THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
  55. | "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
  56. | LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
  57. | A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
  58. | CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
  59. | EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
  60. | PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
  61. | PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
  62. | LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
  63. | NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
  64. | SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Back to
  65. | Top
  66. //////////////////////////////////////////////////////////////////////////
  67. -->
  68. <opencv_storage>
  69. <cascade>
  70. <stageType>BOOST</stageType>
  71. <featureType>HAAR</featureType>
  72. <height>24</height>
  73. <width>24</width>
  74. <stageParams>
  75. <boostType>GAB</boostType>
  76. <minHitRate>9.9500000476837158e-01</minHitRate>
  77. <maxFalseAlarm>5.0000000000000000e-01</maxFalseAlarm>
  78. <weightTrimRate>9.4999999999999996e-01</weightTrimRate>
  79. <maxDepth>1</maxDepth>
  80. <maxWeakCount>100</maxWeakCount></stageParams>
  81. <featureParams>
  82. <maxCatCount>0</maxCatCount>
  83. <featSize>1</featSize>
  84. <mode>ALL</mode></featureParams>
  85. <stageNum>20</stageNum>
  86. <stages>
  87. <!-- stage 0 -->
  88. <_>
  89. <maxWeakCount>13</maxWeakCount>
  90. <stageThreshold>-1.4294912815093994e+00</stageThreshold>
  91. <weakClassifiers>
  92. <_>
  93. <internalNodes>
  94. 0 -1 394 -1.5126220881938934e-02</internalNodes>
  95. <leafValues>
  96. 7.5887596607208252e-01 -3.4230688214302063e-01</leafValues></_>
  97. <_>
  98. <internalNodes>
  99. 0 -1 737 3.9337221533060074e-03</internalNodes>
  100. <leafValues>
  101. -3.3288389444351196e-01 5.2361363172531128e-01</leafValues></_>
  102. <_>
  103. <internalNodes>
  104. 0 -1 757 -1.5044892206788063e-02</internalNodes>
  105. <leafValues>
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