Bug Summary

File:ccv_scd.c
Warning:line 1285, column 22
Potential leak of memory pointed to by 'z.cascade'

Annotated Source Code

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clang -cc1 -cc1 -triple x86_64-unknown-linux-gnu -analyze -disable-free -clear-ast-before-backend -disable-llvm-verifier -discard-value-names -main-file-name ccv_scd.c -analyzer-checker=core -analyzer-checker=apiModeling -analyzer-checker=unix -analyzer-checker=deadcode -analyzer-checker=security.insecureAPI.UncheckedReturn -analyzer-checker=security.insecureAPI.getpw -analyzer-checker=security.insecureAPI.gets -analyzer-checker=security.insecureAPI.mktemp -analyzer-checker=security.insecureAPI.mkstemp -analyzer-checker=security.insecureAPI.vfork -analyzer-checker=nullability.NullPassedToNonnull -analyzer-checker=nullability.NullReturnedFromNonnull -analyzer-output plist -w -setup-static-analyzer -mrelocation-model pic -pic-level 2 -pic-is-pie -mframe-pointer=none -menable-no-infs -menable-no-nans -fapprox-func -funsafe-math-optimizations -fno-signed-zeros -mreassociate -freciprocal-math -fdenormal-fp-math=preserve-sign,preserve-sign -ffp-contract=fast -fno-rounding-math -ffast-math -ffinite-math-only -complex-range=limited -mconstructor-aliases -funwind-tables=2 -target-cpu x86-64 -target-feature +sse2 -tune-cpu generic -debugger-tuning=gdb -fdebug-compilation-dir=/home/liu/actions-runner/_work/ccv/ccv/lib -fcoverage-compilation-dir=/home/liu/actions-runner/_work/ccv/ccv/lib -resource-dir /usr/local/lib/clang/18 -I . -I /usr/local/cuda/include -D HAVE_CBLAS -D HAVE_LIBPNG -D HAVE_LIBJPEG -D HAVE_FFTW3 -D HAVE_PTHREAD -D HAVE_LIBLINEAR -D HAVE_TESSERACT -D HAVE_AVCODEC -D HAVE_AVFORMAT -D HAVE_AVUTIL -D HAVE_SWSCALE -D HAVE_SSE2 -D HAVE_GSL -D HAVE_CUDA -D HAVE_CUDNN -D HAVE_NCCL -D USE_SYSTEM_CUB -D HAVE_CUDA_SM80 -I /usr/local/include -internal-isystem /usr/local/lib/clang/18/include -internal-isystem /usr/local/include -internal-isystem /usr/lib/gcc/x86_64-linux-gnu/12/../../../../x86_64-linux-gnu/include -internal-externc-isystem /usr/include/x86_64-linux-gnu -internal-externc-isystem /include -internal-externc-isystem /usr/include -O3 -ferror-limit 19 -fgnuc-version=4.2.1 -fskip-odr-check-in-gmf -vectorize-loops -vectorize-slp -analyzer-output=html -faddrsig -D__GCC_HAVE_DWARF2_CFI_ASM=1 -o /home/liu/actions-runner/_work/ccv/ccv/_analyze/2024-08-20-112342-102351-1 -x c ccv_scd.c
1#include "ccv.h"
2#include "ccv_internal.h"
3#if defined(HAVE_SSE21)
4#include <xmmintrin.h>
5#elif defined(HAVE_NEON)
6#include <arm_neon.h>
7#endif
8#ifdef HAVE_GSL1
9#include <gsl/gsl_rng.h>
10#include <gsl/gsl_randist.h>
11#endif
12#ifdef USE_OPENMP
13#include <omp.h>
14#endif
15#ifdef USE_DISPATCH
16#include <dispatch/dispatch.h>
17#endif
18#include "3rdparty/sqlite3/sqlite3.h"
19
20const ccv_scd_param_t ccv_scd_default_params = {
21 .interval = 5,
22 .min_neighbors = 1,
23 .step_through = 4,
24 .size = {
25 .width = 48,
26 .height = 48,
27 },
28};
29
30#define CCV_SCD_CHANNEL(11) (11)
31
32// this uses a look up table for cubic root computation because rgb to luv only requires data within range of 0~1
33static inline float fast_cube_root(const float d)
34{
35 static const float cube_root[2048] = {
36 0.000000e+00, 7.875788e-02, 9.922871e-02, 1.135885e-01, 1.250203e-01, 1.346741e-01, 1.431126e-01, 1.506584e-01,
37 1.575158e-01, 1.638230e-01, 1.696787e-01, 1.751560e-01, 1.803105e-01, 1.851861e-01, 1.898177e-01, 1.942336e-01,
38 1.984574e-01, 2.025087e-01, 2.064040e-01, 2.101577e-01, 2.137818e-01, 2.172870e-01, 2.206827e-01, 2.239769e-01,
39 2.271770e-01, 2.302894e-01, 2.333199e-01, 2.362736e-01, 2.391553e-01, 2.419692e-01, 2.447191e-01, 2.474085e-01,
40 2.500407e-01, 2.526186e-01, 2.551450e-01, 2.576222e-01, 2.600528e-01, 2.624387e-01, 2.647821e-01, 2.670846e-01,
41 2.693482e-01, 2.715743e-01, 2.737645e-01, 2.759202e-01, 2.780428e-01, 2.801334e-01, 2.821933e-01, 2.842235e-01,
42 2.862251e-01, 2.881992e-01, 2.901465e-01, 2.920681e-01, 2.939647e-01, 2.958371e-01, 2.976862e-01, 2.995125e-01,
43 3.013168e-01, 3.030998e-01, 3.048621e-01, 3.066041e-01, 3.083267e-01, 3.100302e-01, 3.117152e-01, 3.133821e-01,
44 3.150315e-01, 3.166639e-01, 3.182795e-01, 3.198789e-01, 3.214625e-01, 3.230307e-01, 3.245837e-01, 3.261220e-01,
45 3.276460e-01, 3.291559e-01, 3.306521e-01, 3.321348e-01, 3.336045e-01, 3.350613e-01, 3.365056e-01, 3.379375e-01,
46 3.393574e-01, 3.407656e-01, 3.421622e-01, 3.435475e-01, 3.449216e-01, 3.462850e-01, 3.476377e-01, 3.489799e-01,
47 3.503119e-01, 3.516339e-01, 3.529460e-01, 3.542483e-01, 3.555412e-01, 3.568248e-01, 3.580992e-01, 3.593646e-01,
48 3.606211e-01, 3.618689e-01, 3.631082e-01, 3.643391e-01, 3.655617e-01, 3.667762e-01, 3.679827e-01, 3.691814e-01,
49 3.703723e-01, 3.715556e-01, 3.727314e-01, 3.738999e-01, 3.750610e-01, 3.762151e-01, 3.773621e-01, 3.785022e-01,
50 3.796354e-01, 3.807619e-01, 3.818818e-01, 3.829952e-01, 3.841021e-01, 3.852027e-01, 3.862970e-01, 3.873852e-01,
51 3.884673e-01, 3.895434e-01, 3.906136e-01, 3.916779e-01, 3.927365e-01, 3.937894e-01, 3.948367e-01, 3.958785e-01,
52 3.969149e-01, 3.979458e-01, 3.989714e-01, 3.999918e-01, 4.010071e-01, 4.020171e-01, 4.030222e-01, 4.040223e-01,
53 4.050174e-01, 4.060076e-01, 4.069931e-01, 4.079738e-01, 4.089499e-01, 4.099212e-01, 4.108880e-01, 4.118503e-01,
54 4.128081e-01, 4.137615e-01, 4.147105e-01, 4.156551e-01, 4.165955e-01, 4.175317e-01, 4.184637e-01, 4.193916e-01,
55 4.203153e-01, 4.212351e-01, 4.221508e-01, 4.230626e-01, 4.239704e-01, 4.248744e-01, 4.257746e-01, 4.266710e-01,
56 4.275636e-01, 4.284525e-01, 4.293377e-01, 4.302193e-01, 4.310973e-01, 4.319718e-01, 4.328427e-01, 4.337101e-01,
57 4.345741e-01, 4.354346e-01, 4.362918e-01, 4.371456e-01, 4.379961e-01, 4.388433e-01, 4.396872e-01, 4.405279e-01,
58 4.413654e-01, 4.421997e-01, 4.430309e-01, 4.438590e-01, 4.446840e-01, 4.455060e-01, 4.463249e-01, 4.471409e-01,
59 4.479539e-01, 4.487639e-01, 4.495711e-01, 4.503753e-01, 4.511767e-01, 4.519752e-01, 4.527710e-01, 4.535639e-01,
60 4.543541e-01, 4.551415e-01, 4.559263e-01, 4.567083e-01, 4.574877e-01, 4.582644e-01, 4.590385e-01, 4.598100e-01,
61 4.605789e-01, 4.613453e-01, 4.621091e-01, 4.628704e-01, 4.636292e-01, 4.643855e-01, 4.651394e-01, 4.658908e-01,
62 4.666398e-01, 4.673865e-01, 4.681307e-01, 4.688726e-01, 4.696122e-01, 4.703494e-01, 4.710843e-01, 4.718169e-01,
63 4.725473e-01, 4.732754e-01, 4.740013e-01, 4.747250e-01, 4.754464e-01, 4.761657e-01, 4.768828e-01, 4.775978e-01,
64 4.783106e-01, 4.790214e-01, 4.797300e-01, 4.804365e-01, 4.811410e-01, 4.818434e-01, 4.825437e-01, 4.832420e-01,
65 4.839384e-01, 4.846327e-01, 4.853250e-01, 4.860154e-01, 4.867038e-01, 4.873902e-01, 4.880748e-01, 4.887574e-01,
66 4.894381e-01, 4.901170e-01, 4.907939e-01, 4.914690e-01, 4.921423e-01, 4.928137e-01, 4.934832e-01, 4.941510e-01,
67 4.948170e-01, 4.954812e-01, 4.961436e-01, 4.968042e-01, 4.974631e-01, 4.981203e-01, 4.987757e-01, 4.994294e-01,
68 5.000814e-01, 5.007317e-01, 5.013803e-01, 5.020273e-01, 5.026726e-01, 5.033162e-01, 5.039582e-01, 5.045985e-01,
69 5.052372e-01, 5.058743e-01, 5.065099e-01, 5.071438e-01, 5.077761e-01, 5.084069e-01, 5.090362e-01, 5.096638e-01,
70 5.102900e-01, 5.109145e-01, 5.115376e-01, 5.121592e-01, 5.127792e-01, 5.133978e-01, 5.140148e-01, 5.146304e-01,
71 5.152445e-01, 5.158572e-01, 5.164684e-01, 5.170782e-01, 5.176865e-01, 5.182934e-01, 5.188988e-01, 5.195029e-01,
72 5.201056e-01, 5.207069e-01, 5.213068e-01, 5.219053e-01, 5.225024e-01, 5.230982e-01, 5.236927e-01, 5.242857e-01,
73 5.248775e-01, 5.254679e-01, 5.260570e-01, 5.266448e-01, 5.272312e-01, 5.278164e-01, 5.284002e-01, 5.289828e-01,
74 5.295641e-01, 5.301442e-01, 5.307229e-01, 5.313004e-01, 5.318767e-01, 5.324517e-01, 5.330254e-01, 5.335979e-01,
75 5.341693e-01, 5.347394e-01, 5.353082e-01, 5.358759e-01, 5.364423e-01, 5.370076e-01, 5.375717e-01, 5.381346e-01,
76 5.386963e-01, 5.392569e-01, 5.398163e-01, 5.403746e-01, 5.409316e-01, 5.414876e-01, 5.420424e-01, 5.425960e-01,
77 5.431486e-01, 5.437000e-01, 5.442503e-01, 5.447995e-01, 5.453476e-01, 5.458946e-01, 5.464405e-01, 5.469853e-01,
78 5.475290e-01, 5.480717e-01, 5.486133e-01, 5.491537e-01, 5.496932e-01, 5.502316e-01, 5.507689e-01, 5.513052e-01,
79 5.518404e-01, 5.523747e-01, 5.529078e-01, 5.534400e-01, 5.539711e-01, 5.545012e-01, 5.550303e-01, 5.555584e-01,
80 5.560855e-01, 5.566117e-01, 5.571368e-01, 5.576609e-01, 5.581840e-01, 5.587062e-01, 5.592273e-01, 5.597475e-01,
81 5.602668e-01, 5.607851e-01, 5.613024e-01, 5.618188e-01, 5.623342e-01, 5.628487e-01, 5.633622e-01, 5.638748e-01,
82 5.643865e-01, 5.648973e-01, 5.654072e-01, 5.659161e-01, 5.664241e-01, 5.669311e-01, 5.674374e-01, 5.679426e-01,
83 5.684470e-01, 5.689505e-01, 5.694531e-01, 5.699549e-01, 5.704557e-01, 5.709556e-01, 5.714548e-01, 5.719529e-01,
84 5.724503e-01, 5.729468e-01, 5.734424e-01, 5.739372e-01, 5.744311e-01, 5.749242e-01, 5.754164e-01, 5.759078e-01,
85 5.763984e-01, 5.768881e-01, 5.773770e-01, 5.778650e-01, 5.783523e-01, 5.788387e-01, 5.793243e-01, 5.798091e-01,
86 5.802931e-01, 5.807762e-01, 5.812586e-01, 5.817402e-01, 5.822210e-01, 5.827010e-01, 5.831801e-01, 5.836585e-01,
87 5.841362e-01, 5.846130e-01, 5.850891e-01, 5.855644e-01, 5.860389e-01, 5.865127e-01, 5.869856e-01, 5.874579e-01,
88 5.879294e-01, 5.884001e-01, 5.888700e-01, 5.893393e-01, 5.898077e-01, 5.902755e-01, 5.907425e-01, 5.912087e-01,
89 5.916742e-01, 5.921390e-01, 5.926031e-01, 5.930664e-01, 5.935290e-01, 5.939909e-01, 5.944521e-01, 5.949125e-01,
90 5.953723e-01, 5.958313e-01, 5.962896e-01, 5.967473e-01, 5.972042e-01, 5.976604e-01, 5.981160e-01, 5.985708e-01,
91 5.990250e-01, 5.994784e-01, 5.999312e-01, 6.003833e-01, 6.008347e-01, 6.012855e-01, 6.017355e-01, 6.021850e-01,
92 6.026337e-01, 6.030817e-01, 6.035291e-01, 6.039758e-01, 6.044219e-01, 6.048673e-01, 6.053120e-01, 6.057562e-01,
93 6.061996e-01, 6.066424e-01, 6.070846e-01, 6.075261e-01, 6.079670e-01, 6.084072e-01, 6.088468e-01, 6.092858e-01,
94 6.097241e-01, 6.101618e-01, 6.105989e-01, 6.110353e-01, 6.114712e-01, 6.119064e-01, 6.123410e-01, 6.127750e-01,
95 6.132084e-01, 6.136411e-01, 6.140732e-01, 6.145048e-01, 6.149357e-01, 6.153660e-01, 6.157957e-01, 6.162249e-01,
96 6.166534e-01, 6.170813e-01, 6.175086e-01, 6.179354e-01, 6.183616e-01, 6.187872e-01, 6.192122e-01, 6.196365e-01,
97 6.200604e-01, 6.204836e-01, 6.209063e-01, 6.213284e-01, 6.217499e-01, 6.221709e-01, 6.225913e-01, 6.230111e-01,
98 6.234304e-01, 6.238490e-01, 6.242672e-01, 6.246848e-01, 6.251017e-01, 6.255182e-01, 6.259341e-01, 6.263494e-01,
99 6.267643e-01, 6.271785e-01, 6.275922e-01, 6.280054e-01, 6.284180e-01, 6.288301e-01, 6.292416e-01, 6.296526e-01,
100 6.300631e-01, 6.304730e-01, 6.308824e-01, 6.312913e-01, 6.316996e-01, 6.321074e-01, 6.325147e-01, 6.329215e-01,
101 6.333277e-01, 6.337335e-01, 6.341386e-01, 6.345433e-01, 6.349475e-01, 6.353511e-01, 6.357543e-01, 6.361569e-01,
102 6.365590e-01, 6.369606e-01, 6.373618e-01, 6.377624e-01, 6.381625e-01, 6.385621e-01, 6.389612e-01, 6.393598e-01,
103 6.397579e-01, 6.401555e-01, 6.405526e-01, 6.409492e-01, 6.413454e-01, 6.417410e-01, 6.421362e-01, 6.425309e-01,
104 6.429250e-01, 6.433188e-01, 6.437120e-01, 6.441047e-01, 6.444970e-01, 6.448888e-01, 6.452801e-01, 6.456710e-01,
105 6.460613e-01, 6.464512e-01, 6.468406e-01, 6.472296e-01, 6.476181e-01, 6.480061e-01, 6.483937e-01, 6.487808e-01,
106 6.491674e-01, 6.495536e-01, 6.499393e-01, 6.503246e-01, 6.507094e-01, 6.510937e-01, 6.514776e-01, 6.518611e-01,
107 6.522441e-01, 6.526266e-01, 6.530087e-01, 6.533904e-01, 6.537716e-01, 6.541524e-01, 6.545327e-01, 6.549126e-01,
108 6.552920e-01, 6.556710e-01, 6.560495e-01, 6.564277e-01, 6.568054e-01, 6.571826e-01, 6.575595e-01, 6.579359e-01,
109 6.583118e-01, 6.586874e-01, 6.590625e-01, 6.594372e-01, 6.598114e-01, 6.601852e-01, 6.605586e-01, 6.609316e-01,
110 6.613042e-01, 6.616763e-01, 6.620481e-01, 6.624194e-01, 6.627903e-01, 6.631607e-01, 6.635308e-01, 6.639005e-01,
111 6.642697e-01, 6.646385e-01, 6.650070e-01, 6.653750e-01, 6.657426e-01, 6.661098e-01, 6.664766e-01, 6.668430e-01,
112 6.672090e-01, 6.675746e-01, 6.679398e-01, 6.683046e-01, 6.686690e-01, 6.690330e-01, 6.693966e-01, 6.697598e-01,
113 6.701226e-01, 6.704850e-01, 6.708471e-01, 6.712087e-01, 6.715700e-01, 6.719308e-01, 6.722913e-01, 6.726514e-01,
114 6.730111e-01, 6.733705e-01, 6.737294e-01, 6.740879e-01, 6.744461e-01, 6.748039e-01, 6.751614e-01, 6.755184e-01,
115 6.758750e-01, 6.762313e-01, 6.765872e-01, 6.769428e-01, 6.772979e-01, 6.776527e-01, 6.780071e-01, 6.783612e-01,
116 6.787149e-01, 6.790682e-01, 6.794212e-01, 6.797737e-01, 6.801260e-01, 6.804778e-01, 6.808293e-01, 6.811804e-01,
117 6.815312e-01, 6.818815e-01, 6.822316e-01, 6.825813e-01, 6.829306e-01, 6.832796e-01, 6.836282e-01, 6.839765e-01,
118 6.843244e-01, 6.846719e-01, 6.850191e-01, 6.853660e-01, 6.857125e-01, 6.860586e-01, 6.864043e-01, 6.867498e-01,
119 6.870949e-01, 6.874397e-01, 6.877841e-01, 6.881282e-01, 6.884719e-01, 6.888152e-01, 6.891583e-01, 6.895010e-01,
120 6.898433e-01, 6.901854e-01, 6.905270e-01, 6.908684e-01, 6.912094e-01, 6.915500e-01, 6.918904e-01, 6.922303e-01,
121 6.925700e-01, 6.929094e-01, 6.932484e-01, 6.935870e-01, 6.939254e-01, 6.942633e-01, 6.946011e-01, 6.949384e-01,
122 6.952754e-01, 6.956121e-01, 6.959485e-01, 6.962845e-01, 6.966202e-01, 6.969556e-01, 6.972907e-01, 6.976255e-01,
123 6.979599e-01, 6.982940e-01, 6.986278e-01, 6.989613e-01, 6.992944e-01, 6.996273e-01, 6.999598e-01, 7.002920e-01,
124 7.006239e-01, 7.009555e-01, 7.012867e-01, 7.016177e-01, 7.019483e-01, 7.022786e-01, 7.026086e-01, 7.029384e-01,
125 7.032678e-01, 7.035969e-01, 7.039256e-01, 7.042542e-01, 7.045823e-01, 7.049102e-01, 7.052377e-01, 7.055650e-01,
126 7.058919e-01, 7.062186e-01, 7.065449e-01, 7.068710e-01, 7.071967e-01, 7.075222e-01, 7.078474e-01, 7.081722e-01,
127 7.084967e-01, 7.088210e-01, 7.091449e-01, 7.094686e-01, 7.097920e-01, 7.101150e-01, 7.104378e-01, 7.107603e-01,
128 7.110825e-01, 7.114044e-01, 7.117260e-01, 7.120473e-01, 7.123684e-01, 7.126891e-01, 7.130095e-01, 7.133297e-01,
129 7.136496e-01, 7.139692e-01, 7.142885e-01, 7.146075e-01, 7.149262e-01, 7.152447e-01, 7.155629e-01, 7.158808e-01,
130 7.161984e-01, 7.165157e-01, 7.168328e-01, 7.171495e-01, 7.174660e-01, 7.177821e-01, 7.180981e-01, 7.184138e-01,
131 7.187291e-01, 7.190442e-01, 7.193590e-01, 7.196736e-01, 7.199879e-01, 7.203019e-01, 7.206156e-01, 7.209290e-01,
132 7.212422e-01, 7.215551e-01, 7.218677e-01, 7.221801e-01, 7.224922e-01, 7.228040e-01, 7.231156e-01, 7.234268e-01,
133 7.237378e-01, 7.240486e-01, 7.243591e-01, 7.246693e-01, 7.249793e-01, 7.252890e-01, 7.255983e-01, 7.259076e-01,
134 7.262164e-01, 7.265251e-01, 7.268335e-01, 7.271415e-01, 7.274494e-01, 7.277570e-01, 7.280643e-01, 7.283714e-01,
135 7.286782e-01, 7.289847e-01, 7.292911e-01, 7.295971e-01, 7.299029e-01, 7.302084e-01, 7.305137e-01, 7.308187e-01,
136 7.311234e-01, 7.314279e-01, 7.317322e-01, 7.320362e-01, 7.323400e-01, 7.326434e-01, 7.329467e-01, 7.332497e-01,
137 7.335525e-01, 7.338549e-01, 7.341572e-01, 7.344592e-01, 7.347609e-01, 7.350624e-01, 7.353637e-01, 7.356647e-01,
138 7.359655e-01, 7.362660e-01, 7.365662e-01, 7.368662e-01, 7.371660e-01, 7.374656e-01, 7.377649e-01, 7.380639e-01,
139 7.383628e-01, 7.386613e-01, 7.389597e-01, 7.392578e-01, 7.395556e-01, 7.398532e-01, 7.401506e-01, 7.404477e-01,
140 7.407446e-01, 7.410412e-01, 7.413377e-01, 7.416338e-01, 7.419298e-01, 7.422255e-01, 7.425209e-01, 7.428162e-01,
141 7.431112e-01, 7.434059e-01, 7.437005e-01, 7.439948e-01, 7.442889e-01, 7.445827e-01, 7.448763e-01, 7.451697e-01,
142 7.454628e-01, 7.457558e-01, 7.460485e-01, 7.463409e-01, 7.466331e-01, 7.469251e-01, 7.472169e-01, 7.475084e-01,
143 7.477998e-01, 7.480908e-01, 7.483817e-01, 7.486723e-01, 7.489627e-01, 7.492529e-01, 7.495428e-01, 7.498326e-01,
144 7.501221e-01, 7.504114e-01, 7.507005e-01, 7.509893e-01, 7.512779e-01, 7.515663e-01, 7.518545e-01, 7.521424e-01,
145 7.524302e-01, 7.527177e-01, 7.530050e-01, 7.532921e-01, 7.535789e-01, 7.538656e-01, 7.541520e-01, 7.544382e-01,
146 7.547241e-01, 7.550099e-01, 7.552955e-01, 7.555808e-01, 7.558660e-01, 7.561509e-01, 7.564356e-01, 7.567201e-01,
147 7.570043e-01, 7.572884e-01, 7.575722e-01, 7.578558e-01, 7.581393e-01, 7.584225e-01, 7.587055e-01, 7.589883e-01,
148 7.592708e-01, 7.595532e-01, 7.598354e-01, 7.601173e-01, 7.603990e-01, 7.606806e-01, 7.609619e-01, 7.612430e-01,
149 7.615239e-01, 7.618046e-01, 7.620851e-01, 7.623653e-01, 7.626454e-01, 7.629253e-01, 7.632049e-01, 7.634844e-01,
150 7.637637e-01, 7.640427e-01, 7.643216e-01, 7.646002e-01, 7.648786e-01, 7.651569e-01, 7.654349e-01, 7.657127e-01,
151 7.659904e-01, 7.662678e-01, 7.665451e-01, 7.668221e-01, 7.670989e-01, 7.673756e-01, 7.676520e-01, 7.679282e-01,
152 7.682042e-01, 7.684801e-01, 7.687557e-01, 7.690312e-01, 7.693064e-01, 7.695814e-01, 7.698563e-01, 7.701310e-01,
153 7.704054e-01, 7.706797e-01, 7.709538e-01, 7.712276e-01, 7.715013e-01, 7.717748e-01, 7.720481e-01, 7.723212e-01,
154 7.725941e-01, 7.728668e-01, 7.731394e-01, 7.734116e-01, 7.736838e-01, 7.739558e-01, 7.742275e-01, 7.744991e-01,
155 7.747704e-01, 7.750416e-01, 7.753126e-01, 7.755834e-01, 7.758540e-01, 7.761245e-01, 7.763947e-01, 7.766647e-01,
156 7.769346e-01, 7.772043e-01, 7.774737e-01, 7.777431e-01, 7.780122e-01, 7.782811e-01, 7.785498e-01, 7.788184e-01,
157 7.790868e-01, 7.793550e-01, 7.796230e-01, 7.798908e-01, 7.801584e-01, 7.804259e-01, 7.806932e-01, 7.809603e-01,
158 7.812271e-01, 7.814939e-01, 7.817604e-01, 7.820268e-01, 7.822930e-01, 7.825589e-01, 7.828248e-01, 7.830904e-01,
159 7.833558e-01, 7.836211e-01, 7.838862e-01, 7.841511e-01, 7.844158e-01, 7.846804e-01, 7.849448e-01, 7.852090e-01,
160 7.854730e-01, 7.857369e-01, 7.860005e-01, 7.862641e-01, 7.865273e-01, 7.867905e-01, 7.870535e-01, 7.873163e-01,
161 7.875788e-01, 7.878413e-01, 7.881036e-01, 7.883657e-01, 7.886276e-01, 7.888893e-01, 7.891509e-01, 7.894123e-01,
162 7.896735e-01, 7.899345e-01, 7.901954e-01, 7.904561e-01, 7.907166e-01, 7.909770e-01, 7.912372e-01, 7.914972e-01,
163 7.917571e-01, 7.920167e-01, 7.922763e-01, 7.925356e-01, 7.927948e-01, 7.930537e-01, 7.933126e-01, 7.935712e-01,
164 7.938297e-01, 7.940881e-01, 7.943462e-01, 7.946042e-01, 7.948620e-01, 7.951197e-01, 7.953772e-01, 7.956345e-01,
165 7.958916e-01, 7.961487e-01, 7.964054e-01, 7.966621e-01, 7.969186e-01, 7.971749e-01, 7.974311e-01, 7.976871e-01,
166 7.979429e-01, 7.981986e-01, 7.984541e-01, 7.987095e-01, 7.989646e-01, 7.992196e-01, 7.994745e-01, 7.997292e-01,
167 7.999837e-01, 8.002381e-01, 8.004923e-01, 8.007463e-01, 8.010002e-01, 8.012539e-01, 8.015075e-01, 8.017609e-01,
168 8.020141e-01, 8.022672e-01, 8.025202e-01, 8.027729e-01, 8.030255e-01, 8.032780e-01, 8.035302e-01, 8.037823e-01,
169 8.040344e-01, 8.042861e-01, 8.045378e-01, 8.047893e-01, 8.050406e-01, 8.052918e-01, 8.055428e-01, 8.057937e-01,
170 8.060444e-01, 8.062950e-01, 8.065454e-01, 8.067956e-01, 8.070457e-01, 8.072957e-01, 8.075454e-01, 8.077950e-01,
171 8.080446e-01, 8.082938e-01, 8.085430e-01, 8.087921e-01, 8.090409e-01, 8.092896e-01, 8.095381e-01, 8.097866e-01,
172 8.100348e-01, 8.102829e-01, 8.105308e-01, 8.107786e-01, 8.110263e-01, 8.112738e-01, 8.115211e-01, 8.117683e-01,
173 8.120154e-01, 8.122622e-01, 8.125089e-01, 8.127556e-01, 8.130020e-01, 8.132483e-01, 8.134944e-01, 8.137404e-01,
174 8.139862e-01, 8.142319e-01, 8.144775e-01, 8.147229e-01, 8.149682e-01, 8.152133e-01, 8.154582e-01, 8.157030e-01,
175 8.159477e-01, 8.161922e-01, 8.164365e-01, 8.166808e-01, 8.169249e-01, 8.171688e-01, 8.174126e-01, 8.176562e-01,
176 8.178997e-01, 8.181431e-01, 8.183863e-01, 8.186293e-01, 8.188722e-01, 8.191150e-01, 8.193576e-01, 8.196001e-01,
177 8.198425e-01, 8.200847e-01, 8.203267e-01, 8.205686e-01, 8.208104e-01, 8.210521e-01, 8.212935e-01, 8.215349e-01,
178 8.217760e-01, 8.220171e-01, 8.222581e-01, 8.224988e-01, 8.227395e-01, 8.229799e-01, 8.232203e-01, 8.234605e-01,
179 8.237006e-01, 8.239405e-01, 8.241804e-01, 8.244200e-01, 8.246595e-01, 8.248989e-01, 8.251381e-01, 8.253772e-01,
180 8.256162e-01, 8.258550e-01, 8.260937e-01, 8.263323e-01, 8.265706e-01, 8.268089e-01, 8.270471e-01, 8.272851e-01,
181 8.275229e-01, 8.277607e-01, 8.279983e-01, 8.282357e-01, 8.284730e-01, 8.287102e-01, 8.289472e-01, 8.291842e-01,
182 8.294209e-01, 8.296576e-01, 8.298941e-01, 8.301305e-01, 8.303667e-01, 8.306028e-01, 8.308387e-01, 8.310746e-01,
183 8.313103e-01, 8.315458e-01, 8.317813e-01, 8.320166e-01, 8.322517e-01, 8.324867e-01, 8.327217e-01, 8.329564e-01,
184 8.331911e-01, 8.334256e-01, 8.336599e-01, 8.338942e-01, 8.341283e-01, 8.343623e-01, 8.345962e-01, 8.348299e-01,
185 8.350635e-01, 8.352969e-01, 8.355302e-01, 8.357634e-01, 8.359964e-01, 8.362294e-01, 8.364622e-01, 8.366948e-01,
186 8.369274e-01, 8.371598e-01, 8.373921e-01, 8.376243e-01, 8.378563e-01, 8.380882e-01, 8.383200e-01, 8.385516e-01,
187 8.387831e-01, 8.390145e-01, 8.392458e-01, 8.394769e-01, 8.397079e-01, 8.399388e-01, 8.401695e-01, 8.404002e-01,
188 8.406307e-01, 8.408611e-01, 8.410913e-01, 8.413214e-01, 8.415514e-01, 8.417813e-01, 8.420110e-01, 8.422406e-01,
189 8.424702e-01, 8.426995e-01, 8.429288e-01, 8.431579e-01, 8.433869e-01, 8.436158e-01, 8.438445e-01, 8.440731e-01,
190 8.443016e-01, 8.445300e-01, 8.447582e-01, 8.449863e-01, 8.452144e-01, 8.454422e-01, 8.456700e-01, 8.458977e-01,
191 8.461251e-01, 8.463526e-01, 8.465798e-01, 8.468069e-01, 8.470340e-01, 8.472609e-01, 8.474877e-01, 8.477143e-01,
192 8.479409e-01, 8.481673e-01, 8.483936e-01, 8.486198e-01, 8.488458e-01, 8.490717e-01, 8.492976e-01, 8.495233e-01,
193 8.497488e-01, 8.499743e-01, 8.501996e-01, 8.504249e-01, 8.506500e-01, 8.508750e-01, 8.510998e-01, 8.513246e-01,
194 8.515491e-01, 8.517737e-01, 8.519981e-01, 8.522223e-01, 8.524465e-01, 8.526706e-01, 8.528944e-01, 8.531182e-01,
195 8.533419e-01, 8.535655e-01, 8.537889e-01, 8.540123e-01, 8.542355e-01, 8.544586e-01, 8.546816e-01, 8.549044e-01,
196 8.551272e-01, 8.553498e-01, 8.555723e-01, 8.557947e-01, 8.560170e-01, 8.562392e-01, 8.564612e-01, 8.566832e-01,
197 8.569050e-01, 8.571267e-01, 8.573483e-01, 8.575698e-01, 8.577912e-01, 8.580124e-01, 8.582336e-01, 8.584546e-01,
198 8.586755e-01, 8.588963e-01, 8.591169e-01, 8.593375e-01, 8.595580e-01, 8.597783e-01, 8.599985e-01, 8.602186e-01,
199 8.604387e-01, 8.606585e-01, 8.608783e-01, 8.610980e-01, 8.613176e-01, 8.615370e-01, 8.617563e-01, 8.619756e-01,
200 8.621947e-01, 8.624136e-01, 8.626326e-01, 8.628513e-01, 8.630700e-01, 8.632885e-01, 8.635070e-01, 8.637253e-01,
201 8.639436e-01, 8.641617e-01, 8.643796e-01, 8.645976e-01, 8.648154e-01, 8.650330e-01, 8.652506e-01, 8.654680e-01,
202 8.656853e-01, 8.659026e-01, 8.661197e-01, 8.663368e-01, 8.665537e-01, 8.667705e-01, 8.669872e-01, 8.672037e-01,
203 8.674202e-01, 8.676366e-01, 8.678529e-01, 8.680690e-01, 8.682851e-01, 8.685010e-01, 8.687168e-01, 8.689325e-01,
204 8.691481e-01, 8.693637e-01, 8.695791e-01, 8.697944e-01, 8.700095e-01, 8.702246e-01, 8.704396e-01, 8.706545e-01,
205 8.708693e-01, 8.710839e-01, 8.712984e-01, 8.715129e-01, 8.717272e-01, 8.719414e-01, 8.721556e-01, 8.723696e-01,
206 8.725836e-01, 8.727974e-01, 8.730111e-01, 8.732247e-01, 8.734382e-01, 8.736516e-01, 8.738649e-01, 8.740780e-01,
207 8.742912e-01, 8.745041e-01, 8.747170e-01, 8.749298e-01, 8.751425e-01, 8.753550e-01, 8.755675e-01, 8.757799e-01,
208 8.759921e-01, 8.762043e-01, 8.764163e-01, 8.766283e-01, 8.768401e-01, 8.770519e-01, 8.772635e-01, 8.774751e-01,
209 8.776865e-01, 8.778979e-01, 8.781091e-01, 8.783202e-01, 8.785312e-01, 8.787422e-01, 8.789530e-01, 8.791637e-01,
210 8.793744e-01, 8.795849e-01, 8.797953e-01, 8.800057e-01, 8.802159e-01, 8.804260e-01, 8.806360e-01, 8.808460e-01,
211 8.810558e-01, 8.812655e-01, 8.814751e-01, 8.816847e-01, 8.818941e-01, 8.821034e-01, 8.823127e-01, 8.825217e-01,
212 8.827308e-01, 8.829397e-01, 8.831486e-01, 8.833573e-01, 8.835659e-01, 8.837745e-01, 8.839829e-01, 8.841912e-01,
213 8.843995e-01, 8.846076e-01, 8.848156e-01, 8.850236e-01, 8.852314e-01, 8.854392e-01, 8.856469e-01, 8.858544e-01,
214 8.860618e-01, 8.862692e-01, 8.864765e-01, 8.866837e-01, 8.868908e-01, 8.870977e-01, 8.873046e-01, 8.875114e-01,
215 8.877181e-01, 8.879247e-01, 8.881311e-01, 8.883376e-01, 8.885438e-01, 8.887501e-01, 8.889562e-01, 8.891622e-01,
216 8.893681e-01, 8.895739e-01, 8.897797e-01, 8.899853e-01, 8.901908e-01, 8.903963e-01, 8.906016e-01, 8.908069e-01,
217 8.910121e-01, 8.912171e-01, 8.914221e-01, 8.916270e-01, 8.918318e-01, 8.920364e-01, 8.922410e-01, 8.924455e-01,
218 8.926499e-01, 8.928543e-01, 8.930585e-01, 8.932626e-01, 8.934667e-01, 8.936706e-01, 8.938744e-01, 8.940782e-01,
219 8.942819e-01, 8.944854e-01, 8.946889e-01, 8.948923e-01, 8.950956e-01, 8.952988e-01, 8.955019e-01, 8.957049e-01,
220 8.959078e-01, 8.961107e-01, 8.963134e-01, 8.965160e-01, 8.967186e-01, 8.969210e-01, 8.971235e-01, 8.973257e-01,
221 8.975279e-01, 8.977300e-01, 8.979320e-01, 8.981339e-01, 8.983358e-01, 8.985375e-01, 8.987392e-01, 8.989407e-01,
222 8.991421e-01, 8.993436e-01, 8.995448e-01, 8.997460e-01, 8.999471e-01, 9.001482e-01, 9.003491e-01, 9.005499e-01,
223 9.007506e-01, 9.009513e-01, 9.011519e-01, 9.013523e-01, 9.015527e-01, 9.017531e-01, 9.019532e-01, 9.021534e-01,
224 9.023534e-01, 9.025534e-01, 9.027532e-01, 9.029530e-01, 9.031526e-01, 9.033523e-01, 9.035518e-01, 9.037512e-01,
225 9.039505e-01, 9.041498e-01, 9.043489e-01, 9.045479e-01, 9.047469e-01, 9.049459e-01, 9.051446e-01, 9.053434e-01,
226 9.055420e-01, 9.057405e-01, 9.059390e-01, 9.061373e-01, 9.063356e-01, 9.065338e-01, 9.067319e-01, 9.069299e-01,
227 9.071279e-01, 9.073257e-01, 9.075235e-01, 9.077212e-01, 9.079187e-01, 9.081162e-01, 9.083136e-01, 9.085110e-01,
228 9.087082e-01, 9.089054e-01, 9.091024e-01, 9.092994e-01, 9.094964e-01, 9.096932e-01, 9.098899e-01, 9.100866e-01,
229 9.102831e-01, 9.104796e-01, 9.106760e-01, 9.108723e-01, 9.110685e-01, 9.112647e-01, 9.114607e-01, 9.116567e-01,
230 9.118526e-01, 9.120483e-01, 9.122441e-01, 9.124397e-01, 9.126353e-01, 9.128307e-01, 9.130261e-01, 9.132214e-01,
231 9.134166e-01, 9.136118e-01, 9.138068e-01, 9.140018e-01, 9.141967e-01, 9.143915e-01, 9.145862e-01, 9.147808e-01,
232 9.149753e-01, 9.151698e-01, 9.153642e-01, 9.155585e-01, 9.157528e-01, 9.159469e-01, 9.161409e-01, 9.163349e-01,
233 9.165288e-01, 9.167226e-01, 9.169164e-01, 9.171100e-01, 9.173036e-01, 9.174970e-01, 9.176905e-01, 9.178838e-01,
234 9.180770e-01, 9.182702e-01, 9.184632e-01, 9.186562e-01, 9.188492e-01, 9.190420e-01, 9.192348e-01, 9.194274e-01,
235 9.196200e-01, 9.198125e-01, 9.200049e-01, 9.201973e-01, 9.203895e-01, 9.205818e-01, 9.207739e-01, 9.209659e-01,
236 9.211578e-01, 9.213497e-01, 9.215415e-01, 9.217332e-01, 9.219248e-01, 9.221163e-01, 9.223078e-01, 9.224992e-01,
237 9.226905e-01, 9.228818e-01, 9.230729e-01, 9.232640e-01, 9.234550e-01, 9.236459e-01, 9.238367e-01, 9.240275e-01,
238 9.242182e-01, 9.244088e-01, 9.245993e-01, 9.247897e-01, 9.249801e-01, 9.251704e-01, 9.253606e-01, 9.255507e-01,
239 9.257408e-01, 9.259307e-01, 9.261206e-01, 9.263105e-01, 9.265002e-01, 9.266899e-01, 9.268795e-01, 9.270689e-01,
240 9.272584e-01, 9.274477e-01, 9.276370e-01, 9.278262e-01, 9.280154e-01, 9.282044e-01, 9.283934e-01, 9.285822e-01,
241 9.287710e-01, 9.289598e-01, 9.291484e-01, 9.293370e-01, 9.295255e-01, 9.297140e-01, 9.299023e-01, 9.300906e-01,
242 9.302788e-01, 9.304669e-01, 9.306549e-01, 9.308429e-01, 9.310308e-01, 9.312186e-01, 9.314064e-01, 9.315941e-01,
243 9.317816e-01, 9.319692e-01, 9.321566e-01, 9.323440e-01, 9.325313e-01, 9.327185e-01, 9.329057e-01, 9.330927e-01,
244 9.332797e-01, 9.334666e-01, 9.336535e-01, 9.338402e-01, 9.340270e-01, 9.342135e-01, 9.344001e-01, 9.345866e-01,
245 9.347730e-01, 9.349593e-01, 9.351455e-01, 9.353317e-01, 9.355178e-01, 9.357038e-01, 9.358898e-01, 9.360756e-01,
246 9.362615e-01, 9.364472e-01, 9.366328e-01, 9.368184e-01, 9.370039e-01, 9.371893e-01, 9.373747e-01, 9.375600e-01,
247 9.377452e-01, 9.379303e-01, 9.381154e-01, 9.383004e-01, 9.384854e-01, 9.386702e-01, 9.388550e-01, 9.390397e-01,
248 9.392243e-01, 9.394089e-01, 9.395934e-01, 9.397778e-01, 9.399621e-01, 9.401464e-01, 9.403306e-01, 9.405147e-01,
249 9.406988e-01, 9.408827e-01, 9.410667e-01, 9.412505e-01, 9.414343e-01, 9.416180e-01, 9.418016e-01, 9.419851e-01,
250 9.421686e-01, 9.423520e-01, 9.425353e-01, 9.427186e-01, 9.429018e-01, 9.430850e-01, 9.432680e-01, 9.434510e-01,
251 9.436339e-01, 9.438167e-01, 9.439995e-01, 9.441822e-01, 9.443648e-01, 9.445474e-01, 9.447299e-01, 9.449123e-01,
252 9.450946e-01, 9.452769e-01, 9.454591e-01, 9.456412e-01, 9.458233e-01, 9.460053e-01, 9.461872e-01, 9.463691e-01,
253 9.465508e-01, 9.467326e-01, 9.469142e-01, 9.470958e-01, 9.472773e-01, 9.474587e-01, 9.476401e-01, 9.478214e-01,
254 9.480026e-01, 9.481838e-01, 9.483649e-01, 9.485459e-01, 9.487268e-01, 9.489077e-01, 9.490886e-01, 9.492693e-01,
255 9.494500e-01, 9.496306e-01, 9.498111e-01, 9.499916e-01, 9.501719e-01, 9.503523e-01, 9.505326e-01, 9.507128e-01,
256 9.508929e-01, 9.510729e-01, 9.512529e-01, 9.514329e-01, 9.516127e-01, 9.517925e-01, 9.519722e-01, 9.521519e-01,
257 9.523315e-01, 9.525110e-01, 9.526904e-01, 9.528698e-01, 9.530491e-01, 9.532284e-01, 9.534075e-01, 9.535866e-01,
258 9.537657e-01, 9.539447e-01, 9.541236e-01, 9.543024e-01, 9.544812e-01, 9.546599e-01, 9.548386e-01, 9.550171e-01,
259 9.551957e-01, 9.553741e-01, 9.555525e-01, 9.557307e-01, 9.559090e-01, 9.560872e-01, 9.562653e-01, 9.564433e-01,
260 9.566213e-01, 9.567992e-01, 9.569771e-01, 9.571549e-01, 9.573326e-01, 9.575102e-01, 9.576878e-01, 9.578653e-01,
261 9.580427e-01, 9.582201e-01, 9.583974e-01, 9.585747e-01, 9.587519e-01, 9.589290e-01, 9.591061e-01, 9.592831e-01,
262 9.594600e-01, 9.596368e-01, 9.598137e-01, 9.599904e-01, 9.601671e-01, 9.603436e-01, 9.605201e-01, 9.606966e-01,
263 9.608730e-01, 9.610494e-01, 9.612256e-01, 9.614019e-01, 9.615780e-01, 9.617541e-01, 9.619301e-01, 9.621060e-01,
264 9.622819e-01, 9.624578e-01, 9.626336e-01, 9.628092e-01, 9.629849e-01, 9.631604e-01, 9.633359e-01, 9.635113e-01,
265 9.636867e-01, 9.638621e-01, 9.640373e-01, 9.642125e-01, 9.643876e-01, 9.645627e-01, 9.647377e-01, 9.649126e-01,
266 9.650874e-01, 9.652622e-01, 9.654370e-01, 9.656116e-01, 9.657863e-01, 9.659608e-01, 9.661353e-01, 9.663097e-01,
267 9.664841e-01, 9.666584e-01, 9.668326e-01, 9.670068e-01, 9.671809e-01, 9.673550e-01, 9.675289e-01, 9.677029e-01,
268 9.678767e-01, 9.680505e-01, 9.682242e-01, 9.683979e-01, 9.685715e-01, 9.687451e-01, 9.689186e-01, 9.690920e-01,
269 9.692653e-01, 9.694387e-01, 9.696119e-01, 9.697851e-01, 9.699582e-01, 9.701312e-01, 9.703043e-01, 9.704772e-01,
270 9.706500e-01, 9.708228e-01, 9.709955e-01, 9.711683e-01, 9.713409e-01, 9.715135e-01, 9.716859e-01, 9.718584e-01,
271 9.720308e-01, 9.722031e-01, 9.723753e-01, 9.725475e-01, 9.727197e-01, 9.728917e-01, 9.730637e-01, 9.732357e-01,
272 9.734076e-01, 9.735794e-01, 9.737512e-01, 9.739228e-01, 9.740945e-01, 9.742661e-01, 9.744377e-01, 9.746091e-01,
273 9.747805e-01, 9.749519e-01, 9.751231e-01, 9.752944e-01, 9.754655e-01, 9.756366e-01, 9.758077e-01, 9.759787e-01,
274 9.761496e-01, 9.763204e-01, 9.764913e-01, 9.766620e-01, 9.768327e-01, 9.770033e-01, 9.771739e-01, 9.773444e-01,
275 9.775148e-01, 9.776852e-01, 9.778556e-01, 9.780258e-01, 9.781960e-01, 9.783661e-01, 9.785362e-01, 9.787063e-01,
276 9.788762e-01, 9.790462e-01, 9.792160e-01, 9.793859e-01, 9.795555e-01, 9.797252e-01, 9.798949e-01, 9.800645e-01,
277 9.802339e-01, 9.804034e-01, 9.805728e-01, 9.807421e-01, 9.809114e-01, 9.810806e-01, 9.812497e-01, 9.814188e-01,
278 9.815878e-01, 9.817568e-01, 9.819257e-01, 9.820946e-01, 9.822634e-01, 9.824321e-01, 9.826008e-01, 9.827695e-01,
279 9.829381e-01, 9.831066e-01, 9.832750e-01, 9.834434e-01, 9.836118e-01, 9.837800e-01, 9.839482e-01, 9.841164e-01,
280 9.842845e-01, 9.844526e-01, 9.846206e-01, 9.847885e-01, 9.849564e-01, 9.851242e-01, 9.852920e-01, 9.854597e-01,
281 9.856274e-01, 9.857950e-01, 9.859625e-01, 9.861299e-01, 9.862974e-01, 9.864647e-01, 9.866320e-01, 9.867993e-01,
282 9.869665e-01, 9.871337e-01, 9.873008e-01, 9.874678e-01, 9.876347e-01, 9.878017e-01, 9.879685e-01, 9.881353e-01,
283 9.883021e-01, 9.884688e-01, 9.886354e-01, 9.888020e-01, 9.889685e-01, 9.891350e-01, 9.893014e-01, 9.894677e-01,
284 9.896340e-01, 9.898003e-01, 9.899665e-01, 9.901326e-01, 9.902986e-01, 9.904646e-01, 9.906306e-01, 9.907965e-01,
285 9.909624e-01, 9.911281e-01, 9.912939e-01, 9.914596e-01, 9.916252e-01, 9.917908e-01, 9.919563e-01, 9.921218e-01,
286 9.922872e-01, 9.924526e-01, 9.926178e-01, 9.927831e-01, 9.929483e-01, 9.931134e-01, 9.932785e-01, 9.934435e-01,
287 9.936085e-01, 9.937734e-01, 9.939383e-01, 9.941031e-01, 9.942678e-01, 9.944325e-01, 9.945971e-01, 9.947617e-01,
288 9.949263e-01, 9.950907e-01, 9.952552e-01, 9.954196e-01, 9.955838e-01, 9.957481e-01, 9.959123e-01, 9.960765e-01,
289 9.962406e-01, 9.964046e-01, 9.965686e-01, 9.967325e-01, 9.968964e-01, 9.970602e-01, 9.972240e-01, 9.973878e-01,
290 9.975514e-01, 9.977150e-01, 9.978786e-01, 9.980421e-01, 9.982055e-01, 9.983689e-01, 9.985323e-01, 9.986956e-01,
291 9.988588e-01, 9.990220e-01, 9.991851e-01, 9.993482e-01, 9.995112e-01, 9.996742e-01, 9.998372e-01, 1.000000e+00,
292 };
293 int i = (int)(d * 2047);
294 assert(i >= 0 && i < 2048)((void) sizeof ((i >= 0 && i < 2048) ? 1 : 0), __extension__
({ if (i >= 0 && i < 2048) ; else __assert_fail
("i >= 0 && i < 2048", "ccv_scd.c", 294, __extension__
__PRETTY_FUNCTION__); }))
;
295 return cube_root[i];
296}
297
298static inline void _ccv_rgb_to_luv(const float r, const float g, const float b, float* pl, float* pu, float* pv)
299{
300 const float x = 0.412453f * r + 0.35758f * g + 0.180423f * b;
301 const float y = 0.212671f * r + 0.71516f * g + 0.072169f * b;
302 const float z = 0.019334f * r + 0.119193f * g + 0.950227f * b;
303
304 const float x_n = 0.312713f, y_n = 0.329016f;
305 const float uv_n_divisor = -2.f * x_n + 12.f * y_n + 3.f;
306 const float u_n = 4.f * x_n / uv_n_divisor;
307 const float v_n = 9.f * y_n / uv_n_divisor;
308
309 const float uv_divisor = ccv_max((x + 15.f * y + 3.f * z), FLT_EPSILON)({ typeof ((x + 15.f * y + 3.f * z)) _a = ((x + 15.f * y + 3.f
* z)); typeof (1.19209290e-7F) _b = (1.19209290e-7F); (_a >
_b) ? _a : _b; })
;
310 const float u = 4.f * x / uv_divisor;
311 const float v = 9.f * y / uv_divisor;
312
313 const float y_cube_root = fast_cube_root(y);
314
315 const float l_value = ccv_max(0.f, ((116.f * y_cube_root) - 16.f))({ typeof (0.f) _a = (0.f); typeof (((116.f * y_cube_root) - 16.f
)) _b = (((116.f * y_cube_root) - 16.f)); (_a > _b) ? _a :
_b; })
;
316 const float u_value = 13.f * l_value * (u - u_n);
317 const float v_value = 13.f * l_value * (v - v_n);
318
319 // L in [0, 100], U in [-134, 220], V in [-140, 122]
320 *pl = l_value * (255.f / 100.f);
321 *pu = (u_value + 134.f) * (255.f / (220.f + 134.f));
322 *pv = (v_value + 140.f) * (255.f / (122.f + 140.f));
323}
324
325void ccv_scd(ccv_dense_matrix_t* a, ccv_dense_matrix_t** b, int type)
326{
327 int ch = CCV_GET_CHANNEL(a->type)((a->type) & 0xFFF);
328 assert(ch == 1 || ch == 3)((void) sizeof ((ch == 1 || ch == 3) ? 1 : 0), __extension__ (
{ if (ch == 1 || ch == 3) ; else __assert_fail ("ch == 1 || ch == 3"
, "ccv_scd.c", 328, __extension__ __PRETTY_FUNCTION__); }))
;
329 ccv_declare_derived_signature(sig, a->sig != 0, ccv_sign_with_literal("ccv_scd"), a->sig, CCV_EOF_SIGN)char _ccv_identifier_329[] = ("ccv_scd"); size_t _ccv_string_size_329
= sizeof(_ccv_identifier_329);; uint64_t sig = (a->sig !=
0) ? ccv_cache_generate_signature(_ccv_identifier_329, _ccv_string_size_329
, a->sig, ((uint64_t)0)) : 0;
;
330 // diagonal u, v, x, y and LUV color, therefore 11 channels
331 ccv_dense_matrix_t* db = *b = ccv_dense_matrix_renew(*b, a->rows, a->cols, CCV_32F | 11, CCV_32F | 11, sig);
332 ccv_object_return_if_cached(, db){ if ((!(db) || (((int*)(db))[0] & CCV_GARBAGE)) &&
(!(0) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0
) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (
((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int
*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0)
)[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] &
CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE
)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE)) &&
(!(0) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0
) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (
((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int
*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0)
)[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] &
CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE
)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE)) &&
(!(0) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0
) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (
((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int
*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0)
)[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] &
CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE
)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE)) &&
(!(0) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0
) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (
((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int
*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0)
)[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] &
CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE
)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE)) &&
(!(0) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0
) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (
((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int
*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0)
)[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] &
CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE
)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE)) &&
(!(0) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0
) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (
((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int
*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0)
)[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] &
CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE
)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE)) &&
(!(0) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0
) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (
((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int
*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0)
)[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] &
CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE
)) && (!(0) || (((int*)(0))[0] & CCV_GARBAGE)) &&
(!(0) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0
) || (((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (
((int*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int
*)(0))[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0)
)[0] & CCV_GARBAGE)) && (!(0) || (((int*)(0))[0] &
CCV_GARBAGE))) { (void)((db) && (((int*)(db))[0] &=
~CCV_GARBAGE));(void)((0) && (((int*)(0))[0] &= ~
CCV_GARBAGE));(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE
));(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE)
);(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE))
;(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));
(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(
void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void
)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void)
((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void)(
(0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void)((
0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void)((0
) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void)((0)
&& (((int*)(0))[0] &= ~CCV_GARBAGE));(void)((0) &&
(((int*)(0))[0] &= ~CCV_GARBAGE));(void)((0) && (
((int*)(0))[0] &= ~CCV_GARBAGE));(void)((0) && ((
(int*)(0))[0] &= ~CCV_GARBAGE));(void)((0) && (((
int*)(0))[0] &= ~CCV_GARBAGE));(void)((0) && (((int
*)(0))[0] &= ~CCV_GARBAGE));(void)((0) && (((int*
)(0))[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)
(0))[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(
0))[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0
))[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0)
)[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0))
[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0))[
0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0))[0
] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0))[0]
&= ~CCV_GARBAGE));(void)((0) && (((int*)(0))[0] &=
~CCV_GARBAGE));(void)((0) && (((int*)(0))[0] &= ~
CCV_GARBAGE));(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE
));(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE)
);(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE))
;(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));
(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(
void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void
)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void)
((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void)(
(0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void)((
0) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void)((0
) && (((int*)(0))[0] &= ~CCV_GARBAGE));(void)((0)
&& (((int*)(0))[0] &= ~CCV_GARBAGE));(void)((0) &&
(((int*)(0))[0] &= ~CCV_GARBAGE));(void)((0) && (
((int*)(0))[0] &= ~CCV_GARBAGE));(void)((0) && ((
(int*)(0))[0] &= ~CCV_GARBAGE));(void)((0) && (((
int*)(0))[0] &= ~CCV_GARBAGE));(void)((0) && (((int
*)(0))[0] &= ~CCV_GARBAGE));(void)((0) && (((int*
)(0))[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)
(0))[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(
0))[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0
))[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0)
)[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0))
[0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0))[
0] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0))[0
] &= ~CCV_GARBAGE));(void)((0) && (((int*)(0))[0]
&= ~CCV_GARBAGE));(void)((0) && (((int*)(0))[0] &=
~CCV_GARBAGE));(void)((0) && (((int*)(0))[0] &= ~
CCV_GARBAGE));(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE
));(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE)
);(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE))
;(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));
(void)((0) && (((int*)(0))[0] &= ~CCV_GARBAGE));;
; return ; } }
;
333 ccv_dense_matrix_t* blur = 0;
334 ccv_blur(a, &blur, 0, 0.5); // do a modest blur, which suppresses noise
335 ccv_dense_matrix_t* dx = 0;
336 ccv_sobel(blur, &dx, 0, 1, 0);
337 ccv_dense_matrix_t* dy = 0;
338 ccv_sobel(blur, &dy, 0, 0, 1);
339 ccv_dense_matrix_t* du = 0;
340 ccv_sobel(blur, &du, 0, 1, 1);
341 ccv_dense_matrix_t* dv = 0;
342 ccv_sobel(blur, &dv, 0, -1, 1);
343 ccv_matrix_free(blur);
344 assert(CCV_GET_DATA_TYPE(dx->type) == CCV_GET_DATA_TYPE(dy->type))((void) sizeof ((((dx->type) & 0xFF000) == ((dy->type
) & 0xFF000)) ? 1 : 0), __extension__ ({ if (((dx->type
) & 0xFF000) == ((dy->type) & 0xFF000)) ; else __assert_fail
("CCV_GET_DATA_TYPE(dx->type) == CCV_GET_DATA_TYPE(dy->type)"
, "ccv_scd.c", 344, __extension__ __PRETTY_FUNCTION__); }))
;
345 assert(CCV_GET_DATA_TYPE(dy->type) == CCV_GET_DATA_TYPE(du->type))((void) sizeof ((((dy->type) & 0xFF000) == ((du->type
) & 0xFF000)) ? 1 : 0), __extension__ ({ if (((dy->type
) & 0xFF000) == ((du->type) & 0xFF000)) ; else __assert_fail
("CCV_GET_DATA_TYPE(dy->type) == CCV_GET_DATA_TYPE(du->type)"
, "ccv_scd.c", 345, __extension__ __PRETTY_FUNCTION__); }))
;
346 assert(CCV_GET_DATA_TYPE(du->type) == CCV_GET_DATA_TYPE(dv->type))((void) sizeof ((((du->type) & 0xFF000) == ((dv->type
) & 0xFF000)) ? 1 : 0), __extension__ ({ if (((du->type
) & 0xFF000) == ((dv->type) & 0xFF000)) ; else __assert_fail
("CCV_GET_DATA_TYPE(du->type) == CCV_GET_DATA_TYPE(dv->type)"
, "ccv_scd.c", 346, __extension__ __PRETTY_FUNCTION__); }))
;
347 assert(CCV_GET_CHANNEL(dx->type) == CCV_GET_CHANNEL(dy->type))((void) sizeof ((((dx->type) & 0xFFF) == ((dy->type
) & 0xFFF)) ? 1 : 0), __extension__ ({ if (((dx->type)
& 0xFFF) == ((dy->type) & 0xFFF)) ; else __assert_fail
("CCV_GET_CHANNEL(dx->type) == CCV_GET_CHANNEL(dy->type)"
, "ccv_scd.c", 347, __extension__ __PRETTY_FUNCTION__); }))
;
348 assert(CCV_GET_CHANNEL(dy->type) == CCV_GET_CHANNEL(du->type))((void) sizeof ((((dy->type) & 0xFFF) == ((du->type
) & 0xFFF)) ? 1 : 0), __extension__ ({ if (((dy->type)
& 0xFFF) == ((du->type) & 0xFFF)) ; else __assert_fail
("CCV_GET_CHANNEL(dy->type) == CCV_GET_CHANNEL(du->type)"
, "ccv_scd.c", 348, __extension__ __PRETTY_FUNCTION__); }))
;
349 assert(CCV_GET_CHANNEL(du->type) == CCV_GET_CHANNEL(dv->type))((void) sizeof ((((du->type) & 0xFFF) == ((dv->type
) & 0xFFF)) ? 1 : 0), __extension__ ({ if (((du->type)
& 0xFFF) == ((dv->type) & 0xFFF)) ; else __assert_fail
("CCV_GET_CHANNEL(du->type) == CCV_GET_CHANNEL(dv->type)"
, "ccv_scd.c", 349, __extension__ __PRETTY_FUNCTION__); }))
;
350 // this is a naive unoptimized implementation yet
351 int i, j, k;
352 unsigned char* a_ptr = a->data.u8;
353 unsigned char* dx_ptr = dx->data.u8;
354 unsigned char* dy_ptr = dy->data.u8;
355 unsigned char* du_ptr = du->data.u8;
356 unsigned char* dv_ptr = dv->data.u8;
357 float* dbp = db->data.f32;
358 if (ch == 1)
359 {
360#define for_block(_for_get_d, _for_get_a) \
361 for (i = 0; i < a->rows; i++) \
362 { \
363 for (j = 0; j < a->cols; j++) \
364 { \
365 float fdx = _for_get_d(dx_ptr, j), fdy = _for_get_d(dy_ptr, j); \
366 float fdu = _for_get_d(du_ptr, j), fdv = _for_get_d(dv_ptr, j); \
367 float adx = fabsf(fdx), ady = fabsf(fdy); \
368 float adu = fabsf(fdu), adv = fabsf(fdv); \
369 dbp[0] = fdx, dbp[1] = fdy; \
370 dbp[2] = fdu, dbp[3] = fdv; \
371 dbp[4] = adx, dbp[5] = ady; \
372 dbp[6] = adu, dbp[7] = adv; \
373 dbp[8] = _for_get_a(a_ptr, j) / 255.0; \
374 dbp[9] = dbp[10] = 0; \
375 dbp += 11; \
376 } \
377 a_ptr += a->step; \
378 dx_ptr += dx->step; \
379 dy_ptr += dy->step; \
380 du_ptr += du->step; \
381 dv_ptr += dv->step; \
382 }
383 ccv_matrix_getter(dx->type, ccv_matrix_getter_a, a->type, for_block){ switch (((dx->type) & 0xFF000)) { case CCV_32S: { { switch
(((a->type) & 0xFF000)) { case CCV_32S: { for_block(_ccv_get_32s_value
, _ccv_get_32s_value); break; } case CCV_32F: { for_block(_ccv_get_32s_value
, _ccv_get_32f_value); break; } case CCV_64S: { for_block(_ccv_get_32s_value
, _ccv_get_64s_value); break; } case CCV_64F: { for_block(_ccv_get_32s_value
, _ccv_get_64f_value); break; } default: { for_block(_ccv_get_32s_value
, _ccv_get_8u_value); } } }; break; } case CCV_32F: { { switch
(((a->type) & 0xFF000)) { case CCV_32S: { for_block(_ccv_get_32f_value
, _ccv_get_32s_value); break; } case CCV_32F: { for_block(_ccv_get_32f_value
, _ccv_get_32f_value); break; } case CCV_64S: { for_block(_ccv_get_32f_value
, _ccv_get_64s_value); break; } case CCV_64F: { for_block(_ccv_get_32f_value
, _ccv_get_64f_value); break; } default: { for_block(_ccv_get_32f_value
, _ccv_get_8u_value); } } }; break; } case CCV_64S: { { switch
(((a->type) & 0xFF000)) { case CCV_32S: { for_block(_ccv_get_64s_value
, _ccv_get_32s_value); break; } case CCV_32F: { for_block(_ccv_get_64s_value
, _ccv_get_32f_value); break; } case CCV_64S: { for_block(_ccv_get_64s_value
, _ccv_get_64s_value); break; } case CCV_64F: { for_block(_ccv_get_64s_value
, _ccv_get_64f_value); break; } default: { for_block(_ccv_get_64s_value
, _ccv_get_8u_value); } } }; break; } case CCV_64F: { { switch
(((a->type) & 0xFF000)) { case CCV_32S: { for_block(_ccv_get_64f_value
, _ccv_get_32s_value); break; } case CCV_32F: { for_block(_ccv_get_64f_value
, _ccv_get_32f_value); break; } case CCV_64S: { for_block(_ccv_get_64f_value
, _ccv_get_64s_value); break; } case CCV_64F: { for_block(_ccv_get_64f_value
, _ccv_get_64f_value); break; } default: { for_block(_ccv_get_64f_value
, _ccv_get_8u_value); } } }; break; } default: { { switch (((
a->type) & 0xFF000)) { case CCV_32S: { for_block(_ccv_get_8u_value
, _ccv_get_32s_value); break; } case CCV_32F: { for_block(_ccv_get_8u_value
, _ccv_get_32f_value); break; } case CCV_64S: { for_block(_ccv_get_8u_value
, _ccv_get_64s_value); break; } case CCV_64F: { for_block(_ccv_get_8u_value
, _ccv_get_64f_value); break; } default: { for_block(_ccv_get_8u_value
, _ccv_get_8u_value); } } }; } } }
;
384#undef for_block
385 } else {
386#define for_block(_for_get_d, _for_get_a) \
387 for (i = 0; i < a->rows; i++) \
388 { \
389 for (j = 0; j < a->cols; j++) \
390 { \
391 float fdx = _for_get_d(dx_ptr, j * ch), fdy = _for_get_d(dy_ptr, j * ch); \
392 float fdu = _for_get_d(du_ptr, j * ch), fdv = _for_get_d(dv_ptr, j * ch); \
393 float adx = fabsf(fdx), ady = fabsf(fdy); \
394 float adu = fabsf(fdu), adv = fabsf(fdv); \
395 /* select the strongest ones from all the channels */ \
396 for (k = 1; k < ch; k++) \
397 { \
398 if (fabsf((float)_for_get_d(dx_ptr, j * ch + k)) > adx) \
399 { \
400 fdx = _for_get_d(dx_ptr, j * ch + k); \
401 adx = fabsf(fdx); \
402 } \
403 if (fabsf((float)_for_get_d(dy_ptr, j * ch + k)) > ady) \
404 { \
405 fdy = _for_get_d(dy_ptr, j * ch + k); \
406 ady = fabsf(fdy); \
407 } \
408 if (fabsf((float)_for_get_d(du_ptr, j * ch + k)) > adu) \
409 { \
410 fdu = _for_get_d(du_ptr, j * ch + k); \
411 adu = fabsf(fdu); \
412 } \
413 if (fabsf((float)_for_get_d(dv_ptr, j * ch + k)) > adv) \
414 { \
415 fdv = _for_get_d(dv_ptr, j * ch + k); \
416 adv = fabsf(fdv); \
417 } \
418 } \
419 dbp[0] = fdx, dbp[1] = fdy; \
420 dbp[2] = fdu, dbp[3] = fdv; \
421 dbp[4] = adx, dbp[5] = ady; \
422 dbp[6] = adu, dbp[7] = adv; \
423 _ccv_rgb_to_luv(_for_get_a(a_ptr, j * ch) / 255.0, \
424 _for_get_a(a_ptr, j * ch + 1) / 255.0, \
425 _for_get_a(a_ptr, j * ch + 2) / 255.0, \
426 dbp + 8, dbp + 9, dbp + 10); \
427 dbp += 11; \
428 } \
429 a_ptr += a->step; \
430 dx_ptr += dx->step; \
431 dy_ptr += dy->step; \
432 du_ptr += du->step; \
433 dv_ptr += dv->step; \
434 }
435 ccv_matrix_getter(dx->type, ccv_matrix_getter_a, a->type, for_block){ switch (((dx->type) & 0xFF000)) { case CCV_32S: { { switch
(((a->type) & 0xFF000)) { case CCV_32S: { for_block(_ccv_get_32s_value
, _ccv_get_32s_value); break; } case CCV_32F: { for_block(_ccv_get_32s_value
, _ccv_get_32f_value); break; } case CCV_64S: { for_block(_ccv_get_32s_value
, _ccv_get_64s_value); break; } case CCV_64F: { for_block(_ccv_get_32s_value
, _ccv_get_64f_value); break; } default: { for_block(_ccv_get_32s_value
, _ccv_get_8u_value); } } }; break; } case CCV_32F: { { switch
(((a->type) & 0xFF000)) { case CCV_32S: { for_block(_ccv_get_32f_value
, _ccv_get_32s_value); break; } case CCV_32F: { for_block(_ccv_get_32f_value
, _ccv_get_32f_value); break; } case CCV_64S: { for_block(_ccv_get_32f_value
, _ccv_get_64s_value); break; } case CCV_64F: { for_block(_ccv_get_32f_value
, _ccv_get_64f_value); break; } default: { for_block(_ccv_get_32f_value
, _ccv_get_8u_value); } } }; break; } case CCV_64S: { { switch
(((a->type) & 0xFF000)) { case CCV_32S: { for_block(_ccv_get_64s_value
, _ccv_get_32s_value); break; } case CCV_32F: { for_block(_ccv_get_64s_value
, _ccv_get_32f_value); break; } case CCV_64S: { for_block(_ccv_get_64s_value
, _ccv_get_64s_value); break; } case CCV_64F: { for_block(_ccv_get_64s_value
, _ccv_get_64f_value); break; } default: { for_block(_ccv_get_64s_value
, _ccv_get_8u_value); } } }; break; } case CCV_64F: { { switch
(((a->type) & 0xFF000)) { case CCV_32S: { for_block(_ccv_get_64f_value
, _ccv_get_32s_value); break; } case CCV_32F: { for_block(_ccv_get_64f_value
, _ccv_get_32f_value); break; } case CCV_64S: { for_block(_ccv_get_64f_value
, _ccv_get_64s_value); break; } case CCV_64F: { for_block(_ccv_get_64f_value
, _ccv_get_64f_value); break; } default: { for_block(_ccv_get_64f_value
, _ccv_get_8u_value); } } }; break; } default: { { switch (((
a->type) & 0xFF000)) { case CCV_32S: { for_block(_ccv_get_8u_value
, _ccv_get_32s_value); break; } case CCV_32F: { for_block(_ccv_get_8u_value
, _ccv_get_32f_value); break; } case CCV_64S: { for_block(_ccv_get_8u_value
, _ccv_get_64s_value); break; } case CCV_64F: { for_block(_ccv_get_8u_value
, _ccv_get_64f_value); break; } default: { for_block(_ccv_get_8u_value
, _ccv_get_8u_value); } } }; } } }
;
436#undef for_block
437 }
438 ccv_matrix_free(dx);
439 ccv_matrix_free(dy);
440 ccv_matrix_free(du);
441 ccv_matrix_free(dv);
442}
443
444#if defined(HAVE_SSE21)
445static inline void _ccv_scd_run_feature_at_sse2(float* at, int cols, ccv_scd_stump_feature_t* feature, __m128 surf[8])
446{
447 int i;
448 // extract feature
449 for (i = 0; i < 4; i++)
450 {
451 __m128 d0 = _mm_loadu_ps(at + (cols * feature->sy[i] + feature->sx[i]) * CCV_SCD_CHANNEL(11));
452 __m128 d1 = _mm_loadu_ps(at + 4 + (cols * feature->sy[i] + feature->sx[i]) * CCV_SCD_CHANNEL(11));
453 __m128 du0 = _mm_loadu_ps(at + (cols * feature->dy[i] + feature->sx[i]) * CCV_SCD_CHANNEL(11));
454 __m128 du1 = _mm_loadu_ps(at + 4 + (cols * feature->dy[i] + feature->sx[i]) * CCV_SCD_CHANNEL(11));
455 __m128 dv0 = _mm_loadu_ps(at + (cols * feature->sy[i] + feature->dx[i]) * CCV_SCD_CHANNEL(11));
456 __m128 dv1 = _mm_loadu_ps(at + 4 + (cols * feature->sy[i] + feature->dx[i]) * CCV_SCD_CHANNEL(11));
457 __m128 duv0 = _mm_loadu_ps(at + (cols * feature->dy[i] + feature->dx[i]) * CCV_SCD_CHANNEL(11));
458 __m128 duv1 = _mm_loadu_ps(at + 4 + (cols * feature->dy[i] + feature->dx[i]) * CCV_SCD_CHANNEL(11));
459 surf[i * 2] = _mm_sub_ps(_mm_add_ps(duv0, d0), _mm_add_ps(du0, dv0));
460 surf[i * 2 + 1] = _mm_sub_ps(_mm_add_ps(duv1, d1), _mm_add_ps(du1, dv1));
461 }
462 // L2Hys normalization
463 __m128 v0 = _mm_add_ps(_mm_mul_ps(surf[0], surf[0]), _mm_mul_ps(surf[1], surf[1]));
464 __m128 v1 = _mm_add_ps(_mm_mul_ps(surf[2], surf[2]), _mm_mul_ps(surf[3], surf[3]));
465 __m128 v2 = _mm_add_ps(_mm_mul_ps(surf[4], surf[4]), _mm_mul_ps(surf[5], surf[5]));
466 __m128 v3 = _mm_add_ps(_mm_mul_ps(surf[6], surf[6]), _mm_mul_ps(surf[7], surf[7]));
467 v0 = _mm_add_ps(v0, v1);
468 v2 = _mm_add_ps(v2, v3);
469 union {
470 float f[4];
471 __m128 p;
472 } vx;
473 vx.p = _mm_add_ps(v0, v2);
474 v0 = _mm_set1_ps(1.0 / (sqrtf(vx.f[0] + vx.f[1] + vx.f[2] + vx.f[3]) + 1e-6));
475 static float thlf = -2.0 / 5.65685424949; // -sqrtf(32)
476 static float thuf = 2.0 / 5.65685424949; // sqrtf(32)
477 const __m128 thl = _mm_set1_ps(thlf);
478 const __m128 thu = _mm_set1_ps(thuf);
479 for (i = 0; i < 8; i++)
480 {
481 surf[i] = _mm_mul_ps(surf[i], v0);
482 surf[i] = _mm_min_ps(surf[i], thu);
483 surf[i] = _mm_max_ps(surf[i], thl);
484 }
485 __m128 u0 = _mm_add_ps(_mm_mul_ps(surf[0], surf[0]), _mm_mul_ps(surf[1], surf[1]));
486 __m128 u1 = _mm_add_ps(_mm_mul_ps(surf[2], surf[2]), _mm_mul_ps(surf[3], surf[3]));
487 __m128 u2 = _mm_add_ps(_mm_mul_ps(surf[4], surf[4]), _mm_mul_ps(surf[5], surf[5]));
488 __m128 u3 = _mm_add_ps(_mm_mul_ps(surf[6], surf[6]), _mm_mul_ps(surf[7], surf[7]));
489 u0 = _mm_add_ps(u0, u1);
490 u2 = _mm_add_ps(u2, u3);
491 union {
492 float f[4];
493 __m128 p;
494 } ux;
495 ux.p = _mm_add_ps(u0, u2);
496 u0 = _mm_set1_ps(1.0 / (sqrtf(ux.f[0] + ux.f[1] + ux.f[2] + ux.f[3]) + 1e-6));
497 for (i = 0; i < 8; i++)
498 surf[i] = _mm_mul_ps(surf[i], u0);
499}
500#else
501static inline void _ccv_scd_run_feature_at(float* at, int cols, ccv_scd_stump_feature_t* feature, float surf[32])
502{
503 int i, j;
504 // extract feature
505 for (i = 0; i < 4; i++)
506 {
507 float* d = at + (cols * feature->sy[i] + feature->sx[i]) * CCV_SCD_CHANNEL(11);
508 float* du = at + (cols * feature->dy[i] + feature->sx[i]) * CCV_SCD_CHANNEL(11);
509 float* dv = at + (cols * feature->sy[i] + feature->dx[i]) * CCV_SCD_CHANNEL(11);
510 float* duv = at + (cols * feature->dy[i] + feature->dx[i]) * CCV_SCD_CHANNEL(11);
511 for (j = 0; j < 8; j++)
512 surf[i * 8 + j] = duv[j] - du[j] + d[j] - dv[j];
513 }
514 // L2Hys normalization
515 float v = 0;
516 for (i = 0; i < 32; i++)
517 v += surf[i] * surf[i];
518 v = 1.0 / (sqrtf(v) + 1e-6);
519 static float theta = 2.0 / 5.65685424949; // sqrtf(32)
520 float u = 0;
521 for (i = 0; i < 32; i++)
522 {
523 surf[i] = surf[i] * v;
524 surf[i] = ccv_clamp(surf[i], -theta, theta)({ typeof (-theta) _a = (-theta); typeof (theta) _b = (theta)
; typeof (surf[i]) _x = (surf[i]); (_x < _a) ? _a : ((_x >
_b) ? _b : _x); })
;
525 u += surf[i] * surf[i];
526 }
527 u = 1.0 / (sqrtf(u) + 1e-6);
528 for (i = 0; i < 32; i++)
529 surf[i] = surf[i] * u;
530}
531#endif
532
533#ifdef HAVE_GSL1
534static ccv_array_t* _ccv_scd_collect_negatives(gsl_rng* rng, ccv_size_t size, ccv_array_t* hard_mine, int total, int grayscale)
535{
536 ccv_array_t* negatives = ccv_array_new(ccv_compute_dense_matrix_size(size.height, size.width, CCV_8U | (grayscale ? CCV_C1 : CCV_C3))(((sizeof(ccv_dense_matrix_t) + 63) & -64) + (((size.width
) * _ccv_get_data_type_size[((CCV_8U | (grayscale ? CCV_C1 : CCV_C3
)) & 0xFF000) >> 12] * ((CCV_8U | (grayscale ? CCV_C1
: CCV_C3)) & 0xFFF) + 3) & -4) * (size.height))
, total, 0);
537 int i, j, k;
538 for (i = 0; i < total;)
539 {
540 FLUSH(CCV_CLI_INFO, " - collect negatives %d%% (%d / %d)", (i + 1) * 100 / total, i + 1, total)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - collect negatives %d%% (%d / %d)"
, (i + 1) * 100 / total, i + 1, total); fflush(stdout); } } while
(0)
;
541 double ratio = (double)(total - i) / hard_mine->rnum;
542 for (j = 0; j < hard_mine->rnum && i < total; j++)
543 {
544 ccv_file_info_t* file_info = (ccv_file_info_t*)ccv_array_get(hard_mine, j)((void*)(((char*)((hard_mine)->data)) + (size_t)(hard_mine
)->rsize * (size_t)(j)))
;
545 ccv_dense_matrix_t* image = 0;
546 ccv_read(file_info->filename, &image, CCV_IO_ANY_FILE | (grayscale ? CCV_IO_GRAY : CCV_IO_RGB_COLOR))ccv_read_impl(file_info->filename, &image, CCV_IO_ANY_FILE
| (grayscale ? CCV_IO_GRAY : CCV_IO_RGB_COLOR), 0, 0, 0)
;
547 if (image == 0)
548 {
549 PRINT(CCV_CLI_ERROR, "\n - %s: cannot be open, possibly corrupted\n", file_info->filename)do { if ((CCV_CLI_ERROR & ccv_cli_get_output_levels())) {
printf("\n - %s: cannot be open, possibly corrupted\n", file_info
->filename); fflush(stdout); } } while (0)
;
550 continue;
551 }
552 double max_scale_ratio = ccv_min((double)image->rows / size.height, (double)image->cols / size.width)({ typeof ((double)image->rows / size.height) _a = ((double
)image->rows / size.height); typeof ((double)image->cols
/ size.width) _b = ((double)image->cols / size.width); (_a
< _b) ? _a : _b; })
;
553 if (max_scale_ratio <= 0.5) // too small to be interesting
554 continue;
555 for (k = 0; k < ratio; k++)
556 if (k < (int)ratio || gsl_rng_uniform(rng) <= ccv_max(0.1, ratio - (int)ratio)({ typeof (0.1) _a = (0.1); typeof (ratio - (int)ratio) _b = (
ratio - (int)ratio); (_a > _b) ? _a : _b; })
)
557 {
558 FLUSH(CCV_CLI_INFO, " - collect negatives %d%% (%d / %d)", (i + 1) * 100 / total, i + 1, total)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - collect negatives %d%% (%d / %d)"
, (i + 1) * 100 / total, i + 1, total); fflush(stdout); } } while
(0)
;
559 ccv_rect_t rect;
560 double scale_ratio = gsl_rng_uniform(rng) * (max_scale_ratio - 0.5) + 0.5;
561 rect.width = ccv_min(image->cols, (int)(size.width * scale_ratio + 0.5))({ typeof (image->cols) _a = (image->cols); typeof ((int
)(size.width * scale_ratio + 0.5)) _b = ((int)(size.width * scale_ratio
+ 0.5)); (_a < _b) ? _a : _b; })
;
562 rect.height = ccv_min(image->rows, (int)(size.height * scale_ratio + 0.5))({ typeof (image->rows) _a = (image->rows); typeof ((int
)(size.height * scale_ratio + 0.5)) _b = ((int)(size.height *
scale_ratio + 0.5)); (_a < _b) ? _a : _b; })
;
563 rect.x = gsl_rng_uniform_int(rng, ccv_max(image->cols - rect.width + 1, 1)({ typeof (image->cols - rect.width + 1) _a = (image->cols
- rect.width + 1); typeof (1) _b = (1); (_a > _b) ? _a : _b
; })
);
564 rect.y = gsl_rng_uniform_int(rng, ccv_max(image->rows - rect.height + 1, 1)({ typeof (image->rows - rect.height + 1) _a = (image->
rows - rect.height + 1); typeof (1) _b = (1); (_a > _b) ? _a
: _b; })
);
565 ccv_dense_matrix_t* sliced = 0;
566 ccv_slice(image, (ccv_matrix_t**)&sliced, 0, rect.y, rect.x, rect.height, rect.width);
567 ccv_dense_matrix_t* b = 0;
568 if (size.width > rect.width)
569 ccv_resample(sliced, &b, 0, (double)size.height / (double)sliced->rows, (double)size.width / (double)sliced->cols, CCV_INTER_CUBIC);
570 else
571 ccv_resample(sliced, &b, 0, (double)size.height / (double)sliced->rows, (double)size.width / (double)sliced->cols, CCV_INTER_AREA);
572 ccv_matrix_free(sliced);
573 b->sig = 0;
574 // this leveraged the fact that because I know the ccv_dense_matrix_t is continuous in memory
575 ccv_array_push(negatives, b);
576 ccv_matrix_free(b);
577 ++i;
578 if (i >= total)
579 break;
580 }
581 ccv_matrix_free(image);
582 }
583 }
584 PRINT(CCV_CLI_INFO, "\n")do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { printf
("\n"); fflush(stdout); } } while (0)
;
585 ccv_make_array_immutable(negatives);
586 return negatives;
587}
588
589static ccv_array_t*_ccv_scd_collect_positives(ccv_size_t size, ccv_array_t* posfiles, int grayscale)
590{
591 ccv_array_t* positives = ccv_array_new(ccv_compute_dense_matrix_size(size.height, size.width, CCV_8U | (grayscale ? CCV_C1 : CCV_C3))(((sizeof(ccv_dense_matrix_t) + 63) & -64) + (((size.width
) * _ccv_get_data_type_size[((CCV_8U | (grayscale ? CCV_C1 : CCV_C3
)) & 0xFF000) >> 12] * ((CCV_8U | (grayscale ? CCV_C1
: CCV_C3)) & 0xFFF) + 3) & -4) * (size.height))
, posfiles->rnum, 0);
592 int i;
593 for (i = 0; i < posfiles->rnum; i++)
594 {
595 FLUSH(CCV_CLI_INFO, " - collect positives %d%% (%d / %d)", (i + 1) * 100 / posfiles->rnum, i + 1, posfiles->rnum)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - collect positives %d%% (%d / %d)"
, (i + 1) * 100 / posfiles->rnum, i + 1, posfiles->rnum
); fflush(stdout); } } while (0)
;
596 ccv_file_info_t* file_info = (ccv_file_info_t*)ccv_array_get(posfiles, i)((void*)(((char*)((posfiles)->data)) + (size_t)(posfiles)->
rsize * (size_t)(i)))
;
597 ccv_dense_matrix_t* a = 0;
598 ccv_read(file_info->filename, &a, CCV_IO_ANY_FILE | (grayscale ? CCV_IO_GRAY : CCV_IO_RGB_COLOR))ccv_read_impl(file_info->filename, &a, CCV_IO_ANY_FILE
| (grayscale ? CCV_IO_GRAY : CCV_IO_RGB_COLOR), 0, 0, 0)
;
599 a->sig = 0;
600 ccv_array_push(positives, a);
601 ccv_matrix_free(a);
602 }
603 PRINT(CCV_CLI_INFO, "\n")do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { printf
("\n"); fflush(stdout); } } while (0)
;
604 ccv_make_array_immutable(positives);
605 return positives;
606}
607
608static ccv_array_t* _ccv_scd_stump_features(ccv_size_t base, int range_through, int step_through, ccv_size_t size)
609{
610 ccv_array_t* features = ccv_array_new(sizeof(ccv_scd_stump_feature_t), 64, 0);
611 int x, y, w, h;
612 for (w = base.width; w <= size.width; w += range_through)
613 if (w % 4 == 0) // only allow 4:1
614 {
615 h = w / 4;
616 for (x = 0; x <= size.width - w; x += step_through)
617 for (y = 0; y <= size.height - h; y += step_through)
618 {
619 // 4x1 feature
620 ccv_scd_stump_feature_t feature;
621 feature.sx[0] = x;
622 feature.dx[0] = x + (w / 4);
623 feature.sx[1] = x + (w / 4);
624 feature.dx[1] = x + 2 * (w / 4);
625 feature.sx[2] = x + 2 * (w / 4);
626 feature.dx[2] = x + 3 * (w / 4);
627 feature.sx[3] = x + 3 * (w / 4);
628 feature.dx[3] = x + w;
629 feature.sy[0] = feature.sy[1] = feature.sy[2] = feature.sy[3] = y;
630 feature.dy[0] = feature.dy[1] = feature.dy[2] = feature.dy[3] = y + h;
631 ccv_array_push(features, &feature);
632 }
633 }
634 for (h = base.height; h <= size.height; h += range_through)
635 if (h % 4 == 0) // only allow 1:4
636 {
637 w = h / 4;
638 for (x = 0; x <= size.width - w; x += step_through)
639 for (y = 0; y <= size.height - h; y += step_through)
640 {
641 // 1x4 feature
642 ccv_scd_stump_feature_t feature;
643 feature.sx[0] = feature.sx[1] = feature.sx[2] = feature.sx[3] = x;
644 feature.dx[0] = feature.dx[1] = feature.dx[2] = feature.dx[3] = x + w;
645 feature.sy[0] = y;
646 feature.dy[0] = y + (h / 4);
647 feature.sy[1] = y + (h / 4);
648 feature.dy[1] = y + 2 * (h / 4);
649 feature.sy[2] = y + 2 * (h / 4);
650 feature.dy[2] = y + 3 * (h / 4);
651 feature.sy[3] = y + 3 * (h / 4);
652 feature.dy[3] = y + h;
653 ccv_array_push(features, &feature);
654 }
655 }
656 for (w = base.width; w <= size.width; w += range_through)
657 for (h = base.height; h <= size.height; h += range_through)
658 for (x = 0; x <= size.width - w; x += step_through)
659 for (y = 0; y <= size.height - h; y += step_through)
660 if (w % 2 == 0 && h % 2 == 0 &&
661 (w == h || w == h * 2 || w * 2 == h || w * 2 == h * 3 || w * 3 == h * 2)) // allow 1:1, 1:2, 2:1, 2:3, 3:2
662 {
663 // 2x2 feature
664 ccv_scd_stump_feature_t feature;
665 feature.sx[0] = feature.sx[1] = x;
666 feature.dx[0] = feature.dx[1] = x + (w / 2);
667 feature.sy[0] = feature.sy[2] = y;
668 feature.dy[0] = feature.dy[2] = y + (h / 2);
669 feature.sx[2] = feature.sx[3] = x + (w / 2);
670 feature.dx[2] = feature.dx[3] = x + w;
671 feature.sy[1] = feature.sy[3] = y + (h / 2);
672 feature.dy[1] = feature.dy[3] = y + h;
673 ccv_array_push(features, &feature);
674 }
675 return features;
676}
677
678typedef struct {
679 double value;
680 int index;
681} ccv_scd_value_index_t;
682
683#define more_than(s1, s2, aux) ((s1).value >= (s2).value)
684static CCV_IMPLEMENT_QSORT(_ccv_scd_value_index_sortby_value, ccv_scd_value_index_t, more_than)void _ccv_scd_value_index_sortby_value(ccv_scd_value_index_t *
array, size_t total, int aux) { int isort_thresh = 7; ccv_scd_value_index_t
t; int sp = 0; struct { ccv_scd_value_index_t *lb; ccv_scd_value_index_t
*ub; } stack[48]; if( total <= 1 ) return; stack[0].lb = array
; stack[0].ub = array + (total - 1); while( sp >= 0 ) { ccv_scd_value_index_t
* left = stack[sp].lb; ccv_scd_value_index_t* right = stack[sp
--].ub; for(;;) { int i, n = (int)(right - left) + 1, m; ccv_scd_value_index_t
* ptr; ccv_scd_value_index_t* ptr2; if( n <= isort_thresh )
{ insert_sort: for( ptr = left + 1; ptr <= right; ptr++ )
{ for( ptr2 = ptr; ptr2 > left && more_than(ptr2[
0],ptr2[-1], aux); ptr2--) (((t)) = ((ptr2[0])), ((ptr2[0])) =
((ptr2[-1])), ((ptr2[-1])) = ((t))); } break; } else { ccv_scd_value_index_t
* left0; ccv_scd_value_index_t* left1; ccv_scd_value_index_t*
right0; ccv_scd_value_index_t* right1; ccv_scd_value_index_t
* pivot; ccv_scd_value_index_t* a; ccv_scd_value_index_t* b; ccv_scd_value_index_t
* c; int swap_cnt = 0; left0 = left; right0 = right; pivot = left
+ (n/2); if( n > 40 ) { int d = n / 8; a = left, b = left
+ d, c = left + 2*d; left = more_than(*a, *b, aux) ? (more_than
(*b, *c, aux) ? b : (more_than(*a, *c, aux) ? c : a)) : (more_than
(*c, *b, aux) ? b : (more_than(*a, *c, aux) ? a : c)); a = pivot
- d, b = pivot, c = pivot + d; pivot = more_than(*a, *b, aux
) ? (more_than(*b, *c, aux) ? b : (more_than(*a, *c, aux) ? c
: a)) : (more_than(*c, *b, aux) ? b : (more_than(*a, *c, aux
) ? a : c)); a = right - 2*d, b = right - d, c = right; right
= more_than(*a, *b, aux) ? (more_than(*b, *c, aux) ? b : (more_than
(*a, *c, aux) ? c : a)) : (more_than(*c, *b, aux) ? b : (more_than
(*a, *c, aux) ? a : c)); } a = left, b = pivot, c = right; pivot
= more_than(*a, *b, aux) ? (more_than(*b, *c, aux) ? b : (more_than
(*a, *c, aux) ? c : a)) : (more_than(*c, *b, aux) ? b : (more_than
(*a, *c, aux) ? a : c)); if( pivot != left0 ) { (((t)) = ((*pivot
)), ((*pivot)) = ((*left0)), ((*left0)) = ((t))); pivot = left0
; } left = left1 = left0 + 1; right = right1 = right0; for(;;
) { while( left <= right && !more_than(*pivot, *left
, aux) ) { if( !more_than(*left, *pivot, aux) ) { if( left >
left1 ) (((t)) = ((*left1)), ((*left1)) = ((*left)), ((*left
)) = ((t))); swap_cnt = 1; left1++; } left++; } while( left <=
right && !more_than(*right, *pivot, aux) ) { if( !more_than
(*pivot, *right, aux) ) { if( right < right1 ) (((t)) = ((
*right1)), ((*right1)) = ((*right)), ((*right)) = ((t))); swap_cnt
= 1; right1--; } right--; } if( left > right ) break; (((
t)) = ((*left)), ((*left)) = ((*right)), ((*right)) = ((t)));
swap_cnt = 1; left++; right--; } if( swap_cnt == 0 ) { left =
left0, right = right0; goto insert_sort; } n = ({ typeof ((int
)(left1 - left0)) _a = ((int)(left1 - left0)); typeof ((int)(
left - left1)) _b = ((int)(left - left1)); (_a < _b) ? _a :
_b; }); for( i = 0; i < n; i++ ) (((t)) = ((left0[i])), (
(left0[i])) = ((left[i-n])), ((left[i-n])) = ((t))); n = ({ typeof
((int)(right0 - right1)) _a = ((int)(right0 - right1)); typeof
((int)(right1 - right)) _b = ((int)(right1 - right)); (_a <
_b) ? _a : _b; }); for( i = 0; i < n; i++ ) (((t)) = ((left
[i])), ((left[i])) = ((right0[i-n+1])), ((right0[i-n+1])) = (
(t))); n = (int)(left - left1); m = (int)(right1 - right); if
( n > 1 ) { if( m > 1 ) { if( n > m ) { stack[++sp].
lb = left0; stack[sp].ub = left0 + n - 1; left = right0 - m +
1, right = right0; } else { stack[++sp].lb = right0 - m + 1;
stack[sp].ub = right0; left = left0, right = left0 + n - 1; }
} else left = left0, right = left0 + n - 1; } else if( m >
1 ) left = right0 - m + 1, right = right0; else break; } } }
}
685#undef more_than
686#define less_than(s1, s2, aux) ((s1).index < (s2).index)
687static CCV_IMPLEMENT_QSORT(_ccv_scd_value_index_sortby_index, ccv_scd_value_index_t, less_than)void _ccv_scd_value_index_sortby_index(ccv_scd_value_index_t *
array, size_t total, int aux) { int isort_thresh = 7; ccv_scd_value_index_t
t; int sp = 0; struct { ccv_scd_value_index_t *lb; ccv_scd_value_index_t
*ub; } stack[48]; if( total <= 1 ) return; stack[0].lb = array
; stack[0].ub = array + (total - 1); while( sp >= 0 ) { ccv_scd_value_index_t
* left = stack[sp].lb; ccv_scd_value_index_t* right = stack[sp
--].ub; for(;;) { int i, n = (int)(right - left) + 1, m; ccv_scd_value_index_t
* ptr; ccv_scd_value_index_t* ptr2; if( n <= isort_thresh )
{ insert_sort: for( ptr = left + 1; ptr <= right; ptr++ )
{ for( ptr2 = ptr; ptr2 > left && less_than(ptr2[
0],ptr2[-1], aux); ptr2--) (((t)) = ((ptr2[0])), ((ptr2[0])) =
((ptr2[-1])), ((ptr2[-1])) = ((t))); } break; } else { ccv_scd_value_index_t
* left0; ccv_scd_value_index_t* left1; ccv_scd_value_index_t*
right0; ccv_scd_value_index_t* right1; ccv_scd_value_index_t
* pivot; ccv_scd_value_index_t* a; ccv_scd_value_index_t* b; ccv_scd_value_index_t
* c; int swap_cnt = 0; left0 = left; right0 = right; pivot = left
+ (n/2); if( n > 40 ) { int d = n / 8; a = left, b = left
+ d, c = left + 2*d; left = less_than(*a, *b, aux) ? (less_than
(*b, *c, aux) ? b : (less_than(*a, *c, aux) ? c : a)) : (less_than
(*c, *b, aux) ? b : (less_than(*a, *c, aux) ? a : c)); a = pivot
- d, b = pivot, c = pivot + d; pivot = less_than(*a, *b, aux
) ? (less_than(*b, *c, aux) ? b : (less_than(*a, *c, aux) ? c
: a)) : (less_than(*c, *b, aux) ? b : (less_than(*a, *c, aux
) ? a : c)); a = right - 2*d, b = right - d, c = right; right
= less_than(*a, *b, aux) ? (less_than(*b, *c, aux) ? b : (less_than
(*a, *c, aux) ? c : a)) : (less_than(*c, *b, aux) ? b : (less_than
(*a, *c, aux) ? a : c)); } a = left, b = pivot, c = right; pivot
= less_than(*a, *b, aux) ? (less_than(*b, *c, aux) ? b : (less_than
(*a, *c, aux) ? c : a)) : (less_than(*c, *b, aux) ? b : (less_than
(*a, *c, aux) ? a : c)); if( pivot != left0 ) { (((t)) = ((*pivot
)), ((*pivot)) = ((*left0)), ((*left0)) = ((t))); pivot = left0
; } left = left1 = left0 + 1; right = right1 = right0; for(;;
) { while( left <= right && !less_than(*pivot, *left
, aux) ) { if( !less_than(*left, *pivot, aux) ) { if( left >
left1 ) (((t)) = ((*left1)), ((*left1)) = ((*left)), ((*left
)) = ((t))); swap_cnt = 1; left1++; } left++; } while( left <=
right && !less_than(*right, *pivot, aux) ) { if( !less_than
(*pivot, *right, aux) ) { if( right < right1 ) (((t)) = ((
*right1)), ((*right1)) = ((*right)), ((*right)) = ((t))); swap_cnt
= 1; right1--; } right--; } if( left > right ) break; (((
t)) = ((*left)), ((*left)) = ((*right)), ((*right)) = ((t)));
swap_cnt = 1; left++; right--; } if( swap_cnt == 0 ) { left =
left0, right = right0; goto insert_sort; } n = ({ typeof ((int
)(left1 - left0)) _a = ((int)(left1 - left0)); typeof ((int)(
left - left1)) _b = ((int)(left - left1)); (_a < _b) ? _a :
_b; }); for( i = 0; i < n; i++ ) (((t)) = ((left0[i])), (
(left0[i])) = ((left[i-n])), ((left[i-n])) = ((t))); n = ({ typeof
((int)(right0 - right1)) _a = ((int)(right0 - right1)); typeof
((int)(right1 - right)) _b = ((int)(right1 - right)); (_a <
_b) ? _a : _b; }); for( i = 0; i < n; i++ ) (((t)) = ((left
[i])), ((left[i])) = ((right0[i-n+1])), ((right0[i-n+1])) = (
(t))); n = (int)(left - left1); m = (int)(right1 - right); if
( n > 1 ) { if( m > 1 ) { if( n > m ) { stack[++sp].
lb = left0; stack[sp].ub = left0 + n - 1; left = right0 - m +
1, right = right0; } else { stack[++sp].lb = right0 - m + 1;
stack[sp].ub = right0; left = left0, right = left0 + n - 1; }
} else left = left0, right = left0 + n - 1; } else if( m >
1 ) left = right0 - m + 1, right = right0; else break; } } }
}
688#undef less_than
689
690static float* _ccv_scd_get_surf_at(float* fv, int feature_no, int example_no, int positive_count, int negative_count)
691{
692 return fv + ((off_t)example_no + feature_no * (positive_count + negative_count)) * 32;
693}
694
695static void _ccv_scd_precompute_feature_vectors(const ccv_array_t* features, const ccv_array_t* positives, const ccv_array_t* negatives, float* fv)
696{
697 parallel_for(i, positives->rnum){ int i; for ((i) = 0; (i) < (positives->rnum); (i)++) { {
698 int j;
699 if ((i + 1) % 4031 == 1)
700 FLUSH(CCV_CLI_INFO, " - precompute feature vectors of example %d / %d over %d features", (int)(i + 1), positives->rnum + negatives->rnum, features->rnum)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - precompute feature vectors of example %d / %d over %d features"
, (int)(i + 1), positives->rnum + negatives->rnum, features
->rnum); fflush(stdout); } } while (0)
;
701 ccv_dense_matrix_t* a = (ccv_dense_matrix_t*)ccv_array_get(positives, i)((void*)(((char*)((positives)->data)) + (size_t)(positives
)->rsize * (size_t)(i)))
;
702 a->data.u8 = (unsigned char*)(a + 1);
703 ccv_dense_matrix_t* b = 0;
704 ccv_scd(a, &b, 0);
705 ccv_dense_matrix_t* sat = 0;
706 ccv_sat(b, &sat, 0, CCV_PADDING_ZERO);
707 ccv_matrix_free(b);
708 for (j = 0; j < features->rnum; j++)
709 {
710 ccv_scd_stump_feature_t* feature = (ccv_scd_stump_feature_t*)ccv_array_get(features, j)((void*)(((char*)((features)->data)) + (size_t)(features)->
rsize * (size_t)(j)))
;
711 // save to fv
712#if defined(HAVE_SSE21)
713 _ccv_scd_run_feature_at_sse2(sat->data.f32, sat->cols, feature, (__m128*)_ccv_scd_get_surf_at(fv, j, i, positives->rnum, negatives->rnum));
714#else
715 _ccv_scd_run_feature_at(sat->data.f32, sat->cols, feature, _ccv_scd_get_surf_at(fv, j, i, positives->rnum, negatives->rnum));
716#endif
717 }
718 ccv_matrix_free(sat);
719 } parallel_endfor} }
720 parallel_for(i, negatives->rnum){ int i; for ((i) = 0; (i) < (negatives->rnum); (i)++) { {
721 int j;
722 if ((i + 1) % 731 == 1 || (i + 1) == negatives->rnum)
723 FLUSH(CCV_CLI_INFO, " - precompute feature vectors of example %d / %d over %d features", (int)(i + positives->rnum + 1), positives->rnum + negatives->rnum, features->rnum)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - precompute feature vectors of example %d / %d over %d features"
, (int)(i + positives->rnum + 1), positives->rnum + negatives
->rnum, features->rnum); fflush(stdout); } } while (0)
;
724 ccv_dense_matrix_t* a = (ccv_dense_matrix_t*)ccv_array_get(negatives, i)((void*)(((char*)((negatives)->data)) + (size_t)(negatives
)->rsize * (size_t)(i)))
;
725 a->data.u8 = (unsigned char*)(a + 1);
726 ccv_dense_matrix_t* b = 0;
727 ccv_scd(a, &b, 0);
728 ccv_dense_matrix_t* sat = 0;
729 ccv_sat(b, &sat, 0, CCV_PADDING_ZERO);
730 ccv_matrix_free(b);
731 for (j = 0; j < features->rnum; j++)
732 {
733 ccv_scd_stump_feature_t* feature = (ccv_scd_stump_feature_t*)ccv_array_get(features, j)((void*)(((char*)((features)->data)) + (size_t)(features)->
rsize * (size_t)(j)))
;
734 // save to fv
735#if defined(HAVE_SSE21)
736 _ccv_scd_run_feature_at_sse2(sat->data.f32, sat->cols, feature, (__m128*)_ccv_scd_get_surf_at(fv, j, i + positives->rnum, positives->rnum, negatives->rnum));
737#else
738 _ccv_scd_run_feature_at(sat->data.f32, sat->cols, feature, _ccv_scd_get_surf_at(fv, j, i + positives->rnum, positives->rnum, negatives->rnum));
739#endif
740 }
741 ccv_matrix_free(sat);
742 } parallel_endfor} }
743}
744
745typedef struct {
746 int feature_no;
747 double C;
748 ccv_scd_value_index_t* pwidx;
749 ccv_scd_value_index_t* nwidx;
750 int positive_count;
751 int negative_count;
752 int active_positive_count;
753 int active_negative_count;
754 float* fv;
755} ccv_loss_minimize_context_t;
756
757static int _ccv_scd_stump_feature_gentle_adaboost_loss(const ccv_dense_matrix_t* x, double* f, ccv_dense_matrix_t* df, void* data)
758{
759 ccv_loss_minimize_context_t* context = (ccv_loss_minimize_context_t*)data;
760 int i, j;
761 float loss = 0;
762 float* d = df->data.f32;
763 for (i = 0; i < 32; i++)
764 {
765 loss += context->C * fabs(x->data.f32[i]);
766 d[i] = x->data.f32[i] > 0 ? context->C : -context->C;
767 }
768 d[32] = 0;
769 float* surf = _ccv_scd_get_surf_at(context->fv, context->feature_no, 0, context->positive_count, context->negative_count);
770 for (i = 0; i < context->active_positive_count; i++)
771 {
772 float* cur_surf = surf + (off_t)(context->pwidx[i].index) * 32;
773 float v = x->data.f32[32];
774 for (j = 0; j < 32; j++)
775 v += cur_surf[j] * x->data.f32[j];
776 v = expf(v);
777 float tanh = (v - 1) / (v + 1);
778 loss += context->pwidx[i].value * (1.0 - tanh) * (1.0 - tanh);
779 float dv = -8.0 * context->pwidx[i].value * v / ((1.0 + v) * (1.0 + v) * (1.0 + v));
780 for (j = 0; j < 32; j++)
781 d[j] += dv * cur_surf[j];
782 d[32] += dv;
783 }
784 for (i = 0; i < context->active_negative_count; i++)
785 {
786 float* cur_surf = surf + (off_t)(context->nwidx[i].index + context->positive_count) * 32;
787 float v = x->data.f32[32];
788 for (j = 0; j < 32; j++)
789 v += cur_surf[j] * x->data.f32[j];
790 v = expf(v);
791 float tanh = (v - 1) / (v + 1);
792 loss += context->nwidx[i].value * (-1.0 - tanh) * (-1.0 - tanh);
793 float dv = 8.0 * context->nwidx[i].value * v * v / ((1.0 + v) * (1.0 + v) * (1.0 + v));
794 for (j = 0; j < 32; j++)
795 d[j] += dv * cur_surf[j];
796 d[32] += dv;
797 }
798 f[0] = loss;
799 return 0;
800}
801
802static int _ccv_scd_weight_trimming(ccv_scd_value_index_t* idx, int count, double weight_trimming)
803{
804 int active_count = count;
805 int i;
806 double w = 0;
807 for (i = 0; i < count; i++)
808 {
809 w += idx[i].value;
810 if (w >= weight_trimming)
811 {
812 active_count = i + 1;
813 break;
814 }
815 }
816 assert(active_count > 0)((void) sizeof ((active_count > 0) ? 1 : 0), __extension__
({ if (active_count > 0) ; else __assert_fail ("active_count > 0"
, "ccv_scd.c", 816, __extension__ __PRETTY_FUNCTION__); }))
;
817 for (i = active_count; i < count; i++)
818 if (idx[i - 1].value == idx[i].value) // for exactly the same weight, we skip
819 active_count = i + 1;
820 else
821 break;
822 return active_count;
823}
824
825static void _ccv_scd_stump_feature_supervised_train(gsl_rng* rng, ccv_array_t* features, int positive_count, int negative_count, double* pw, double* nw, float* fv, double C, double weight_trimming)
826{
827 int i;
828 ccv_scd_value_index_t* pwidx = (ccv_scd_value_index_t*)ccmallocmalloc(sizeof(ccv_scd_value_index_t) * positive_count);
829 ccv_scd_value_index_t* nwidx = (ccv_scd_value_index_t*)ccmallocmalloc(sizeof(ccv_scd_value_index_t) * negative_count);
830 for (i = 0; i < positive_count; i++)
831 pwidx[i].value = pw[i], pwidx[i].index = i;
832 for (i = 0; i < negative_count; i++)
833 nwidx[i].value = nw[i], nwidx[i].index = i;
834 _ccv_scd_value_index_sortby_value(pwidx, positive_count, 0);
835 _ccv_scd_value_index_sortby_value(nwidx, negative_count, 0);
836 int active_positive_count = _ccv_scd_weight_trimming(pwidx, positive_count, weight_trimming * 0.5); // the sum of positive weights is 0.5
837 int active_negative_count = _ccv_scd_weight_trimming(nwidx, negative_count, weight_trimming * 0.5); // the sum of negative weights is 0.5
838 _ccv_scd_value_index_sortby_index(pwidx, active_positive_count, 0);
839 _ccv_scd_value_index_sortby_index(nwidx, active_negative_count, 0);
840 parallel_for(i, features->rnum){ int i; for ((i) = 0; (i) < (features->rnum); (i)++) { {
841 if ((i + 1) % 31 == 1 || (i + 1) == features->rnum)
842 FLUSH(CCV_CLI_INFO, " - supervised train feature %d / %d with logistic regression, active set {%d, %d}", (int)(i + 1), features->rnum, active_positive_count, active_negative_count)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - supervised train feature %d / %d with logistic regression, active set {%d, %d}"
, (int)(i + 1), features->rnum, active_positive_count, active_negative_count
); fflush(stdout); } } while (0)
;
843 ccv_scd_stump_feature_t* feature = (ccv_scd_stump_feature_t*)ccv_array_get(features, i)((void*)(((char*)((features)->data)) + (size_t)(features)->
rsize * (size_t)(i)))
;
844 ccv_loss_minimize_context_t context = {
845 .feature_no = i,
846 .C = C,
847 .positive_count = positive_count,
848 .negative_count = negative_count,
849 .active_positive_count = active_positive_count,
850 .active_negative_count = active_negative_count,
851 .pwidx = pwidx,
852 .nwidx = nwidx,
853 .fv = fv,
854 };
855 ccv_dense_matrix_t* x = ccv_dense_matrix_new(1, 33, CCV_32F | CCV_C1, 0, 0);
856 int j;
857 for (j = 0; j < 33; j++)
858 x->data.f32[j] = gsl_rng_uniform_pos(rng) * 2 - 1.0;
859 ccv_minimize(x, 10, 1.0, _ccv_scd_stump_feature_gentle_adaboost_loss, ccv_minimize_default_params, &context);
860 for (j = 0; j < 32; j++)
861 feature->w[j] = x->data.f32[j];
862 feature->bias = x->data.f32[32];
863 ccv_matrix_free(x);
864 } parallel_endfor} }
865 ccfreefree(pwidx);
866 ccfreefree(nwidx);
867}
868
869static double _ccv_scd_auc(double* s, int posnum, int negnum)
870{
871 ccv_scd_value_index_t* sidx = (ccv_scd_value_index_t*)ccmallocmalloc(sizeof(ccv_scd_value_index_t) * (posnum + negnum));
872 int i;
873 for (i = 0; i < posnum + negnum; i++)
874 sidx[i].value = s[i], sidx[i].index = i;
875 _ccv_scd_value_index_sortby_value(sidx, posnum + negnum, 0);
876 int fp = 0, tp = 0, fp_prev = 0, tp_prev = 0;
877 double a = 0;
878 double f_prev = -DBL_MAX1.7976931348623157e+308;
879 for (i = 0; i < posnum + negnum; i++)
880 {
881 if (sidx[i].value != f_prev)
882 {
883 a += (double)(fp - fp_prev) * (tp + tp_prev) * 0.5;
884 f_prev = sidx[i].value;
885 fp_prev = fp;
886 tp_prev = tp;
887 }
888 if (sidx[i].index < posnum)
889 ++tp;
890 else
891 ++fp;
892 }
893 ccfreefree(sidx);
894 a += (double)(negnum - fp_prev) * (posnum + tp_prev) * 0.5;
895 return a / ((double)posnum * negnum);
896}
897
898static int _ccv_scd_find_match_feature(ccv_scd_stump_feature_t* value, ccv_array_t* features)
899{
900 int i;
901 for (i = 0; i < features->rnum; i++)
902 {
903 ccv_scd_stump_feature_t* feature = (ccv_scd_stump_feature_t*)ccv_array_get(features, i)((void*)(((char*)((features)->data)) + (size_t)(features)->
rsize * (size_t)(i)))
;
904 if (feature->sx[0] == value->sx[0] && feature->sy[0] == value->sy[0] &&
905 feature->dx[0] == value->dx[0] && feature->dy[0] == value->dy[0] &&
906 feature->sx[1] == value->sx[1] && feature->sy[1] == value->sy[1] &&
907 feature->dx[1] == value->dx[1] && feature->dy[1] == value->dy[1] &&
908 feature->sx[2] == value->sx[2] && feature->sy[2] == value->sy[2] &&
909 feature->dx[2] == value->dx[2] && feature->dy[2] == value->dy[2] &&
910 feature->sx[3] == value->sx[3] && feature->sy[3] == value->sy[3] &&
911 feature->dx[3] == value->dx[3] && feature->dy[3] == value->dy[3])
912 return i;
913 }
914 return -1;
915}
916
917static int _ccv_scd_best_feature_gentle_adaboost(double* s, ccv_array_t* features, double* pw, double* nw, int positive_count, int negative_count, float* fv)
918{
919 int i;
920 double* error_rate = (double*)cccalloccalloc(features->rnum, sizeof(double));
921 assert(positive_count + negative_count > 0)((void) sizeof ((positive_count + negative_count > 0) ? 1 :
0), __extension__ ({ if (positive_count + negative_count >
0) ; else __assert_fail ("positive_count + negative_count > 0"
, "ccv_scd.c", 921, __extension__ __PRETTY_FUNCTION__); }))
;
922 parallel_for(i, features->rnum){ int i; for ((i) = 0; (i) < (features->rnum); (i)++) { {
923 int j, k;
924 if ((i + 1) % 331 == 1 || (i + 1) == features->rnum)
925 FLUSH(CCV_CLI_INFO, " - go through %d / %d (%.1f%%) for adaboost", (int)(i + 1), features->rnum, (float)(i + 1) * 100 / features->rnum)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - go through %d / %d (%.1f%%) for adaboost"
, (int)(i + 1), features->rnum, (float)(i + 1) * 100 / features
->rnum); fflush(stdout); } } while (0)
;
926 ccv_scd_stump_feature_t* feature = (ccv_scd_stump_feature_t*)ccv_array_get(features, i)((void*)(((char*)((features)->data)) + (size_t)(features)->
rsize * (size_t)(i)))
;
927 for (j = 0; j < positive_count; j++)
928 {
929 float* surf = _ccv_scd_get_surf_at(fv, i, j, positive_count, negative_count);
930 float v = feature->bias;
931 for (k = 0; k < 32; k++)
932 v += surf[k] * feature->w[k];
933 v = expf(v);
934 v = (v - 1) / (v + 1); // probability
935 error_rate[i] += pw[j] * (1 - v) * (1 - v);
936 }
937 for (j = 0; j < negative_count; j++)
938 {
939 float* surf = _ccv_scd_get_surf_at(fv, i, j + positive_count, positive_count, negative_count);
940 float v = feature->bias;
941 for (k = 0; k < 32; k++)
942 v += surf[k] * feature->w[k];
943 v = expf(v);
944 v = (v - 1) / (v + 1); // probability
945 error_rate[i] += nw[j] * (-1 - v) * (-1 - v);
946 }
947 } parallel_endfor} }
948 double min_error_rate = error_rate[0];
949 int j = 0;
950 for (i = 1; i < features->rnum; i++)
951 if (error_rate[i] < min_error_rate)
952 {
953 min_error_rate = error_rate[i];
954 j = i;
955 }
956 ccfreefree(error_rate);
957 return j;
958}
959
960static float _ccv_scd_threshold_at_hit_rate(double* s, int posnum, int negnum, float hit_rate, float* tp_out, float* fp_out)
961{
962 ccv_scd_value_index_t* psidx = (ccv_scd_value_index_t*)ccmallocmalloc(sizeof(ccv_scd_value_index_t) * posnum);
963 int i;
964 for (i = 0; i < posnum; i++)
965 psidx[i].value = s[i], psidx[i].index = i;
966 _ccv_scd_value_index_sortby_value(psidx, posnum, 0);
967 float threshold = psidx[(int)((posnum - 0.5) * hit_rate - 0.5)].value - 1e-6;
968 ccfreefree(psidx);
969 int tp = 0;
970 for (i = 0; i < posnum; i++)
971 if (s[i] > threshold)
972 ++tp;
973 int fp = 0;
974 for (i = 0; i < negnum; i++)
975 if (s[i + posnum] > threshold)
976 ++fp;
977 if (tp_out)
978 *tp_out = (float)tp / posnum;
979 if (fp_out)
980 *fp_out = (float)fp / negnum;
981 return threshold;
982}
983
984static int _ccv_scd_classifier_cascade_pass(ccv_scd_classifier_cascade_t* cascade, ccv_dense_matrix_t* a)
985{
986#if defined(HAVE_SSE21)
987 __m128 surf[8];
988#else
989 float surf[32];
990#endif
991 ccv_dense_matrix_t* b = 0;
992 ccv_scd(a, &b, 0);
993 ccv_dense_matrix_t* sat = 0;
994 ccv_sat(b, &sat, 0, CCV_PADDING_ZERO);
995 ccv_matrix_free(b);
996 int pass = 1;
997 int i, j;
998 for (i = 0; i < cascade->count; i++)
999 {
1000 ccv_scd_stump_classifier_t* classifier = cascade->classifiers + i;
1001 float v = 0;
1002 for (j = 0; j < classifier->count; j++)
1003 {
1004 ccv_scd_stump_feature_t* feature = classifier->features + j;
1005#if defined(HAVE_SSE21)
1006 _ccv_scd_run_feature_at_sse2(sat->data.f32, sat->cols, feature, surf);
1007 __m128 u0 = _mm_add_ps(_mm_mul_ps(surf[0], _mm_loadu_ps(feature->w)), _mm_mul_ps(surf[1], _mm_loadu_ps(feature->w + 4)));
1008 __m128 u1 = _mm_add_ps(_mm_mul_ps(surf[2], _mm_loadu_ps(feature->w + 8)), _mm_mul_ps(surf[3], _mm_loadu_ps(feature->w + 12)));
1009 __m128 u2 = _mm_add_ps(_mm_mul_ps(surf[4], _mm_loadu_ps(feature->w + 16)), _mm_mul_ps(surf[5], _mm_loadu_ps(feature->w + 20)));
1010 __m128 u3 = _mm_add_ps(_mm_mul_ps(surf[6], _mm_loadu_ps(feature->w + 24)), _mm_mul_ps(surf[7], _mm_loadu_ps(feature->w + 28)));
1011 u0 = _mm_add_ps(u0, u1);
1012 u2 = _mm_add_ps(u2, u3);
1013 union {
1014 float f[4];
1015 __m128 p;
1016 } ux;
1017 ux.p = _mm_add_ps(u0, u2);
1018 float u = expf(feature->bias + ux.f[0] + ux.f[1] + ux.f[2] + ux.f[3]);
1019#else
1020 _ccv_scd_run_feature_at(sat->data.f32, sat->cols, feature, surf);
1021 float u = feature->bias;
1022 int k;
1023 for (k = 0; k < 32; k++)
1024 u += surf[k] * feature->w[k];
1025 u = expf(u);
1026#endif
1027 v += (u - 1) / (u + 1);
1028 }
1029 if (v <= classifier->threshold)
1030 {
1031 pass = 0;
1032 break;
1033 }
1034 }
1035 ccv_matrix_free(sat);
1036 return pass;
1037}
1038
1039static ccv_array_t* _ccv_scd_hard_mining(gsl_rng* rng, ccv_scd_classifier_cascade_t* cascade, ccv_array_t* hard_mine, ccv_array_t* negatives, int negative_count, int grayscale, int even_dist)
1040{
1041 ccv_array_t* hard_negatives = ccv_array_new(ccv_compute_dense_matrix_size(cascade->size.height, cascade->size.width, CCV_8U | (grayscale ? CCV_C1 : CCV_C3))(((sizeof(ccv_dense_matrix_t) + 63) & -64) + (((cascade->
size.width) * _ccv_get_data_type_size[((CCV_8U | (grayscale ?
CCV_C1 : CCV_C3)) & 0xFF000) >> 12] * ((CCV_8U | (
grayscale ? CCV_C1 : CCV_C3)) & 0xFFF) + 3) & -4) * (
cascade->size.height))
, negative_count, 0);
1042 int i, j, t;
1043 for (i = 0; i < negatives->rnum; i++)
1044 {
1045 ccv_dense_matrix_t* a = (ccv_dense_matrix_t*)ccv_array_get(negatives, i)((void*)(((char*)((negatives)->data)) + (size_t)(negatives
)->rsize * (size_t)(i)))
;
1046 a->data.u8 = (unsigned char*)(a + 1);
1047 if (_ccv_scd_classifier_cascade_pass(cascade, a))
1048 ccv_array_push(hard_negatives, a);
1049 }
1050 int n_per_mine = ccv_max((negative_count - hard_negatives->rnum) / hard_mine->rnum, 10)({ typeof ((negative_count - hard_negatives->rnum) / hard_mine
->rnum) _a = ((negative_count - hard_negatives->rnum) /
hard_mine->rnum); typeof (10) _b = (10); (_a > _b) ? _a
: _b; })
;
1051 // the hard mining comes in following fashion:
1052 // 1). original, with n_per_mine set;
1053 // 2). horizontal flip, with n_per_mine set;
1054 // 3). vertical flip, with n_per_mine set;
1055 // 4). 180 rotation, with n_per_mine set;
1056 // 5~8). repeat above, but with no n_per_mine set;
1057 // after above, if we still cannot collect enough, so be it.
1058 for (t = (even_dist ? 0 : 4); t < 8 /* exhausted all variations */ && hard_negatives->rnum < negative_count; t++)
1059 {
1060 for (i = 0; i < hard_mine->rnum; i++)
1061 {
1062 FLUSH(CCV_CLI_INFO, " - hard mine negatives %d%% with %d-th permutation", 100 * hard_negatives->rnum / negative_count, t + 1)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - hard mine negatives %d%% with %d-th permutation"
, 100 * hard_negatives->rnum / negative_count, t + 1); fflush
(stdout); } } while (0)
;
1063 ccv_file_info_t* file_info = (ccv_file_info_t*)ccv_array_get(hard_mine, i)((void*)(((char*)((hard_mine)->data)) + (size_t)(hard_mine
)->rsize * (size_t)(i)))
;
1064 ccv_dense_matrix_t* image = 0;
1065 ccv_read(file_info->filename, &image, CCV_IO_ANY_FILE | (grayscale ? CCV_IO_GRAY : CCV_IO_RGB_COLOR))ccv_read_impl(file_info->filename, &image, CCV_IO_ANY_FILE
| (grayscale ? CCV_IO_GRAY : CCV_IO_RGB_COLOR), 0, 0, 0)
;
1066 if (image == 0)
1067 {
1068 PRINT(CCV_CLI_ERROR, "\n - %s: cannot be open, possibly corrupted\n", file_info->filename)do { if ((CCV_CLI_ERROR & ccv_cli_get_output_levels())) {
printf("\n - %s: cannot be open, possibly corrupted\n", file_info
->filename); fflush(stdout); } } while (0)
;
1069 continue;
1070 }
1071 if (t % 2 != 0)
1072 ccv_flip(image, 0, 0, CCV_FLIP_X);
1073 if (t % 4 >= 2)
1074 ccv_flip(image, 0, 0, CCV_FLIP_Y);
1075 if (t >= 4)
1076 n_per_mine = negative_count; // no hard limit on n_per_mine anymore for the last pass
1077 ccv_scd_param_t params = {
1078 .interval = 3,
1079 .min_neighbors = 0,
1080 .step_through = 4,
1081 .size = cascade->size,
1082 };
1083 ccv_array_t* objects = ccv_scd_detect_objects(image, &cascade, 1, params);
1084 if (objects->rnum > 0)
1085 {
1086 gsl_ran_shuffle(rng, objects->data, objects->rnum, objects->rsize);
1087 for (j = 0; j < ccv_min(objects->rnum, n_per_mine)({ typeof (objects->rnum) _a = (objects->rnum); typeof (
n_per_mine) _b = (n_per_mine); (_a < _b) ? _a : _b; })
; j++)
1088 {
1089 ccv_rect_t* rect = (ccv_rect_t*)ccv_array_get(objects, j)((void*)(((char*)((objects)->data)) + (size_t)(objects)->
rsize * (size_t)(j)))
;
1090 if (rect->x < 0 || rect->y < 0 || rect->x + rect->width > image->cols || rect->y + rect->height > image->rows)
1091 continue;
1092 ccv_dense_matrix_t* sliced = 0;
1093 ccv_slice(image, (ccv_matrix_t**)&sliced, 0, rect->y, rect->x, rect->height, rect->width);
1094 ccv_dense_matrix_t* resized = 0;
1095 assert(sliced->rows >= cascade->size.height && sliced->cols >= cascade->size.width)((void) sizeof ((sliced->rows >= cascade->size.height
&& sliced->cols >= cascade->size.width) ? 1
: 0), __extension__ ({ if (sliced->rows >= cascade->
size.height && sliced->cols >= cascade->size
.width) ; else __assert_fail ("sliced->rows >= cascade->size.height && sliced->cols >= cascade->size.width"
, "ccv_scd.c", 1095, __extension__ __PRETTY_FUNCTION__); }))
;
1096 if (sliced->rows > cascade->size.height || sliced->cols > cascade->size.width)
1097 {
1098 ccv_resample(sliced, &resized, 0, (double)cascade->size.height / (double)sliced->rows, (double)cascade->size.width / (double)sliced->cols, CCV_INTER_CUBIC);
1099 ccv_matrix_free(sliced);
1100 } else {
1101 resized = sliced;
1102 }
1103 if (_ccv_scd_classifier_cascade_pass(cascade, resized))
1104 ccv_array_push(hard_negatives, resized);
1105 ccv_matrix_free(resized);
1106 if (hard_negatives->rnum >= negative_count)
1107 break;
1108 }
1109 }
1110 ccv_matrix_free(image);
1111 if (hard_negatives->rnum >= negative_count)
1112 break;
1113 }
1114 }
1115 FLUSH(CCV_CLI_INFO, " - hard mine negatives : %d\n", hard_negatives->rnum)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - hard mine negatives : %d\n"
, hard_negatives->rnum); fflush(stdout); } } while (0)
;
1116 ccv_make_array_immutable(hard_negatives);
1117 return hard_negatives;
1118}
1119
1120typedef struct {
1121 ccv_function_state_reserve_fieldint line_no;;
1122 int t, k;
1123 uint64_t array_signature;
1124 ccv_array_t* features;
1125 ccv_array_t* positives;
1126 ccv_array_t* negatives;
1127 double* s;
1128 double* pw;
1129 double* nw;
1130 float* fv; // feature vector for examples * feature
1131 double auc_prev;
1132 double accu_true_positive_rate;
1133 double accu_false_positive_rate;
1134 ccv_scd_classifier_cascade_t* cascade;
1135 ccv_scd_train_param_t params;
1136} ccv_scd_classifier_cascade_new_function_state_t;
1137
1138static void _ccv_scd_classifier_cascade_new_function_state_read(const char* filename, ccv_scd_classifier_cascade_new_function_state_t* z)
1139{
1140 ccv_scd_classifier_cascade_t* cascade = ccv_scd_classifier_cascade_read(filename);
17
Calling 'ccv_scd_classifier_cascade_read'
30
Returned allocated memory
1141 if (!cascade
30.1
'cascade' is non-null
)
31
Taking false branch
1142 return;
1143 if (z->cascade)
32
Assuming field 'cascade' is non-null
33
Taking true branch
1144 ccv_scd_classifier_cascade_free(z->cascade);
1145 z->cascade = cascade;
1146 assert(z->cascade->size.width == z->params.size.width)((void) sizeof ((z->cascade->size.width == z->params
.size.width) ? 1 : 0), __extension__ ({ if (z->cascade->
size.width == z->params.size.width) ; else __assert_fail (
"z->cascade->size.width == z->params.size.width", "ccv_scd.c"
, 1146, __extension__ __PRETTY_FUNCTION__); }))
;
34
Assuming 'z->cascade->size.width' is equal to 'z->params.size.width'
35
Taking true branch
1147 assert(z->cascade->size.height == z->params.size.height)((void) sizeof ((z->cascade->size.height == z->params
.size.height) ? 1 : 0), __extension__ ({ if (z->cascade->
size.height == z->params.size.height) ; else __assert_fail
("z->cascade->size.height == z->params.size.height"
, "ccv_scd.c", 1147, __extension__ __PRETTY_FUNCTION__); }))
;
36
Assuming 'z->cascade->size.height' is equal to 'z->params.size.height'
37
Taking true branch
1148 sqlite3* db = 0;
1149 if (SQLITE_OK0 == sqlite3_open(filename, &db))
38
Assuming the condition is false
39
Taking false branch
1150 {
1151 const char negative_data_qs[] =
1152 "SELECT data, rnum, rsize FROM negative_data WHERE id=0;";
1153 sqlite3_stmt* negative_data_stmt = 0;
1154 if (SQLITE_OK0 == sqlite3_prepare_v2(db, negative_data_qs, sizeof(negative_data_qs), &negative_data_stmt, 0))
1155 {
1156 if (sqlite3_step(negative_data_stmt) == SQLITE_ROW100)
1157 {
1158 int rsize = ccv_compute_dense_matrix_size(z->cascade->size.height, z->cascade->size.width, CCV_8U | (z->params.grayscale ? CCV_C1 : CCV_C3))(((sizeof(ccv_dense_matrix_t) + 63) & -64) + (((z->cascade
->size.width) * _ccv_get_data_type_size[((CCV_8U | (z->
params.grayscale ? CCV_C1 : CCV_C3)) & 0xFF000) >> 12
] * ((CCV_8U | (z->params.grayscale ? CCV_C1 : CCV_C3)) &
0xFFF) + 3) & -4) * (z->cascade->size.height))
;
1159 int rnum = sqlite3_column_int(negative_data_stmt, 1);
1160 assert(sqlite3_column_int(negative_data_stmt, 2) == rsize)((void) sizeof ((sqlite3_column_int(negative_data_stmt, 2) ==
rsize) ? 1 : 0), __extension__ ({ if (sqlite3_column_int(negative_data_stmt
, 2) == rsize) ; else __assert_fail ("sqlite3_column_int(negative_data_stmt, 2) == rsize"
, "ccv_scd.c", 1160, __extension__ __PRETTY_FUNCTION__); }))
;
1161 size_t size = sqlite3_column_bytes(negative_data_stmt, 0);
1162 assert(size == (size_t)rsize * rnum)((void) sizeof ((size == (size_t)rsize * rnum) ? 1 : 0), __extension__
({ if (size == (size_t)rsize * rnum) ; else __assert_fail ("size == (size_t)rsize * rnum"
, "ccv_scd.c", 1162, __extension__ __PRETTY_FUNCTION__); }))
;
1163 if (z->negatives)
1164 ccv_array_clear(z->negatives);
1165 else
1166 z->negatives = ccv_array_new(rsize, rnum, 0);
1167 int i;
1168 const uint8_t* data = (const uint8_t*)sqlite3_column_blob(negative_data_stmt, 0);
1169 for (i = 0; i < rnum; i++)
1170 ccv_array_push(z->negatives, data + (off_t)i * rsize);
1171 ccv_make_array_immutable(z->negatives);
1172 z->array_signature = z->negatives->sig;
1173 }
1174 sqlite3_finalize(negative_data_stmt);
1175 }
1176 const char function_state_qs[] =
1177 "SELECT t, k, positive_count, auc_prev, " // 4
1178 "accu_true_positive_rate, accu_false_positive_rate, " // 6
1179 "line_no, s, pw, nw FROM function_state WHERE fsid = 0;"; // 10
1180 sqlite3_stmt* function_state_stmt = 0;
1181 if (SQLITE_OK0 == sqlite3_prepare_v2(db, function_state_qs, sizeof(function_state_qs), &function_state_stmt, 0))
1182 {
1183 if (sqlite3_step(function_state_stmt) == SQLITE_ROW100)
1184 {
1185 z->t = sqlite3_column_int(function_state_stmt, 0);
1186 z->k = sqlite3_column_int(function_state_stmt, 1);
1187 int positive_count = sqlite3_column_int(function_state_stmt, 2);
1188 assert(positive_count == z->positives->rnum)((void) sizeof ((positive_count == z->positives->rnum) ?
1 : 0), __extension__ ({ if (positive_count == z->positives
->rnum) ; else __assert_fail ("positive_count == z->positives->rnum"
, "ccv_scd.c", 1188, __extension__ __PRETTY_FUNCTION__); }))
;
1189 z->auc_prev = sqlite3_column_double(function_state_stmt, 3);
1190 z->accu_true_positive_rate = sqlite3_column_double(function_state_stmt, 4);
1191 z->accu_false_positive_rate = sqlite3_column_double(function_state_stmt, 5);
1192 z->line_no = sqlite3_column_int(function_state_stmt, 6);
1193 size_t size = sqlite3_column_bytes(function_state_stmt, 7);
1194 const void* s = sqlite3_column_blob(function_state_stmt, 7);
1195 memcpy(z->s, s, size);
1196 size = sqlite3_column_bytes(function_state_stmt, 8);
1197 const void* pw = sqlite3_column_blob(function_state_stmt, 8);
1198 memcpy(z->pw, pw, size);
1199 size = sqlite3_column_bytes(function_state_stmt, 9);
1200 const void* nw = sqlite3_column_blob(function_state_stmt, 9);
1201 memcpy(z->nw, nw, size);
1202 }
1203 sqlite3_finalize(function_state_stmt);
1204 }
1205 _ccv_scd_precompute_feature_vectors(z->features, z->positives, z->negatives, z->fv);
1206 sqlite3_close(db);
1207 }
1208}
1209
1210static void _ccv_scd_classifier_cascade_new_function_state_write(ccv_scd_classifier_cascade_new_function_state_t* z, const char* filename)
1211{
1212 ccv_scd_classifier_cascade_write(z->cascade, filename);
1213 sqlite3* db = 0;
1214 if (SQLITE_OK0 == sqlite3_open(filename, &db))
1215 {
1216 const char function_state_create_table_qs[] =
1217 "CREATE TABLE IF NOT EXISTS function_state "
1218 "(fsid INTEGER PRIMARY KEY ASC, t INTEGER, k INTEGER, positive_count INTEGER, auc_prev DOUBLE, accu_true_positive_rate DOUBLE, accu_false_positive_rate DOUBLE, line_no INTEGER, s BLOB, pw BLOB, nw BLOB);"
1219 "CREATE TABLE IF NOT EXISTS negative_data "
1220 "(id INTEGER PRIMARY KEY ASC, data BLOB, rnum INTEGER, rsize INTEGER);";
1221 assert(SQLITE_OK == sqlite3_exec(db, function_state_create_table_qs, 0, 0, 0))((void) sizeof ((0 == sqlite3_exec(db, function_state_create_table_qs
, 0, 0, 0)) ? 1 : 0), __extension__ ({ if (0 == sqlite3_exec(
db, function_state_create_table_qs, 0, 0, 0)) ; else __assert_fail
("SQLITE_OK == sqlite3_exec(db, function_state_create_table_qs, 0, 0, 0)"
, "ccv_scd.c", 1221, __extension__ __PRETTY_FUNCTION__); }))
;
1222 const char function_state_insert_qs[] =
1223 "REPLACE INTO function_state "
1224 "(fsid, t, k, positive_count, auc_prev, accu_true_positive_rate, accu_false_positive_rate, line_no, s, pw, nw) VALUES "
1225 "(0, $t, $k, $positive_count, $auc_prev, $accu_true_positive_rate, $accu_false_positive_rate, $line_no, $s, $pw, $nw);";
1226 sqlite3_stmt* function_state_insert_stmt = 0;
1227 assert(SQLITE_OK == sqlite3_prepare_v2(db, function_state_insert_qs, sizeof(function_state_insert_qs), &function_state_insert_stmt, 0))((void) sizeof ((0 == sqlite3_prepare_v2(db, function_state_insert_qs
, sizeof(function_state_insert_qs), &function_state_insert_stmt
, 0)) ? 1 : 0), __extension__ ({ if (0 == sqlite3_prepare_v2(
db, function_state_insert_qs, sizeof(function_state_insert_qs
), &function_state_insert_stmt, 0)) ; else __assert_fail (
"SQLITE_OK == sqlite3_prepare_v2(db, function_state_insert_qs, sizeof(function_state_insert_qs), &function_state_insert_stmt, 0)"
, "ccv_scd.c", 1227, __extension__ __PRETTY_FUNCTION__); }))
;
1228 sqlite3_bind_int(function_state_insert_stmt, 1, z->t);
1229 sqlite3_bind_int(function_state_insert_stmt, 2, z->k);
1230 sqlite3_bind_int(function_state_insert_stmt, 3, z->positives->rnum);
1231 sqlite3_bind_double(function_state_insert_stmt, 4, z->auc_prev);
1232 sqlite3_bind_double(function_state_insert_stmt, 5, z->accu_true_positive_rate);
1233 sqlite3_bind_double(function_state_insert_stmt, 6, z->accu_false_positive_rate);
1234 sqlite3_bind_int(function_state_insert_stmt, 7, z->line_no);
1235 sqlite3_bind_blob(function_state_insert_stmt, 8, z->s, sizeof(double) * (z->positives->rnum + z->negatives->rnum), SQLITE_STATIC((sqlite3_destructor_type)0));
1236 sqlite3_bind_blob(function_state_insert_stmt, 9, z->pw, sizeof(double) * z->positives->rnum, SQLITE_STATIC((sqlite3_destructor_type)0));
1237 sqlite3_bind_blob(function_state_insert_stmt, 10, z->nw, sizeof(double) * z->negatives->rnum, SQLITE_STATIC((sqlite3_destructor_type)0));
1238 assert(SQLITE_DONE == sqlite3_step(function_state_insert_stmt))((void) sizeof ((101 == sqlite3_step(function_state_insert_stmt
)) ? 1 : 0), __extension__ ({ if (101 == sqlite3_step(function_state_insert_stmt
)) ; else __assert_fail ("SQLITE_DONE == sqlite3_step(function_state_insert_stmt)"
, "ccv_scd.c", 1238, __extension__ __PRETTY_FUNCTION__); }))
;
1239 sqlite3_finalize(function_state_insert_stmt);
1240 if (z->array_signature != z->negatives->sig)
1241 {
1242 const char negative_data_insert_qs[] =
1243 "REPLACE INTO negative_data "
1244 "(id, data, rnum, rsize) VALUES (0, $data, $rnum, $rsize);";
1245 sqlite3_stmt* negative_data_insert_stmt = 0;
1246 assert(SQLITE_OK == sqlite3_prepare_v2(db, negative_data_insert_qs, sizeof(negative_data_insert_qs), &negative_data_insert_stmt, 0))((void) sizeof ((0 == sqlite3_prepare_v2(db, negative_data_insert_qs
, sizeof(negative_data_insert_qs), &negative_data_insert_stmt
, 0)) ? 1 : 0), __extension__ ({ if (0 == sqlite3_prepare_v2(
db, negative_data_insert_qs, sizeof(negative_data_insert_qs),
&negative_data_insert_stmt, 0)) ; else __assert_fail ("SQLITE_OK == sqlite3_prepare_v2(db, negative_data_insert_qs, sizeof(negative_data_insert_qs), &negative_data_insert_stmt, 0)"
, "ccv_scd.c", 1246, __extension__ __PRETTY_FUNCTION__); }))
;
1247 sqlite3_bind_blob(negative_data_insert_stmt, 1, z->negatives->data, z->negatives->rsize * z->negatives->rnum, SQLITE_STATIC((sqlite3_destructor_type)0));
1248 sqlite3_bind_int(negative_data_insert_stmt, 2, z->negatives->rnum);
1249 sqlite3_bind_int(negative_data_insert_stmt, 3, z->negatives->rsize);
1250 assert(SQLITE_DONE == sqlite3_step(negative_data_insert_stmt))((void) sizeof ((101 == sqlite3_step(negative_data_insert_stmt
)) ? 1 : 0), __extension__ ({ if (101 == sqlite3_step(negative_data_insert_stmt
)) ; else __assert_fail ("SQLITE_DONE == sqlite3_step(negative_data_insert_stmt)"
, "ccv_scd.c", 1250, __extension__ __PRETTY_FUNCTION__); }))
;
1251 sqlite3_finalize(negative_data_insert_stmt);
1252 z->array_signature = z->negatives->sig;
1253 }
1254 sqlite3_close(db);
1255 }
1256}
1257#endif
1258
1259ccv_scd_classifier_cascade_t* ccv_scd_classifier_cascade_new(ccv_array_t* posfiles, ccv_array_t* hard_mine, int negative_count, const char* filename, ccv_scd_train_param_t params)
1260{
1261#ifdef HAVE_GSL1
1262 assert(posfiles->rnum > 0)((void) sizeof ((posfiles->rnum > 0) ? 1 : 0), __extension__
({ if (posfiles->rnum > 0) ; else __assert_fail ("posfiles->rnum > 0"
, "ccv_scd.c", 1262, __extension__ __PRETTY_FUNCTION__); }))
;
1
Assuming field 'rnum' is > 0
2
Taking true branch
1263 assert(hard_mine->rnum > 0)((void) sizeof ((hard_mine->rnum > 0) ? 1 : 0), __extension__
({ if (hard_mine->rnum > 0) ; else __assert_fail ("hard_mine->rnum > 0"
, "ccv_scd.c", 1263, __extension__ __PRETTY_FUNCTION__); }))
;
3
Assuming field 'rnum' is > 0
4
Taking true branch
1264 gsl_rng_env_setup();
1265 gsl_rng* rng = gsl_rng_alloc(gsl_rng_default);
1266 ccv_scd_classifier_cascade_new_function_state_t z = {0};
1267 z.features = _ccv_scd_stump_features(params.feature.base, params.feature.range_through, params.feature.step_through, params.size);
1268 PRINT(CCV_CLI_INFO, " - using %d features\n", z.features->rnum)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { printf
(" - using %d features\n", z.features->rnum); fflush(stdout
); } } while (0)
;
5
Assuming the condition is false
6
Taking false branch
7
Loop condition is false. Exiting loop
1269 int i, j, p, q;
1270 z.positives = _ccv_scd_collect_positives(params.size, posfiles, params.grayscale);
1271 double* h = (double*)ccmallocmalloc(sizeof(double) * (z.positives->rnum + negative_count));
1272 z.s = (double*)ccmallocmalloc(sizeof(double) * (z.positives->rnum + negative_count));
1273 assert(z.s)((void) sizeof ((z.s) ? 1 : 0), __extension__ ({ if (z.s) ; else
__assert_fail ("z.s", "ccv_scd.c", 1273, __extension__ __PRETTY_FUNCTION__
); }))
;
8
Assuming field 's' is non-null
9
Taking true branch
1274 z.pw = (double*)ccmallocmalloc(sizeof(double) * z.positives->rnum);
1275 assert(z.pw)((void) sizeof ((z.pw) ? 1 : 0), __extension__ ({ if (z.pw) ;
else __assert_fail ("z.pw", "ccv_scd.c", 1275, __extension__
__PRETTY_FUNCTION__); }))
;
10
Assuming field 'pw' is non-null
11
Taking true branch
1276 z.nw = (double*)ccmallocmalloc(sizeof(double) * negative_count);
1277 assert(z.nw)((void) sizeof ((z.nw) ? 1 : 0), __extension__ ({ if (z.nw) ;
else __assert_fail ("z.nw", "ccv_scd.c", 1277, __extension__
__PRETTY_FUNCTION__); }))
;
12
Assuming field 'nw' is non-null
13
Taking true branch
1278 ccmemalignposix_memalign((void**)&z.fv, 16, sizeof(float) * (z.positives->rnum + negative_count) * z.features->rnum * 32);
1279 assert(z.fv)((void) sizeof ((z.fv) ? 1 : 0), __extension__ ({ if (z.fv) ;
else __assert_fail ("z.fv", "ccv_scd.c", 1279, __extension__
__PRETTY_FUNCTION__); }))
;
14
Assuming field 'fv' is non-null
15
Taking true branch
1280 z.params = params;
1281 ccv_function_state_begin(_ccv_scd_classifier_cascade_new_function_state_read, z, filename)(_ccv_scd_classifier_cascade_new_function_state_read)((filename
), &(z)); switch ((z).line_no) { case 0:;
;
16
Calling '_ccv_scd_classifier_cascade_new_function_state_read'
40
Returned allocated memory
41
Control jumps to 'case 0:' at line 1281
1282 z.negatives = _ccv_scd_collect_negatives(rng, params.size, hard_mine, negative_count, params.grayscale);
1283 _ccv_scd_precompute_feature_vectors(z.features, z.positives, z.negatives, z.fv);
1284 z.cascade = (ccv_scd_classifier_cascade_t*)ccmallocmalloc(sizeof(ccv_scd_classifier_cascade_t));
1285 z.cascade->margin = ccv_margin(0, 0, 0, 0);
42
Potential leak of memory pointed to by 'z.cascade'
1286 z.cascade->size = params.size;
1287 z.cascade->count = 0;
1288 z.cascade->classifiers = 0;
1289 z.accu_true_positive_rate = 1;
1290 z.accu_false_positive_rate = 1;
1291 ccv_function_state_resume(_ccv_scd_classifier_cascade_new_function_state_write, z, filename)do { (z).line_no = 1291; (_ccv_scd_classifier_cascade_new_function_state_write
)(&(z), (filename)); case 1291:; } while (0)
;
1292 for (z.t = 0; z.t < params.boosting; z.t++)
1293 {
1294 for (i = 0; i < z.positives->rnum; i++)
1295 z.pw[i] = 0.5 / z.positives->rnum;
1296 for (i = 0; i < z.negatives->rnum; i++)
1297 z.nw[i] = 0.5 / z.negatives->rnum;
1298 memset(z.s, 0, sizeof(double) * (z.positives->rnum + z.negatives->rnum));
1299 z.cascade->classifiers = (ccv_scd_stump_classifier_t*)ccreallocrealloc(z.cascade->classifiers, sizeof(ccv_scd_stump_classifier_t) * (z.t + 1));
1300 z.cascade->count = z.t + 1;
1301 z.cascade->classifiers[z.t].threshold = 0;
1302 z.cascade->classifiers[z.t].features = 0;
1303 z.cascade->classifiers[z.t].count = 0;
1304 z.auc_prev = 0;
1305 assert(z.positives->rnum > 0 && z.negatives->rnum > 0)((void) sizeof ((z.positives->rnum > 0 && z.negatives
->rnum > 0) ? 1 : 0), __extension__ ({ if (z.positives->
rnum > 0 && z.negatives->rnum > 0) ; else __assert_fail
("z.positives->rnum > 0 && z.negatives->rnum > 0"
, "ccv_scd.c", 1305, __extension__ __PRETTY_FUNCTION__); }))
;
1306 // for the first prune stages, we have more restrictive number of features (faster)
1307 for (z.k = 0; z.k < (z.t < params.stop_criteria.prune_stage ? params.stop_criteria.prune_feature : params.stop_criteria.maximum_feature); z.k++)
1308 {
1309 ccv_scd_stump_classifier_t* classifier = z.cascade->classifiers + z.t;
1310 classifier->features = (ccv_scd_stump_feature_t*)ccreallocrealloc(classifier->features, sizeof(ccv_scd_stump_feature_t) * (z.k + 1));
1311 _ccv_scd_stump_feature_supervised_train(rng, z.features, z.positives->rnum, z.negatives->rnum, z.pw, z.nw, z.fv, params.C, params.weight_trimming);
1312 int best_feature_no = _ccv_scd_best_feature_gentle_adaboost(z.s, z.features, z.pw, z.nw, z.positives->rnum, z.negatives->rnum, z.fv);
1313 ccv_scd_stump_feature_t best_feature = *(ccv_scd_stump_feature_t*)ccv_array_get(z.features, best_feature_no)((void*)(((char*)((z.features)->data)) + (size_t)(z.features
)->rsize * (size_t)(best_feature_no)))
;
1314 for (i = 0; i < z.positives->rnum + z.negatives->rnum; i++)
1315 {
1316 float* surf = _ccv_scd_get_surf_at(z.fv, best_feature_no, i, z.positives->rnum, z.negatives->rnum);
1317 float v = best_feature.bias;
1318 for (j = 0; j < 32; j++)
1319 v += best_feature.w[j] * surf[j];
1320 v = expf(v);
1321 h[i] = (v - 1) / (v + 1);
1322 }
1323 // compute the total score so far
1324 for (i = 0; i < z.positives->rnum + z.negatives->rnum; i++)
1325 z.s[i] += h[i];
1326 // compute AUC
1327 double auc = _ccv_scd_auc(z.s, z.positives->rnum, z.negatives->rnum);
1328 float true_positive_rate = 0;
1329 float false_positive_rate = 0;
1330 // compute true positive / false positive rate
1331 _ccv_scd_threshold_at_hit_rate(z.s, z.positives->rnum, z.negatives->rnum, params.stop_criteria.hit_rate, &true_positive_rate, &false_positive_rate);
1332 FLUSH(CCV_CLI_INFO, " - at %d-th iteration, auc: %lf, TP rate: %f, FP rate: %f\n", z.k + 1, auc, true_positive_rate, false_positive_rate)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - at %d-th iteration, auc: %lf, TP rate: %f, FP rate: %f\n"
, z.k + 1, auc, true_positive_rate, false_positive_rate); fflush
(stdout); } } while (0)
;
1333 PRINT(CCV_CLI_INFO, " --- pick feature %s @ (%d, %d, %d, %d)\n", ((best_feature.dy[3] == best_feature.dy[0] ? "4x1" : (best_feature.dx[3] == best_feature.dx[0] ? "1x4" : "2x2"))), best_feature.sx[0], best_feature.sy[0], best_feature.dx[3], best_feature.dy[3])do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { printf
(" --- pick feature %s @ (%d, %d, %d, %d)\n", ((best_feature.
dy[3] == best_feature.dy[0] ? "4x1" : (best_feature.dx[3] == best_feature
.dx[0] ? "1x4" : "2x2"))), best_feature.sx[0], best_feature.sy
[0], best_feature.dx[3], best_feature.dy[3]); fflush(stdout);
} } while (0)
;
1334 classifier->features[z.k] = best_feature;
1335 classifier->count = z.k + 1;
1336 double auc_prev = z.auc_prev;
1337 z.auc_prev = auc;
1338 // auc stop to improve, as well as the false positive rate goal reach, at that point, we stop
1339 if (auc - auc_prev < params.stop_criteria.auc_crit && false_positive_rate < params.stop_criteria.false_positive_rate)
1340 break;
1341 // re-weight, with Gentle AdaBoost
1342 for (i = 0; i < z.positives->rnum; i++)
1343 z.pw[i] *= exp(-h[i]);
1344 for (i = 0; i < z.negatives->rnum; i++)
1345 z.nw[i] *= exp(h[i + z.positives->rnum]);
1346 // re-normalize
1347 double w = 0;
1348 for (i = 0; i < z.positives->rnum; i++)
1349 w += z.pw[i];
1350 w = 0.5 / w;
1351 for (i = 0; i < z.positives->rnum; i++)
1352 z.pw[i] *= w;
1353 w = 0;
1354 for (i = 0; i < z.negatives->rnum; i++)
1355 w += z.nw[i];
1356 w = 0.5 / w;
1357 for (i = 0; i < z.negatives->rnum; i++)
1358 z.nw[i] *= w;
1359 ccv_function_state_resume(_ccv_scd_classifier_cascade_new_function_state_write, z, filename)do { (z).line_no = 1359; (_ccv_scd_classifier_cascade_new_function_state_write
)(&(z), (filename)); case 1359:; } while (0)
;
1360 }
1361 // backtrack removal
1362 while (z.cascade->classifiers[z.t].count > 1)
1363 {
1364 double max_auc = 0;
1365 p = -1;
1366 for (i = 0; i < z.cascade->classifiers[z.t].count; i++)
1367 {
1368 ccv_scd_stump_feature_t* feature = z.cascade->classifiers[z.t].features + i;
1369 int k = _ccv_scd_find_match_feature(feature, z.features);
1370 assert(k >= 0)((void) sizeof ((k >= 0) ? 1 : 0), __extension__ ({ if (k >=
0) ; else __assert_fail ("k >= 0", "ccv_scd.c", 1370, __extension__
__PRETTY_FUNCTION__); }))
;
1371 for (j = 0; j < z.positives->rnum + z.negatives->rnum; j++)
1372 {
1373 float* surf = _ccv_scd_get_surf_at(z.fv, k, j, z.positives->rnum, z.negatives->rnum);
1374 float v = feature->bias;
1375 for (q = 0; q < 32; q++)
1376 v += feature->w[q]* surf[q];
1377 v = expf(v);
1378 h[j] = z.s[j] - (v - 1) / (v + 1);
1379 }
1380 double auc = _ccv_scd_auc(h, z.positives->rnum, z.negatives->rnum);
1381 FLUSH(CCV_CLI_INFO, " - attempting without %d-th feature, auc: %lf", i + 1, auc)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - attempting without %d-th feature, auc: %lf"
, i + 1, auc); fflush(stdout); } } while (0)
;
1382 if (auc >= max_auc)
1383 max_auc = auc, p = i;
1384 }
1385 if (max_auc >= z.auc_prev)
1386 {
1387 FLUSH(CCV_CLI_INFO, " - remove %d-th feature with new auc %lf\n", p + 1, max_auc)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - remove %d-th feature with new auc %lf\n"
, p + 1, max_auc); fflush(stdout); } } while (0)
;
1388 ccv_scd_stump_feature_t* feature = z.cascade->classifiers[z.t].features + p;
1389 int k = _ccv_scd_find_match_feature(feature, z.features);
1390 assert(k >= 0)((void) sizeof ((k >= 0) ? 1 : 0), __extension__ ({ if (k >=
0) ; else __assert_fail ("k >= 0", "ccv_scd.c", 1390, __extension__
__PRETTY_FUNCTION__); }))
;
1391 for (j = 0; j < z.positives->rnum + z.negatives->rnum; j++)
1392 {
1393 float* surf = _ccv_scd_get_surf_at(z.fv, k, j, z.positives->rnum, z.negatives->rnum);
1394 float v = feature->bias;
1395 for (q = 0; q < 32; q++)
1396 v += feature->w[q] * surf[q];
1397 v = expf(v);
1398 z.s[j] -= (v - 1) / (v + 1);
1399 }
1400 z.auc_prev = _ccv_scd_auc(z.s, z.positives->rnum, z.negatives->rnum);
1401 --z.cascade->classifiers[z.t].count;
1402 if (p < z.cascade->classifiers[z.t].count)
1403 memmove(z.cascade->classifiers[z.t].features + p + 1, z.cascade->classifiers[z.t].features + p, sizeof(ccv_scd_stump_feature_t) * (z.cascade->classifiers[z.t].count - p));
1404 } else
1405 break;
1406 }
1407 float true_positive_rate = 0;
1408 float false_positive_rate = 0;
1409 z.cascade->classifiers[z.t].threshold = _ccv_scd_threshold_at_hit_rate(z.s, z.positives->rnum, z.negatives->rnum, params.stop_criteria.hit_rate, &true_positive_rate, &false_positive_rate);
1410 z.accu_true_positive_rate *= true_positive_rate;
1411 z.accu_false_positive_rate *= false_positive_rate;
1412 FLUSH(CCV_CLI_INFO, " - %d-th stage classifier TP rate : %f, FP rate : %f, ATP rate : %lf, AFP rate : %lg, at threshold : %f\n", z.t + 1, true_positive_rate, false_positive_rate, z.accu_true_positive_rate, z.accu_false_positive_rate, z.cascade->classifiers[z.t].threshold)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { for
(_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT;
_CCV_PRINT_LOOP++) printf("\b"); for (_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP
< _CCV_PRINT_COUNT; _CCV_PRINT_LOOP++) printf(" "); for (
_CCV_PRINT_LOOP = 0; _CCV_PRINT_LOOP < _CCV_PRINT_COUNT; _CCV_PRINT_LOOP
++) printf("\b"); _CCV_PRINT_COUNT = printf(" - %d-th stage classifier TP rate : %f, FP rate : %f, ATP rate : %lf, AFP rate : %lg, at threshold : %f\n"
, z.t + 1, true_positive_rate, false_positive_rate, z.accu_true_positive_rate
, z.accu_false_positive_rate, z.cascade->classifiers[z.t].
threshold); fflush(stdout); } } while (0)
;
1413 if (z.accu_false_positive_rate < params.stop_criteria.accu_false_positive_rate)
1414 break;
1415 ccv_function_state_resume(_ccv_scd_classifier_cascade_new_function_state_write, z, filename)do { (z).line_no = 1415; (_ccv_scd_classifier_cascade_new_function_state_write
)(&(z), (filename)); case 1415:; } while (0)
;
1416 if (z.t < params.boosting - 1)
1417 {
1418 int pass = 0;
1419 for (i = 0; i < z.positives->rnum; i++)
1420 {
1421 ccv_dense_matrix_t* a = (ccv_dense_matrix_t*)ccv_array_get(z.positives, i)((void*)(((char*)((z.positives)->data)) + (size_t)(z.positives
)->rsize * (size_t)(i)))
;
1422 a->data.u8 = (unsigned char*)(a + 1);
1423 if (_ccv_scd_classifier_cascade_pass(z.cascade, a))
1424 ++pass;
1425 }
1426 PRINT(CCV_CLI_INFO, " - %d-th stage classifier TP rate (with pass) : %f\n", z.t + 1, (float)pass / z.positives->rnum)do { if ((CCV_CLI_INFO & ccv_cli_get_output_levels())) { printf
(" - %d-th stage classifier TP rate (with pass) : %f\n", z.t +
1, (float)pass / z.positives->rnum); fflush(stdout); } } while
(0)
;
1427 ccv_array_t* hard_negatives = _ccv_scd_hard_mining(rng, z.cascade, hard_mine, z.negatives, negative_count, params.grayscale, z.t < params.stop_criteria.prune_stage /* try to balance even distribution among negatives when we are in prune stage */);
1428 ccv_array_free(z.negatives);
1429 z.negatives = hard_negatives;
1430 _ccv_scd_precompute_feature_vectors(z.features, z.positives, z.negatives, z.fv);
1431 }
1432 ccv_function_state_resume(_ccv_scd_classifier_cascade_new_function_state_write, z, filename)do { (z).line_no = 1432; (_ccv_scd_classifier_cascade_new_function_state_write
)(&(z), (filename)); case 1432:; } while (0)
;
1433 }
1434 ccv_array_free(z.negatives);
1435 ccv_function_state_finish()};
1436 ccv_array_free(z.features);
1437 ccv_array_free(z.positives);
1438 ccfreefree(h);
1439 ccfreefree(z.s);
1440 ccfreefree(z.pw);
1441 ccfreefree(z.nw);
1442 ccfreefree(z.fv);
1443 gsl_rng_free(rng);
1444 return z.cascade;
1445#else
1446 assert(0 && "ccv_scd_classifier_cascade_new requires GSL library and support")((void) sizeof ((0 && "ccv_scd_classifier_cascade_new requires GSL library and support"
) ? 1 : 0), __extension__ ({ if (0 && "ccv_scd_classifier_cascade_new requires GSL library and support"
) ; else __assert_fail ("0 && \"ccv_scd_classifier_cascade_new requires GSL library and support\""
, "ccv_scd.c", 1446, __extension__ __PRETTY_FUNCTION__); }))
;
1447 return 0;
1448#endif
1449}
1450
1451void ccv_scd_classifier_cascade_write(ccv_scd_classifier_cascade_t* cascade, const char* filename)
1452{
1453 sqlite3* db = 0;
1454 if (SQLITE_OK0 == sqlite3_open(filename, &db))
1455 {
1456 const char create_table_qs[] =
1457 "CREATE TABLE IF NOT EXISTS cascade_params "
1458 "(id INTEGER PRIMARY KEY ASC, count INTEGER, "
1459 "margin_left INTEGER, margin_top INTEGER, margin_right INTEGER, margin_bottom INTEGER, "
1460 "size_width INTEGER, size_height INTEGER);"
1461 "CREATE TABLE IF NOT EXISTS classifier_params "
1462 "(classifier INTEGER PRIMARY KEY ASC, count INTEGER, threshold DOUBLE);"
1463 "CREATE TABLE IF NOT EXISTS feature_params "
1464 "(classifier INTEGER, id INTEGER, "
1465 "sx_0 INTEGER, sy_0 INTEGER, dx_0 INTEGER, dy_0 INTEGER, "
1466 "sx_1 INTEGER, sy_1 INTEGER, dx_1 INTEGER, dy_1 INTEGER, "
1467 "sx_2 INTEGER, sy_2 INTEGER, dx_2 INTEGER, dy_2 INTEGER, "
1468 "sx_3 INTEGER, sy_3 INTEGER, dx_3 INTEGER, dy_3 INTEGER, "
1469 "bias DOUBLE, w BLOB, UNIQUE (classifier, id));";
1470 assert(SQLITE_OK == sqlite3_exec(db, create_table_qs, 0, 0, 0))((void) sizeof ((0 == sqlite3_exec(db, create_table_qs, 0, 0,
0)) ? 1 : 0), __extension__ ({ if (0 == sqlite3_exec(db, create_table_qs
, 0, 0, 0)) ; else __assert_fail ("SQLITE_OK == sqlite3_exec(db, create_table_qs, 0, 0, 0)"
, "ccv_scd.c", 1470, __extension__ __PRETTY_FUNCTION__); }))
;
1471 const char cascade_params_insert_qs[] =
1472 "REPLACE INTO cascade_params "
1473 "(id, count, "
1474 "margin_left, margin_top, margin_right, margin_bottom, "
1475 "size_width, size_height) VALUES "
1476 "(0, $count, " // 0
1477 "$margin_left, $margin_top, $margin_bottom, $margin_right, " // 4
1478 "$size_width, $size_height);"; // 6
1479 sqlite3_stmt* cascade_params_insert_stmt = 0;
1480 assert(SQLITE_OK == sqlite3_prepare_v2(db, cascade_params_insert_qs, sizeof(cascade_params_insert_qs), &cascade_params_insert_stmt, 0))((void) sizeof ((0 == sqlite3_prepare_v2(db, cascade_params_insert_qs
, sizeof(cascade_params_insert_qs), &cascade_params_insert_stmt
, 0)) ? 1 : 0), __extension__ ({ if (0 == sqlite3_prepare_v2(
db, cascade_params_insert_qs, sizeof(cascade_params_insert_qs
), &cascade_params_insert_stmt, 0)) ; else __assert_fail (
"SQLITE_OK == sqlite3_prepare_v2(db, cascade_params_insert_qs, sizeof(cascade_params_insert_qs), &cascade_params_insert_stmt, 0)"
, "ccv_scd.c", 1480, __extension__ __PRETTY_FUNCTION__); }))
;
1481 sqlite3_bind_int(cascade_params_insert_stmt, 1, cascade->count);
1482 sqlite3_bind_int(cascade_params_insert_stmt, 2, cascade->margin.left);
1483 sqlite3_bind_int(cascade_params_insert_stmt, 3, cascade->margin.top);
1484 sqlite3_bind_int(cascade_params_insert_stmt, 4, cascade->margin.right);
1485 sqlite3_bind_int(cascade_params_insert_stmt, 5, cascade->margin.bottom);
1486 sqlite3_bind_int(cascade_params_insert_stmt, 6, cascade->size.width);
1487 sqlite3_bind_int(cascade_params_insert_stmt, 7, cascade->size.height);
1488 assert(SQLITE_DONE == sqlite3_step(cascade_params_insert_stmt))((void) sizeof ((101 == sqlite3_step(cascade_params_insert_stmt
)) ? 1 : 0), __extension__ ({ if (101 == sqlite3_step(cascade_params_insert_stmt
)) ; else __assert_fail ("SQLITE_DONE == sqlite3_step(cascade_params_insert_stmt)"
, "ccv_scd.c", 1488, __extension__ __PRETTY_FUNCTION__); }))
;
1489 sqlite3_finalize(cascade_params_insert_stmt);
1490 const char classifier_params_insert_qs[] =
1491 "REPLACE INTO classifier_params "
1492 "(classifier, count, threshold) VALUES "
1493 "($classifier, $count, $threshold);";
1494 sqlite3_stmt* classifier_params_insert_stmt = 0;
1495 assert(SQLITE_OK == sqlite3_prepare_v2(db, classifier_params_insert_qs, sizeof(classifier_params_insert_qs), &classifier_params_insert_stmt, 0))((void) sizeof ((0 == sqlite3_prepare_v2(db, classifier_params_insert_qs
, sizeof(classifier_params_insert_qs), &classifier_params_insert_stmt
, 0)) ? 1 : 0), __extension__ ({ if (0 == sqlite3_prepare_v2(
db, classifier_params_insert_qs, sizeof(classifier_params_insert_qs
), &classifier_params_insert_stmt, 0)) ; else __assert_fail
("SQLITE_OK == sqlite3_prepare_v2(db, classifier_params_insert_qs, sizeof(classifier_params_insert_qs), &classifier_params_insert_stmt, 0)"
, "ccv_scd.c", 1495, __extension__ __PRETTY_FUNCTION__); }))
;
1496 const char feature_params_insert_qs[] =
1497 "REPLACE INTO feature_params "
1498 "(classifier, id, "
1499 "sx_0, sy_0, dx_0, dy_0, "
1500 "sx_1, sy_1, dx_1, dy_1, "
1501 "sx_2, sy_2, dx_2, dy_2, "
1502 "sx_3, sy_3, dx_3, dy_3, "
1503 "bias, w) VALUES "
1504 "($classifier, $id, " // 1
1505 "$sx_0, $sy_0, $dx_0, $dy_0, " // 5
1506 "$sx_1, $sy_1, $dx_1, $dy_1, " // 9
1507 "$sx_2, $sy_2, $dx_2, $dy_2, " // 13
1508 "$sx_3, $sy_3, $dx_3, $dy_3, " // 17
1509 "$bias, $w);"; // 19
1510 sqlite3_stmt* feature_params_insert_stmt = 0;
1511 assert(SQLITE_OK == sqlite3_prepare_v2(db, feature_params_insert_qs, sizeof(feature_params_insert_qs), &feature_params_insert_stmt, 0))((void) sizeof ((0 == sqlite3_prepare_v2(db, feature_params_insert_qs
, sizeof(feature_params_insert_qs), &feature_params_insert_stmt
, 0)) ? 1 : 0), __extension__ ({ if (0 == sqlite3_prepare_v2(
db, feature_params_insert_qs, sizeof(feature_params_insert_qs
), &feature_params_insert_stmt, 0)) ; else __assert_fail (
"SQLITE_OK == sqlite3_prepare_v2(db, feature_params_insert_qs, sizeof(feature_params_insert_qs), &feature_params_insert_stmt, 0)"
, "ccv_scd.c", 1511, __extension__ __PRETTY_FUNCTION__); }))
;
1512 int i, j, k;
1513 for (i = 0; i < cascade->count; i++)
1514 {
1515 ccv_scd_stump_classifier_t* classifier = cascade->classifiers + i;
1516 sqlite3_bind_int(classifier_params_insert_stmt, 1, i);
1517 sqlite3_bind_int(classifier_params_insert_stmt, 2, classifier->count);
1518 sqlite3_bind_double(classifier_params_insert_stmt, 3, classifier->threshold);
1519 assert(SQLITE_DONE == sqlite3_step(classifier_params_insert_stmt))((void) sizeof ((101 == sqlite3_step(classifier_params_insert_stmt
)) ? 1 : 0), __extension__ ({ if (101 == sqlite3_step(classifier_params_insert_stmt
)) ; else __assert_fail ("SQLITE_DONE == sqlite3_step(classifier_params_insert_stmt)"
, "ccv_scd.c", 1519, __extension__ __PRETTY_FUNCTION__); }))
;
1520 sqlite3_reset(classifier_params_insert_stmt);
1521 sqlite3_clear_bindings(classifier_params_insert_stmt);
1522 for (j = 0; j < classifier->count; j++)
1523 {
1524 ccv_scd_stump_feature_t* feature = classifier->features + j;
1525 sqlite3_bind_int(feature_params_insert_stmt, 1, i);
1526 sqlite3_bind_int(feature_params_insert_stmt, 2, j);
1527 for (k = 0; k < 4; k++)
1528 {
1529 sqlite3_bind_int(feature_params_insert_stmt, 3 + k * 4, feature->sx[k]);
1530 sqlite3_bind_int(feature_params_insert_stmt, 4 + k * 4, feature->sy[k]);
1531 sqlite3_bind_int(feature_params_insert_stmt, 5 + k * 4, feature->dx[k]);
1532 sqlite3_bind_int(feature_params_insert_stmt, 6 + k * 4, feature->dy[k]);
1533 }
1534 sqlite3_bind_double(feature_params_insert_stmt, 19, feature->bias);
1535 sqlite3_bind_blob(feature_params_insert_stmt, 20, feature->w, sizeof(float) * 32, SQLITE_STATIC((sqlite3_destructor_type)0));
1536 assert(SQLITE_DONE == sqlite3_step(feature_params_insert_stmt))((void) sizeof ((101 == sqlite3_step(feature_params_insert_stmt
)) ? 1 : 0), __extension__ ({ if (101 == sqlite3_step(feature_params_insert_stmt
)) ; else __assert_fail ("SQLITE_DONE == sqlite3_step(feature_params_insert_stmt)"
, "ccv_scd.c", 1536, __extension__ __PRETTY_FUNCTION__); }))
;
1537 sqlite3_reset(feature_params_insert_stmt);
1538 sqlite3_clear_bindings(feature_params_insert_stmt);
1539 }
1540 }
1541 sqlite3_finalize(classifier_params_insert_stmt);
1542 sqlite3_finalize(feature_params_insert_stmt);
1543 sqlite3_close(db);
1544 }
1545}
1546
1547ccv_scd_classifier_cascade_t* ccv_scd_classifier_cascade_read(const char* filename)
1548{
1549 int i;
1550 sqlite3* db = 0;
1551 ccv_scd_classifier_cascade_t* cascade = 0;
1552 if (SQLITE_OK0 == sqlite3_open(filename, &db))
18
Assuming the condition is true
19
Taking true branch
1553 {
1554 const char cascade_params_qs[] =
1555 "SELECT count, " // 1
1556 "margin_left, margin_top, margin_right, margin_bottom, " // 5
1557 "size_width, size_height FROM cascade_params WHERE id = 0;"; // 7
1558 sqlite3_stmt* cascade_params_stmt = 0;
1559 if (SQLITE_OK0 == sqlite3_prepare_v2(db, cascade_params_qs, sizeof(cascade_params_qs), &cascade_params_stmt, 0))
20
Assuming the condition is true
21
Taking true branch
1560 {
1561 if (sqlite3_step(cascade_params_stmt) == SQLITE_ROW100)
22
Assuming the condition is true
23
Taking true branch
1562 {
1563 cascade = (ccv_scd_classifier_cascade_t*)ccmallocmalloc(sizeof(ccv_scd_classifier_cascade_t));
24
Memory is allocated
1564 cascade->count = sqlite3_column_int(cascade_params_stmt, 0);
1565 cascade->classifiers = (ccv_scd_stump_classifier_t*)cccalloccalloc(cascade->count, sizeof(ccv_scd_stump_classifier_t));
1566 cascade->margin = ccv_margin(sqlite3_column_int(cascade_params_stmt, 1), sqlite3_column_int(cascade_params_stmt, 2), sqlite3_column_int(cascade_params_stmt, 3), sqlite3_column_int(cascade_params_stmt, 4));
1567 cascade->size = ccv_size(sqlite3_column_int(cascade_params_stmt, 5), sqlite3_column_int(cascade_params_stmt, 6));
1568 }
1569 sqlite3_finalize(cascade_params_stmt);
1570 }
1571 if (cascade
24.1
'cascade' is non-null
)
25
Taking true branch
1572 {
1573 const char classifier_params_qs[] =
1574 "SELECT classifier, count, threshold FROM classifier_params ORDER BY classifier ASC;";
1575 sqlite3_stmt* classifier_params_stmt = 0;
1576 if (SQLITE_OK0 == sqlite3_prepare_v2(db, classifier_params_qs, sizeof(classifier_params_qs), &classifier_params_stmt, 0))
26
Assuming the condition is false
27
Taking false branch
1577 {
1578 while (sqlite3_step(classifier_params_stmt) == SQLITE_ROW100)
1579 if (sqlite3_column_int(classifier_params_stmt, 0) < cascade->count)
1580 {
1581 ccv_scd_stump_classifier_t* classifier = cascade->classifiers + sqlite3_column_int(classifier_params_stmt, 0);
1582 classifier->count = sqlite3_column_int(classifier_params_stmt, 1);
1583 classifier->features = (ccv_scd_stump_feature_t*)ccmallocmalloc(sizeof(ccv_scd_stump_feature_t) * classifier->count);
1584 classifier->threshold = (float)sqlite3_column_double(classifier_params_stmt, 2);
1585 }
1586 sqlite3_finalize(classifier_params_stmt);
1587 }
1588 const char feature_params_qs[] =
1589 "SELECT classifier, id, "
1590 "sx_0, sy_0, dx_0, dy_0, "
1591 "sx_1, sy_1, dx_1, dy_1, "
1592 "sx_2, sy_2, dx_2, dy_2, "
1593 "sx_3, sy_3, dx_3, dy_3, "
1594 "bias, w FROM feature_params ORDER BY classifier, id ASC;";
1595 sqlite3_stmt* feature_params_stmt = 0;
1596 if (SQLITE_OK0 == sqlite3_prepare_v2(db, feature_params_qs, sizeof(feature_params_qs), &feature_params_stmt, 0))
28
Assuming the condition is false
29
Taking false branch
1597 {
1598 while (sqlite3_step(feature_params_stmt) == SQLITE_ROW100)
1599 if (sqlite3_column_int(feature_params_stmt, 0) < cascade->count)
1600 {
1601 ccv_scd_stump_classifier_t* classifier = cascade->classifiers + sqlite3_column_int(feature_params_stmt, 0);
1602 if (sqlite3_column_int(feature_params_stmt, 1) < classifier->count)
1603 {
1604 ccv_scd_stump_feature_t* feature = classifier->features + sqlite3_column_int(feature_params_stmt, 1);
1605 for (i = 0; i < 4; i++)
1606 {
1607 feature->sx[i] = sqlite3_column_int(feature_params_stmt, 2 + i * 4);
1608 feature->sy[i] = sqlite3_column_int(feature_params_stmt, 3 + i * 4);
1609 feature->dx[i] = sqlite3_column_int(feature_params_stmt, 4 + i * 4);
1610 feature->dy[i] = sqlite3_column_int(feature_params_stmt, 5 + i * 4);
1611 }
1612 feature->bias = (float)sqlite3_column_double(feature_params_stmt, 18);
1613 int wnum = sqlite3_column_bytes(feature_params_stmt, 19);
1614 assert(wnum == 32 * sizeof(float))((void) sizeof ((wnum == 32 * sizeof(float)) ? 1 : 0), __extension__
({ if (wnum == 32 * sizeof(float)) ; else __assert_fail ("wnum == 32 * sizeof(float)"
, "ccv_scd.c", 1614, __extension__ __PRETTY_FUNCTION__); }))
;
1615 const void* w = sqlite3_column_blob(feature_params_stmt, 19);
1616 memcpy(feature->w, w, sizeof(float) * 32);
1617 }
1618 }
1619 sqlite3_finalize(feature_params_stmt);
1620 }
1621 }
1622 sqlite3_close(db);
1623 }
1624 return cascade;
1625}
1626
1627void ccv_scd_classifier_cascade_free(ccv_scd_classifier_cascade_t* cascade)
1628{
1629 int i;
1630 for (i = 0; i < cascade->count; i++)
1631 {
1632 ccv_scd_stump_classifier_t* classifier = cascade->classifiers + i;
1633 ccfreefree(classifier->features);
1634 }
1635 ccfreefree(cascade->classifiers);
1636 ccfreefree(cascade);
1637}
1638
1639static int _ccv_is_equal_same_class(const void* _r1, const void* _r2, void* data)
1640{
1641 const ccv_comp_t* r1 = (const ccv_comp_t*)_r1;
1642 const ccv_comp_t* r2 = (const ccv_comp_t*)_r2;
1643
1644 if (r2->classification.id != r1->classification.id)
1645 return 0;
1646
1647 int i = ccv_max(ccv_min(r2->rect.x + r2->rect.width, r1->rect.x + r1->rect.width) - ccv_max(r2->rect.x, r1->rect.x), 0)({ typeof (({ typeof (r2->rect.x + r2->rect.width) _a =
(r2->rect.x + r2->rect.width); typeof (r1->rect.x +
r1->rect.width) _b = (r1->rect.x + r1->rect.width);
(_a < _b) ? _a : _b; }) - ({ typeof (r2->rect.x) _a = (
r2->rect.x); typeof (r1->rect.x) _b = (r1->rect.x); (
_a > _b) ? _a : _b; })) _a = (({ typeof (r2->rect.x + r2
->rect.width) _a = (r2->rect.x + r2->rect.width); typeof
(r1->rect.x + r1->rect.width) _b = (r1->rect.x + r1
->rect.width); (_a < _b) ? _a : _b; }) - ({ typeof (r2->
rect.x) _a = (r2->rect.x); typeof (r1->rect.x) _b = (r1
->rect.x); (_a > _b) ? _a : _b; })); typeof (0) _b = (0
); (_a > _b) ? _a : _b; })
* ccv_max(ccv_min(r2->rect.y + r2->rect.height, r1->rect.y + r1->rect.height) - ccv_max(r2->rect.y, r1->rect.y), 0)({ typeof (({ typeof (r2->rect.y + r2->rect.height) _a =
(r2->rect.y + r2->rect.height); typeof (r1->rect.y +
r1->rect.height) _b = (r1->rect.y + r1->rect.height
); (_a < _b) ? _a : _b; }) - ({ typeof (r2->rect.y) _a =
(r2->rect.y); typeof (r1->rect.y) _b = (r1->rect.y)
; (_a > _b) ? _a : _b; })) _a = (({ typeof (r2->rect.y +
r2->rect.height) _a = (r2->rect.y + r2->rect.height
); typeof (r1->rect.y + r1->rect.height) _b = (r1->rect
.y + r1->rect.height); (_a < _b) ? _a : _b; }) - ({ typeof
(r2->rect.y) _a = (r2->rect.y); typeof (r1->rect.y)
_b = (r1->rect.y); (_a > _b) ? _a : _b; })); typeof (0
) _b = (0); (_a > _b) ? _a : _b; })
;
1648 int m = ccv_min(r2->rect.width * r2->rect.height, r1->rect.width * r1->rect.height)({ typeof (r2->rect.width * r2->rect.height) _a = (r2->
rect.width * r2->rect.height); typeof (r1->rect.width *
r1->rect.height) _b = (r1->rect.width * r1->rect.height
); (_a < _b) ? _a : _b; })
;
1649
1650 return i >= 0.3 * m; // IoM > 0.3 like HeadHunter does
1651}
1652
1653ccv_array_t* ccv_scd_detect_objects(ccv_dense_matrix_t* a, ccv_scd_classifier_cascade_t** cascades, int count, ccv_scd_param_t params)
1654{
1655 int i, j, k, x, y, p, q;
1656 int scale_upto = 1;
1657 float up_ratio = 1.0;
1658 for (i = 0; i < count; i++)
1659 up_ratio = ccv_max(up_ratio, ccv_max((float)cascades[i]->size.width / params.size.width, (float)cascades[i]->size.height / params.size.height))({ typeof (up_ratio) _a = (up_ratio); typeof (({ typeof ((float
)cascades[i]->size.width / params.size.width) _a = ((float
)cascades[i]->size.width / params.size.width); typeof ((float
)cascades[i]->size.height / params.size.height) _b = ((float
)cascades[i]->size.height / params.size.height); (_a > _b
) ? _a : _b; })) _b = (({ typeof ((float)cascades[i]->size
.width / params.size.width) _a = ((float)cascades[i]->size
.width / params.size.width); typeof ((float)cascades[i]->size
.height / params.size.height) _b = ((float)cascades[i]->size
.height / params.size.height); (_a > _b) ? _a : _b; })); (
_a > _b) ? _a : _b; })
;
1660 if (up_ratio - 1.0 > 1e-4)
1661 {
1662 ccv_dense_matrix_t* resized = 0;
1663 ccv_resample(a, &resized, 0, up_ratio, up_ratio, CCV_INTER_CUBIC);
1664 a = resized;
1665 }
1666 for (i = 0; i < count; i++)
1667 scale_upto = ccv_max(scale_upto, (int)(log(ccv_min((double)a->rows / (cascades[i]->size.height - cascades[i]->margin.top - cascades[i]->margin.bottom), (double)a->cols / (cascades[i]->size.width - cascades[i]->margin.left - cascades[i]->margin.right))) / log(2.) - DBL_MIN) + 1)({ typeof (scale_upto) _a = (scale_upto); typeof ((int)(log((
{ typeof ((double)a->rows / (cascades[i]->size.height -
cascades[i]->margin.top - cascades[i]->margin.bottom))
_a = ((double)a->rows / (cascades[i]->size.height - cascades
[i]->margin.top - cascades[i]->margin.bottom)); typeof (
(double)a->cols / (cascades[i]->size.width - cascades[i
]->margin.left - cascades[i]->margin.right)) _b = ((double
)a->cols / (cascades[i]->size.width - cascades[i]->margin
.left - cascades[i]->margin.right)); (_a < _b) ? _a : _b
; })) / log(2.) - 2.2250738585072014e-308) + 1) _b = ((int)(log
(({ typeof ((double)a->rows / (cascades[i]->size.height
- cascades[i]->margin.top - cascades[i]->margin.bottom
)) _a = ((double)a->rows / (cascades[i]->size.height - cascades
[i]->margin.top - cascades[i]->margin.bottom)); typeof (
(double)a->cols / (cascades[i]->size.width - cascades[i
]->margin.left - cascades[i]->margin.right)) _b = ((double
)a->cols / (cascades[i]->size.width - cascades[i]->margin
.left - cascades[i]->margin.right)); (_a < _b) ? _a : _b
; })) / log(2.) - 2.2250738585072014e-308) + 1); (_a > _b)
? _a : _b; })
;
1668 ccv_dense_matrix_t** pyr = (ccv_dense_matrix_t**)alloca(sizeof(ccv_dense_matrix_t*) * scale_upto)__builtin_alloca (sizeof(ccv_dense_matrix_t*) * scale_upto);
1669 pyr[0] = a;
1670 for (i = 1; i < scale_upto; i++)
1671 {
1672 pyr[i] = 0;
1673 ccv_sample_down(pyr[i - 1], &pyr[i], 0, 0, 0);
1674 }
1675#if defined(HAVE_SSE21)
1676 __m128 surf[8];
1677#else
1678 float surf[32];
1679#endif
1680 ccv_array_t** seq = (ccv_array_t**)alloca(sizeof(ccv_array_t*) * count)__builtin_alloca (sizeof(ccv_array_t*) * count);
1681 for (i = 0; i < count; i++)
1682 seq[i] = ccv_array_new(sizeof(ccv_comp_t), 64, 0);
1683 for (i = 0; i < scale_upto; i++)
1684 {
1685 // run it
1686 for (j = 0; j < count; j++)
1687 {
1688 double scale_ratio = pow(2., 1. / (params.interval + 1));
1689 double scale = 1;
1690 ccv_scd_classifier_cascade_t* cascade = cascades[j];
1691 for (k = 0; k <= params.interval; k++)
1692 {
1693 int rows = (int)(pyr[i]->rows / scale + 0.5);
1694 int cols = (int)(pyr[i]->cols / scale + 0.5);
1695 if (rows < cascade->size.height || cols < cascade->size.width)
1696 break;
1697 ccv_dense_matrix_t* image = k == 0 ? pyr[i] : 0;
1698 if (k > 0)
1699 ccv_resample(pyr[i], &image, 0, (double)rows / (double)pyr[i]->rows, (double)cols / (double)pyr[i]->cols, CCV_INTER_AREA);
1700 ccv_dense_matrix_t* scd = 0;
1701 if (cascade->margin.left == 0 && cascade->margin.top == 0 && cascade->margin.right == 0 && cascade->margin.bottom == 0)
1702 {
1703 ccv_scd(image, &scd, 0);
1704 if (k > 0)
1705 ccv_matrix_free(image);
1706 } else {
1707 ccv_dense_matrix_t* bordered = 0;
1708 ccv_border(image, (ccv_matrix_t**)&bordered, 0, cascade->margin);
1709 if (k > 0)
1710 ccv_matrix_free(image);
1711 ccv_scd(bordered, &scd, 0);
1712 ccv_matrix_free(bordered);
1713 }
1714 ccv_dense_matrix_t* sat = 0;
1715 ccv_sat(scd, &sat, 0, CCV_PADDING_ZERO);
1716 assert(CCV_GET_CHANNEL(sat->type) == CCV_SCD_CHANNEL)((void) sizeof ((((sat->type) & 0xFFF) == (11)) ? 1 : 0
), __extension__ ({ if (((sat->type) & 0xFFF) == (11))
; else __assert_fail ("CCV_GET_CHANNEL(sat->type) == CCV_SCD_CHANNEL"
, "ccv_scd.c", 1716, __extension__ __PRETTY_FUNCTION__); }))
;
1717 ccv_matrix_free(scd);
1718 float* ptr = sat->data.f32;
1719 for (y = 0; y < rows; y += params.step_through)
1720 {
1721 if (y >= sat->rows - cascade->size.height - 1)
1722 break;
1723 for (x = 0; x < cols; x += params.step_through)
1724 {
1725 if (x >= sat->cols - cascade->size.width - 1)
1726 break;
1727 int pass = 1;
1728 float sum = 0;
1729 for (p = 0; p < cascade->count; p++)
1730 {
1731 ccv_scd_stump_classifier_t* classifier = cascade->classifiers + p;
1732 float v = 0;
1733 for (q = 0; q < classifier->count; q++)
1734 {
1735 ccv_scd_stump_feature_t* feature = classifier->features + q;
1736#if defined(HAVE_SSE21)
1737 _ccv_scd_run_feature_at_sse2(ptr + x * CCV_SCD_CHANNEL(11), sat->cols, feature, surf);
1738 __m128 u0 = _mm_add_ps(_mm_mul_ps(surf[0], _mm_loadu_ps(feature->w)), _mm_mul_ps(surf[1], _mm_loadu_ps(feature->w + 4)));
1739 __m128 u1 = _mm_add_ps(_mm_mul_ps(surf[2], _mm_loadu_ps(feature->w + 8)), _mm_mul_ps(surf[3], _mm_loadu_ps(feature->w + 12)));
1740 __m128 u2 = _mm_add_ps(_mm_mul_ps(surf[4], _mm_loadu_ps(feature->w + 16)), _mm_mul_ps(surf[5], _mm_loadu_ps(feature->w + 20)));
1741 __m128 u3 = _mm_add_ps(_mm_mul_ps(surf[6], _mm_loadu_ps(feature->w + 24)), _mm_mul_ps(surf[7], _mm_loadu_ps(feature->w + 28)));
1742 u0 = _mm_add_ps(u0, u1);
1743 u2 = _mm_add_ps(u2, u3);
1744 union {
1745 float f[4];
1746 __m128 p;
1747 } ux;
1748 ux.p = _mm_add_ps(u0, u2);
1749 float u = expf(feature->bias + ux.f[0] + ux.f[1] + ux.f[2] + ux.f[3]);
1750#else
1751 _ccv_scd_run_feature_at(ptr + x * CCV_SCD_CHANNEL(11), sat->cols, feature, surf);
1752 float u = feature->bias;
1753 int r;
1754 for (r = 0; r < 32; r++)
1755 u += surf[r] * feature->w[r];
1756 u = expf(u);
1757#endif
1758 v += (u - 1) / (u + 1);
1759 }
1760 if (v <= classifier->threshold)
1761 {
1762 pass = 0;
1763 break;
1764 }
1765 sum = v / classifier->count;
1766 }
1767 if (pass)
1768 {
1769 ccv_comp_t comp;
1770 comp.rect = ccv_rect((int)((x + 0.5) * (scale / up_ratio) * (1 << i) - 0.5),
1771 (int)((y + 0.5) * (scale / up_ratio) * (1 << i) - 0.5),
1772 (cascade->size.width - cascade->margin.left - cascade->margin.right) * (scale / up_ratio) * (1 << i),
1773 (cascade->size.height - cascade->margin.top - cascade->margin.bottom) * (scale / up_ratio) * (1 << i));
1774 comp.neighbors = 1;
1775 comp.classification.id = j + 1;
1776 comp.classification.confidence = sum + (cascade->count - 1);
1777 ccv_array_push(seq[j], &comp);
1778 }
1779 }
1780 ptr += sat->cols * CCV_SCD_CHANNEL(11) * params.step_through;
1781 }
1782 ccv_matrix_free(sat);
1783 scale *= scale_ratio;
1784 }
1785 }
1786 }
1787
1788 for (i = 1; i < scale_upto; i++)
1789 ccv_matrix_free(pyr[i]);
1790 if (up_ratio - 1.0 > 1e-4)
1791 ccv_matrix_free(a);
1792
1793 ccv_array_t* result_seq = ccv_array_new(sizeof(ccv_comp_t), 64, 0);
1794 for (k = 0; k < count; k++)
1795 {
1796 /* simple non-maximum suppression, we merge when intersected area / min area > 0.3 */
1797 if(params.min_neighbors == 0)
1798 {
1799 for (i = 0; i < seq[k]->rnum; i++)
1800 {
1801 ccv_comp_t* comp = (ccv_comp_t*)ccv_array_get(seq[k], i)((void*)(((char*)((seq[k])->data)) + (size_t)(seq[k])->
rsize * (size_t)(i)))
;
1802 ccv_array_push(result_seq, comp);
1803 }
1804 } else {
1805 ccv_array_t* idx_seq = 0;
1806 // group retrieved rectangles in order to filter out noise
1807 int ncomp = ccv_array_group(seq[k], &idx_seq, _ccv_is_equal_same_class, 0);
1808 ccv_comp_t* comps = (ccv_comp_t*)cccalloccalloc(ncomp + 1, sizeof(ccv_comp_t));
1809
1810 // count number of neighbors
1811 for (i = 0; i < seq[k]->rnum; i++)
1812 {
1813 ccv_comp_t r1 = *(ccv_comp_t*)ccv_array_get(seq[k], i)((void*)(((char*)((seq[k])->data)) + (size_t)(seq[k])->
rsize * (size_t)(i)))
;
1814 int idx = *(int*)ccv_array_get(idx_seq, i)((void*)(((char*)((idx_seq)->data)) + (size_t)(idx_seq)->
rsize * (size_t)(i)))
;
1815
1816 comps[idx].classification.id = r1.classification.id;
1817 if (r1.classification.confidence > comps[idx].classification.confidence || comps[idx].neighbors == 0)
1818 {
1819 comps[idx].rect = r1.rect;
1820 comps[idx].classification.confidence = r1.classification.confidence;
1821 }
1822
1823 ++comps[idx].neighbors;
1824 }
1825
1826 // push merged bounding box to result_seq
1827 for (i = 0; i < ncomp; i++)
1828 {
1829 int n = comps[i].neighbors;
1830 if (n >= params.min_neighbors)
1831 ccv_array_push(result_seq, comps + i);
1832 }
1833 ccv_array_free(idx_seq);
1834 ccfreefree(comps);
1835 }
1836 ccv_array_free(seq[k]);
1837 }
1838
1839 return result_seq;
1840}