openpose-models，覆盖openpose/models下面的文件

<?xml version="1.0"?> <!-- Stump-based 20x20 gentle adaboost frontal face detector. Created by Rainer Lienhart. //////////////////////////////////////////////////////////////////////////////////////// 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. Intel License Agreement For Open Source Computer Vision Library Copyright (C) 2000, Intel Corporation, all rights reserved. Third party copyrights are property of their respective owners. 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In no event shall the Intel Corporation or 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. --> <opencv_storage> <cascade type_id="opencv-cascade-classifier"><stageType>BOOST</stageType> <featureType>HAAR</featureType> <height>20</height> <width>20</width> <stageParams> <maxWeakCount>213</maxWeakCount></stageParams> <featureParams> <maxCatCount>0</maxCatCount></featureParams> <stageNum>22</stageNum> <stages> <_> <maxWeakCount>3</maxWeakCount> <stageThreshold>8.2268941402435303e-01</stageThreshold> <weakClassifiers> <_> <internalNodes> 0 -1 0 4.0141958743333817e-03</internalNodes> <leafValues> 3.3794190734624863e-02 8.3781069517135620e-01</leafValues></_> <_> <internalNodes> 0 -1 1 1.5151339583098888e-02</internalNodes> <leafValues> 1.5141320228576660e-01 7.4888122081756592e-01</leafValues></_> <_> <internalNodes> 0 -1 2 4.2109931819140911e-03</internalNodes> <leafValues> 9.0049281716346741e-02 6.3748198747634888e-01</leafValues></_></weakClassifiers></_> <_> <maxWeakCount>16</maxWeakCount> <stageThreshold>6.9566087722778320e+00</stageThreshold> <weakClassifiers> <_> <internalNodes> 0 -1 3 1.6227109590545297e-03</internalNodes> <leafValues> 6.9308586418628693e-02 7.1109461784362793e-01</leafValues></_> <_> <internalNodes> 0 -1 4 2.2906649392098188e-03</internalNodes> <leafValues> 1.7958030104637146e-01 6.6686922311782837e-01</leafValues></_> <_> <internalNodes> 0 -1 5 5.0025708042085171e-03</internalNodes> <leafValues> 1.6936729848384857e-01 6.5540069341659546e-01</leafValues></_> <_> <internalNodes> 0 -1 6 7.9659894108772278e-03</internalNodes> <leafValues> 5.8663320541381836e-01 9.1414518654346466e-02</leafValues></_> <_> <internalNodes> 0 -1 7 -3.5227010957896709e-03</internalNodes> <leafValues> 1.4131669700145721e-01 6.0318958759307861e-01</leafValues></_> <_> <internalNodes> 0 -1 8 3.6667689681053162e-02</internalNodes> <leafValues> 3.6756721138954163e-01 7.9203182458877563e-01</leafValues></_> <_> <internalNodes> 0 -1 9 9.3361474573612213e-03</internalNodes> <leafValues> 6.1613857746124268e-01 2.0885099470615387e-01</leafValues></_> <_> <internalNodes> 0 -1 10 8.6961314082145691e-03</internalNodes> <leafValues> 2.8362309932708740e-01 6.3602739572525024e-01</leafValues></_> <_> <internalNodes> 0 -1 11 1.1488880263641477e-03</internalNodes> <leafValues> 2.2235809266567230e-01 5.8007007837295532e-01</leafValues></_> <_> <internalNodes> 0 -1 12 -2.1484689787030220e-03</internalNodes> <leafValues> 2.4064640700817108e-01 5.7870548963546753e-01</leafValues></_> <_> <internalNodes> 0 -1 13 2.1219060290604830e-03</internalNodes> <leafValues> 5.5596548318862915e-01 1.3622370362281799e-01</leafValues></_> <_> <internalNodes> 0 -1 14 -9.3949146568775177e-02</internalNodes> <leafValues> 8.5027372837066650e-01 4.7177401185035706e-01</leafValues></_> <_> <internalNodes> 0 -1 15 1.3777789426967502e-03</internalNodes> <leafValues> 5.9936738014221191e-01 2.8345298767089844e-01</leafValues></_> <_> <internalNodes> 0 -1 16 7.3063157498836517e-02</internalNodes> <leafValues> 4.3418860435485840e-01 7.0600342750549316e-01</leafValues></_> <_> <internalNodes> 0 -1 17 3.6767389974556863e-04</internalNodes> <leafValues> 3.0278879404067993e-01 6.0515749454498291e-01</leafValues></_> <_> <internalNodes> 0 -1 18 -6.0479710809886456e-03</internalNodes> <leafValues> 1.7984339594841003e-01 5.6752568483352661e-01</leafValues></_></weakClassifiers></_> <_> <maxWeakCount>21</maxWeakCount> <stageThreshold>9.4985427856445312e+00</stageThreshold> <weakClassifiers> <_> <internalNodes> 0 -1 19 -1.6510689631104469e-02</internalNodes> <leafValues> 6.6442251205444336e-01 1.4248579740524292e-01</leafValues></_> <_> <internalNodes> 0 -1 20 2.7052499353885651e-03</internalNodes> <leafValues> 6.3253521919250488e-01 1.2884770333766937e-01</leafValues></_> <_> <internalNodes> 0 -1 21 2.8069869149476290e-03</internalNodes> <leafValues> 1.2402880191802979e-01 6.1931931972503662e-01</leafValues></_> <_> <internalNodes> 0 -1 22 -1.5402400167658925e-03</internalNodes> <leafValues> 1.4321430027484894e-01 5.6700158119201660e-01</leafValues></_> <_> <internalNodes> 0 -1 23 -5.6386279175058007e-04</internalNodes> <leafValues> 1.6574330627918243e-01 5.9052079916000366e-01</leafValues></_> <_> <internalNodes> 0 -1 24 1.9253729842603207e-03</internalNodes> <leafValues> 2.6955071091651917e-01 5.7388240098953247e-01</leafValues></_> <_> <internalNodes> 0 -1 25 -5.0214841030538082e-03</internalNodes> <leafValues> 1.8935389816761017e-01 5.7827740907669067e-01</leafValues></_> <_> <interna