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https://github.com/opencv/opencv.git
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added checksum-based test for Lab bit-exactness
This commit is contained in:
Rostislav Vasilikhin
parent
d25344c257
commit
f1e8aa70a0
@ -2110,6 +2110,326 @@ TEST(Imgproc_ColorLab_Full, accuracy)
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}
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}
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static uint32_t adler32(Mat m)
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{
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uint32_t s1 = 1, s2 = 0;
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for(int y = 0; y < m.rows; y++)
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{
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uchar* py = m.ptr(y);
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for(size_t x = 0; x < m.cols*m.elemSize(); x++)
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{
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s1 = (s1 + py[x]) % 65521;
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s2 = (s1 + s2 ) % 65521;
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}
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}
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return (s2 << 16) + s1;
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}
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// taken from color.cpp
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static ushort sRGBGammaTab_b[256], linearGammaTab_b[256];
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enum { inv_gamma_shift = 12, INV_GAMMA_TAB_SIZE = (1 << inv_gamma_shift) };
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static ushort sRGBInvGammaTab_b[INV_GAMMA_TAB_SIZE], linearInvGammaTab_b[INV_GAMMA_TAB_SIZE];
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#undef lab_shift
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// #define lab_shift xyz_shift
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#define lab_shift 12
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#define gamma_shift 3
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#define lab_shift2 (lab_shift + gamma_shift)
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#define LAB_CBRT_TAB_SIZE_B (256*3/2*(1<<gamma_shift))
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static ushort LabCbrtTab_b[LAB_CBRT_TAB_SIZE_B];
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enum
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{
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lab_base_shift = 14,
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LAB_BASE = (1 << lab_base_shift),
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};
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#define CV_DESCALE(x,n) (((x) + (1 << ((n)-1))) >> (n))
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static ushort LabToYF_b[256*2];
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static const int minABvalue = -8145;
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static int abToXZ_b[LAB_BASE*9/4];
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static void initLabTabs()
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{
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static bool initialized = false;
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if(!initialized)
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{
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static const softfloat lthresh = softfloat(216) / softfloat(24389); // 0.008856f = (6/29)^3
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static const softfloat lscale = softfloat(841) / softfloat(108); // 7.787f = (29/3)^3/(29*4)
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static const softfloat lbias = softfloat(16) / softfloat(116);
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static const softfloat f255(255);
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static const softfloat intScale(255*(1 << gamma_shift));
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for(int i = 0; i < 256; i++)
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{
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softfloat x = softfloat(i)/f255;
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sRGBGammaTab_b[i] = (ushort)(cvRound(intScale*applyGamma(x)));
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linearGammaTab_b[i] = (ushort)(i*(1 << gamma_shift));
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}
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static const softfloat invScale = softfloat::one()/softfloat((int)INV_GAMMA_TAB_SIZE);
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for(int i = 0; i < INV_GAMMA_TAB_SIZE; i++)
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{
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softfloat x = invScale*softfloat(i);
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sRGBInvGammaTab_b[i] = (ushort)(cvRound(f255*applyInvGamma(x)));
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linearInvGammaTab_b[i] = (ushort)(cvTrunc(f255*x));
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}
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static const softfloat cbTabScale(softfloat::one()/(f255*(1 << gamma_shift)));
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static const softfloat lshift2(1 << lab_shift2);
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for(int i = 0; i < LAB_CBRT_TAB_SIZE_B; i++)
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{
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softfloat x = cbTabScale*softfloat(i);
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LabCbrtTab_b[i] = (ushort)(cvRound(lshift2 * (x < lthresh ? mulAdd(x, lscale, lbias) : cbrt(x))));
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}
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//Lookup table for L to y and ify calculations
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static const int BASE = (1 << 14);
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for(int i = 0; i < 256; i++)
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{
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int y, ify;
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//8 * 255.0 / 100.0 == 20.4
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if( i <= 20)
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{
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//yy = li / 903.3f;
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//y = L*100/903.3f; 903.3f = (29/3)^3, 255 = 17*3*5
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y = cvRound(softfloat(i*BASE*20*9)/softfloat(17*29*29*29));
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//fy = 7.787f * yy + 16.0f / 116.0f; 7.787f = (29/3)^3/(29*4)
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ify = cvRound(softfloat(BASE)*(softfloat(16)/softfloat(116) + softfloat(i*5)/softfloat(3*17*29)));
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}
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else
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{
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//fy = (li + 16.0f) / 116.0f;
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softfloat fy = (softfloat(i*100*BASE)/softfloat(255*116) +
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softfloat(16*BASE)/softfloat(116));
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ify = cvRound(fy);
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//yy = fy * fy * fy;
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y = cvRound(fy*fy*fy/softfloat(BASE*BASE));
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}
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LabToYF_b[i*2 ] = (ushort)y; // 2260 <= y <= BASE
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LabToYF_b[i*2+1] = (ushort)ify; // 0 <= ify <= BASE
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}
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//Lookup table for a,b to x,z conversion
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for(int i = minABvalue; i < LAB_BASE*9/4+minABvalue; i++)
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{
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int v;
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//6.f/29.f*BASE = 3389.730
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if(i <= 3390)
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{
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//fxz[k] = (fxz[k] - 16.0f / 116.0f) / 7.787f;
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// 7.787f = (29/3)^3/(29*4)
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v = i*108/841 - BASE*16/116*108/841;
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}
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else
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{
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//fxz[k] = fxz[k] * fxz[k] * fxz[k];
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v = i*i/BASE*i/BASE;
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}
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abToXZ_b[i-minABvalue] = v; // -1335 <= v <= 88231
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}
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initialized = true;
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}
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}
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static int row8uRGB2Lab(const uchar* src_row, uchar *dst_row, int n, int cn, int blue_idx, bool srgb)
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{
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int coeffs[9];
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softdouble whitept[3] = {Xn, softdouble::one(), Zn};
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static const softdouble lshift(1 << lab_shift);
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for(int i = 0; i < 3; i++)
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{
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coeffs[i*3 + (blue_idx^2)] = cvRound(lshift*RGB2XYZ[i*3 ]/whitept[i]);
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coeffs[i*3 + 1 ] = cvRound(lshift*RGB2XYZ[i*3+1]/whitept[i]);
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coeffs[i*3 + (blue_idx )] = cvRound(lshift*RGB2XYZ[i*3+2]/whitept[i]);
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}
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const int Lscale = (116*255+50)/100;
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const int Lshift = -((16*255*(1 << lab_shift2) + 50)/100);
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const ushort* tab = srgb ? sRGBGammaTab_b : linearGammaTab_b;
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for (int x = 0; x < n; x++)
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{
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int R = src_row[x*cn + 0],
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G = src_row[x*cn + 1],
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B = src_row[x*cn + 2];
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R = tab[R], G = tab[G], B = tab[B];
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int fX = LabCbrtTab_b[CV_DESCALE(R*coeffs[0] + G*coeffs[1] + B*coeffs[2], lab_shift)];
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int fY = LabCbrtTab_b[CV_DESCALE(R*coeffs[3] + G*coeffs[4] + B*coeffs[5], lab_shift)];
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int fZ = LabCbrtTab_b[CV_DESCALE(R*coeffs[6] + G*coeffs[7] + B*coeffs[8], lab_shift)];
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int L = CV_DESCALE( Lscale*fY + Lshift, lab_shift2 );
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int a = CV_DESCALE( 500*(fX - fY) + 128*(1 << lab_shift2), lab_shift2 );
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int b = CV_DESCALE( 200*(fY - fZ) + 128*(1 << lab_shift2), lab_shift2 );
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dst_row[x*3 ] = saturate_cast<uchar>(L);
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dst_row[x*3 + 1] = saturate_cast<uchar>(a);
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dst_row[x*3 + 2] = saturate_cast<uchar>(b);
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}
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return n;
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}
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int row8uLab2RGB(const uchar* src_row, uchar *dst_row, int n, int cn, int blue_idx, bool srgb)
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{
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static const int base_shift = 14;
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static const int BASE = (1 << base_shift);
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static const int shift = lab_shift+(base_shift-inv_gamma_shift);
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int coeffs[9];
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softdouble whitept[3] = {Xn, softdouble::one(), Zn};
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static const softdouble lshift(1 << lab_shift);
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for(int i = 0; i < 3; i++)
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{
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coeffs[i+(blue_idx )*3] = cvRound(lshift*XYZ2RGB[i ]*whitept[i]);
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coeffs[i+ 1*3] = cvRound(lshift*XYZ2RGB[i+3]*whitept[i]);
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coeffs[i+(blue_idx^2)*3] = cvRound(lshift*XYZ2RGB[i+6]*whitept[i]);
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}
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ushort* tab = srgb ? sRGBInvGammaTab_b : linearInvGammaTab_b;
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for(int x = 0; x < n; x++)
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{
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uchar LL = src_row[x*3 ];
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uchar aa = src_row[x*3 + 1];
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uchar bb = src_row[x*3 + 2];
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int ro, go, bo, xx, yy, zz, ify;
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yy = LabToYF_b[LL*2 ];
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ify = LabToYF_b[LL*2+1];
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int adiv, bdiv;
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//adiv = aa*BASE/500 - 128*BASE/500, bdiv = bb*BASE/200 - 128*BASE/200;
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//approximations with reasonable precision
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adiv = ((5*aa*53687 + (1 << 7)) >> 13) - 128*BASE/500;
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bdiv = (( bb*41943 + (1 << 4)) >> 9) - 128*BASE/200+1;
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int ifxz[] = {ify + adiv, ify - bdiv};
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for(int k = 0; k < 2; k++)
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{
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int& v = ifxz[k];
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v = abToXZ_b[v-minABvalue];
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}
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xx = ifxz[0]; /* yy = yy */; zz = ifxz[1];
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ro = CV_DESCALE(coeffs[0]*xx + coeffs[1]*yy + coeffs[2]*zz, shift);
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go = CV_DESCALE(coeffs[3]*xx + coeffs[4]*yy + coeffs[5]*zz, shift);
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bo = CV_DESCALE(coeffs[6]*xx + coeffs[7]*yy + coeffs[8]*zz, shift);
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ro = max(0, min((int)INV_GAMMA_TAB_SIZE-1, ro));
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go = max(0, min((int)INV_GAMMA_TAB_SIZE-1, go));
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bo = max(0, min((int)INV_GAMMA_TAB_SIZE-1, bo));
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ro = tab[ro];
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go = tab[go];
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bo = tab[bo];
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dst_row[x*cn ] = saturate_cast<uchar>(bo);
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dst_row[x*cn + 1] = saturate_cast<uchar>(go);
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dst_row[x*cn + 2] = saturate_cast<uchar>(ro);
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if(cn == 4) dst_row[x*cn + 3] = 255;
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}
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return n;
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}
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int row8uLabChoose(const uchar* src_row, uchar *dst_row, int n, bool forward, int blue_idx, bool srgb)
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{
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if(forward)
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return row8uRGB2Lab(src_row, dst_row, n, 3, blue_idx, srgb);
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else
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return row8uLab2RGB(src_row, dst_row, n, 3, blue_idx, srgb);
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}
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TEST(Imgproc_ColorLab_Full, bitExactness)
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{
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int codes[] = { CV_BGR2Lab, CV_RGB2Lab, CV_LBGR2Lab, CV_LRGB2Lab,
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CV_Lab2BGR, CV_Lab2RGB, CV_Lab2LBGR, CV_Lab2LRGB};
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string names[] = { "CV_BGR2Lab", "CV_RGB2Lab", "CV_LBGR2Lab", "CV_LRGB2Lab",
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"CV_Lab2BGR", "CV_Lab2RGB", "CV_Lab2LBGR", "CV_Lab2LRGB" };
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// need to be recalculated each time we change Lab algorithms, RNG or test system
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const int nIterations = 8;
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uint32_t hashes[] = {
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0xca7d94c4, 0x34aeb79a, 0x7272c2cf, 0x62c2efed, 0x047cab77, 0x5e8dfb85, 0x10fed613, 0x34d2f4aa,
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0x048bea9a, 0xbbe20ef2, 0x3274e88f, 0x710e9272, 0x9fd6cd59, 0x69d67639, 0x04742095, 0x9ef2b60b,
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0x75b78f5b, 0x3fda9801, 0x374cc472, 0x3239e8ad, 0x94749b2d, 0x9362ac0c, 0xa4d7dd36, 0xe25ef694,
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0x51d1b01d, 0xb0f6e3f5, 0x2b72a228, 0xb7429fa0, 0x799ba6bd, 0x2141d3d2, 0xb4dde471, 0x813b6e0f,
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0x9c029161, 0xb51eb5ec, 0x460c3a09, 0x27724f63, 0xb446c9a8, 0x3adf1b61, 0xe6b0d30f, 0xd1078779,
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0xfaa7525b, 0x5b6ea158, 0xdf3511f7, 0xf01dc02d, 0x5c663841, 0xce611ed4, 0x758ad851, 0xa43c3a1c,
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0xed30f68c, 0xcb6babd9, 0xf38262b5, 0x608cb3db, 0x13425e5a, 0x6dc5fdc7, 0x9519090a, 0x87aa73d0,
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0x8e9bf980, 0x46b98728, 0x0064591c, 0x7e1efc9b, 0xf0ec2465, 0x89a75c8d, 0x0d162fa7, 0xffea7a2f,
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};
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RNG rng(0);
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// blueIdx x srgb x direction
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for(int c = 0; c < 8; c++)
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{
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int v = c;
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int blueIdx = (v % 2 != 0) ? 2 : 0; v /=2;
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bool srgb = (v % 2 == 0); v /= 2;
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bool forward = (v % 2 == 0);
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for(int iter = 0; iter < nIterations; iter++)
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{
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Mat probe(256, 256, CV_8UC3), result;
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rng.fill(probe, RNG::UNIFORM, 0, 255, true);
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cvtColor(probe, result, codes[c]);
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uint32_t h = adler32(result);
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if(h != hashes[c*nIterations + iter])
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{
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initLabTabs();
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cvtest::TS* ts = cvtest::TS::ptr();
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vector<uchar> goldBuf(probe.cols*4);
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uchar* goldRow = &goldBuf[0];
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bool next = true;
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for(int y = 0; next && y < probe.rows; y++)
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{
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uchar* probeRow = probe.ptr(y);
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uchar* resultRow = result.ptr(y);
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row8uLabChoose(probeRow, goldRow, probe.cols, forward, blueIdx, srgb);
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for(int x = 0; next && x < probe.cols; x++)
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{
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uchar* px = probeRow + x*3;
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uchar* gx = goldRow + x*3;
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uchar* rx = resultRow + x*3;
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if(gx[0] != rx[0] || gx[1] != rx[1] || gx[2] != rx[2])
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{
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next = false;
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ts->printf(cvtest::TS::SUMMARY, "Error in: (%d, %d)\n", x, y);
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ts->printf(cvtest::TS::SUMMARY, "Conversion code: %s\n", names[c].c_str());
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ts->printf(cvtest::TS::SUMMARY, "Reference value: %d %d %d\n", gx[0], gx[1], gx[2]);
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ts->printf(cvtest::TS::SUMMARY, "Actual value: %d %d %d\n", rx[0], rx[1], rx[2]);
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ts->printf(cvtest::TS::SUMMARY, "Src value: %d %d %d\n", px[0], px[1], px[2]);
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ts->printf(cvtest::TS::SUMMARY, "Size: (%d, %d)\n", probe.rows, probe.cols);
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ts->set_failed_test_info(cvtest::TS::FAIL_BAD_ACCURACY);
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ts->set_gtest_status();
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break;
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}
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}
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}
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if(next)
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// this place should never be reached
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throw std::runtime_error("Test system error: hash function mismatch when results are the same");
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}
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}
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}
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}
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static void test_Bayer2RGB_EdgeAware_8u(const Mat& src, Mat& dst, int code)
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{
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if (dst.empty())
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