added gpu::dft implemented via CUFFT

modules/gpu/include/opencv2/gpu/gpu.hpp

@@ -628,15 +628,28 @@ namespace cv
         //! computes minimum eigen value of 2x2 derivative covariation matrix at each pixel - the cornerness criteria
         CV_EXPORTS void cornerMinEigenVal(const GpuMat& src, GpuMat& dst, int blockSize, int ksize, int borderType=BORDER_REFLECT101);
 
-        //! performs per-element multiplication of two full (i.e. not packed) Fourier spectrums
-        //! supports only 32FC2 matrixes (interleaved format)
+        //! performs per-element multiplication of two full (not packed) Fourier spectrums
+        //! supports 32FC2 matrixes only (interleaved format)
         CV_EXPORTS void mulSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flags, bool conjB=false);
 
-        //! performs per-element multiplication of two full (i.e. not packed) Fourier spectrums
-        //! supports only 32FC2 matrixes (interleaved format)
+        //! performs per-element multiplication of two full (not packed) Fourier spectrums
+        //! supports 32FC2 matrixes only (interleaved format)
         CV_EXPORTS void mulAndScaleSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c, int flags, 
                                              float scale, bool conjB=false);
 
+        //! performs a forward or inverse discrete Fourier transform (1D or 2D) of floating point matrix
+        //!
+        //! If the source matrix is not continous, then additional copy will be done,
+        //! so to avoid copying ensure the source matrix is continous one.
+        //!
+        //! Being implemented via CUFFT real-to-complex transform result contains only non-redundant values
+        //! in CUFFT's format. Result as full complex matrix for such kind of transform cannot be retrieved.
+        //!
+        //! For complex-to-real transform it is assumed that the source matrix is packed in CUFFT's format, which
+        //! doesn't allow us to retrieve parity of the destiantion matrix dimension (along which the first step 
+        //! of DFT is performed). You must specifiy odd case explicitely.
+        CV_EXPORTS void dft(const GpuMat& src, GpuMat& dst, int flags=0, int nonZeroRows=0, bool odd=false);
+
         //! computes convolution (or cross-correlation) of two images using discrete Fourier transform
         //! supports source images of 32FC1 type only
         //! result matrix will have 32FC1 type

modules/gpu/src/imgproc_gpu.cpp

@@ -76,6 +76,7 @@ void cv::gpu::cornerHarris(const GpuMat&, GpuMat&, int, int, double, int) { thro
 void cv::gpu::cornerMinEigenVal(const GpuMat&, GpuMat&, int, int, int) { throw_nogpu(); }
 void cv::gpu::mulSpectrums(const GpuMat&, const GpuMat&, GpuMat&, int, bool) { throw_nogpu(); }
 void cv::gpu::mulAndScaleSpectrums(const GpuMat&, const GpuMat&, GpuMat&, int, float, bool) { throw_nogpu(); }
+void cv::gpu::dft(const GpuMat&, GpuMat&, int, int, bool) { throw_nogpu(); }
 void cv::gpu::convolve(const GpuMat&, const GpuMat&, GpuMat&, bool) { throw_nogpu(); }
 
 
@@ -1126,6 +1127,164 @@ void cv::gpu::mulAndScaleSpectrums(const GpuMat& a, const GpuMat& b, GpuMat& c,
     caller(a, b, scale, c);
 }
 
+//////////////////////////////////////////////////////////////////////////////
+// dft
+
+void cv::gpu::dft(const GpuMat& src, GpuMat& dst, int flags, int nonZeroRows, bool odd)
+{
+    CV_Assert(src.type() == CV_32F || src.type() == CV_32FC2);
+
+    // We don't support unpacked output (in the case of real input)
+    CV_Assert(!(flags & DFT_COMPLEX_OUTPUT));
+
+    bool is_1d_input = (src.rows == 1) || (src.cols == 1);
+    int is_row_dft = flags & DFT_ROWS;
+    int is_scaled_dft = flags & DFT_SCALE;
+    int is_inverse = flags & DFT_INVERSE;
+    bool is_complex_input = src.channels() == 2;
+    bool is_complex_output = !(flags & DFT_REAL_OUTPUT);
+
+    // We don't support scaled transform
+    CV_Assert(!is_scaled_dft);
+
+    // We don't support real-to-real transform
+    CV_Assert(is_complex_input || is_complex_output);
+
+    GpuMat src_data, src_aux;
+
+    // Make sure here we work with the continuous input, 
+    // as CUFFT can't handle gaps
+    if (src.isContinuous())
+        src_aux = src;
+    else
+    {
+        src_data = GpuMat(1, src.size().area(), src.type());
+        src_aux = GpuMat(src.rows, src.cols, src.type(), src_data.ptr(), src.cols * src.elemSize());
+        src.copyTo(src_aux);
+
+        if (is_1d_input && !is_row_dft)
+        {
+            // If the source matrix is the single column
+            // reshape it into single row
+            int rows = std::min(src.rows, src.cols);
+            int cols = src.size().area() / rows;
+            src_aux = GpuMat(rows, cols, src.type(), src_data.ptr(), cols * src.elemSize());
+        }
+    }
+
+    cufftType dft_type = CUFFT_R2C;
+    if (is_complex_input) 
+        dft_type = is_complex_output ? CUFFT_C2C : CUFFT_C2R;
+
+    int dft_cols = src_aux.cols;
+    if (is_complex_input && !is_complex_output)
+        dft_cols = (src_aux.cols - 1) * 2 + (int)odd;
+    CV_Assert(dft_cols > 1);
+
+    cufftHandle plan;
+    if (is_1d_input || is_row_dft)
+        cufftPlan1d(&plan, dft_cols, dft_type, src_aux.rows);
+    else
+        cufftPlan2d(&plan, src_aux.rows, dft_cols, dft_type);
+
+    GpuMat dst_data, dst_aux;
+    int dst_cols, dst_rows;
+    bool is_dst_mem_good;
+
+    if (is_complex_input)
+    {
+        if (is_complex_output)
+        {
+            is_dst_mem_good = dst.isContinuous() && dst.type() == CV_32FC2 
+                              && dst.size().area() >= src.size().area();
+
+            if (is_dst_mem_good)
+                dst_data = dst;
+            else
+            {
+                dst_data.create(1, src.size().area(), CV_32FC2);
+                dst_aux = GpuMat(src.rows, src.cols, dst_data.type(), dst_data.ptr(),
+                                 src.cols * dst_data.elemSize());
+            }
+
+            cufftSafeCall(cufftExecC2C(
+                    plan, src_data.ptr<cufftComplex>(),
+                    dst_data.ptr<cufftComplex>(),
+                    is_inverse ? CUFFT_INVERSE : CUFFT_FORWARD));
+
+            if (!is_dst_mem_good)
+            {
+                dst.create(dst_aux.size(), dst_aux.type());
+                dst_aux.copyTo(dst);
+            }
+        }
+        else
+        {
+            dst_rows = src.rows;
+            dst_cols = (src.cols - 1) * 2 + (int)odd;
+            if (src_aux.size() != src.size())
+            {
+                dst_rows = (src.rows - 1) * 2 + (int)odd;
+                dst_cols = src.cols;
+            }
+
+            is_dst_mem_good = dst.isContinuous() && dst.type() == CV_32F
+                              && dst.rows >= dst_rows && dst.cols >= dst_cols;
+
+            if (is_dst_mem_good)
+                dst_data = dst;
+            else
+            {
+                dst_data.create(1, dst_rows * dst_cols, CV_32F);
+                dst_aux = GpuMat(dst_rows, dst_cols, dst_data.type(), dst_data.ptr(), 
+                                 dst_cols * dst_data.elemSize());
+            }
+
+            cufftSafeCall(cufftExecC2R(
+                    plan, src_data.ptr<cufftComplex>(), dst_data.ptr<cufftReal>()));
+
+            if (!is_dst_mem_good)
+            {
+                dst.create(dst_aux.size(), dst_aux.type());
+                dst_aux.copyTo(dst);
+            }
+        }
+    }
+    else
+    {
+        dst_rows = src.rows;
+        dst_cols = src.cols / 2 + 1;
+        if (src_aux.size() != src.size())
+        {
+            dst_rows = src.rows / 2 + 1;
+            dst_cols = src.cols;
+        }
+
+        is_dst_mem_good = dst.isContinuous() && dst.type() == CV_32FC2 
+                          && dst.rows >= dst_rows && dst.cols >= dst_cols;
+
+        if (is_dst_mem_good)
+            dst_data = dst;
+        else
+        {
+            dst_data.create(1, dst_rows * dst_cols, CV_32FC2);
+            dst_aux = GpuMat(dst_rows, dst_cols, dst_data.type(), dst_data.ptr(), 
+                             dst_cols * dst_data.elemSize());
+        }
+
+        cufftSafeCall(cufftExecR2C(
+                plan, src_data.ptr<cufftReal>(), dst_data.ptr<cufftComplex>()));
+
+        if (!is_dst_mem_good)
+        {
+            dst.create(dst_aux.size(), dst_aux.type());
+            dst_aux.copyTo(dst);
+        }
+    }
+
+    cufftSafeCall(cufftDestroy(plan));
+}
+
 //////////////////////////////////////////////////////////////////////////////
 // crossCorr
 

tests/gpu/src/dft_routines.cpp

@@ -53,13 +53,18 @@ struct CV_GpuMulSpectrumsTest: CvTest
     {
         try
         {
-            if (!test(1 + rand() % 100, 1 + rand() % 1000)) return;
-            if (!testConj(1 + rand() % 100, 1 + rand() % 1000)) return;
-            if (!testScaled(1 + rand() % 100, 1 + rand() % 1000)) return;
-            if (!testScaledConj(1 + rand() % 100, 1 + rand() % 1000)) return;
+            test(0);
+            testConj(0);
+            testScaled(0);
+            testScaledConj(0);
+            test(DFT_ROWS);
+            testConj(DFT_ROWS);
+            testScaled(DFT_ROWS);
+            testScaledConj(DFT_ROWS);
         }
         catch (const Exception& e)
         {
+            ts->printf(CvTS::CONSOLE, e.what());
             if (!check_and_treat_gpu_exception(e, ts)) throw;
             return;
         }
@@ -134,69 +139,225 @@ struct CV_GpuMulSpectrumsTest: CvTest
         return true;
     }
 
-    bool test(int cols, int rows)
+    void test(int flags)
     {
+        int cols = 1 + rand() % 100, rows = 1 + rand() % 1000;
+
         Mat a, b;
         gen(cols, rows, a);
         gen(cols, rows, b);
 
         Mat c_gold;
-        mulSpectrums(a, b, c_gold, 0, false);
+        mulSpectrums(a, b, c_gold, flags, false);
 
         GpuMat d_c;
-        mulSpectrums(GpuMat(a), GpuMat(b), d_c, 0, false);
+        mulSpectrums(GpuMat(a), GpuMat(b), d_c, flags, false);
 
-        return cmp(c_gold, Mat(d_c)) 
-            || (ts->printf(CvTS::CONSOLE, "test failed: cols=%d, rows=%d\n", cols, rows), false);
+        if (!cmp(c_gold, Mat(d_c)))
+            ts->printf(CvTS::CONSOLE, "test failed: cols=%d, rows=%d, flags=%d\n", cols, rows, flags);
     }
 
-    bool testConj(int cols, int rows)
+    void testConj(int flags)
     {
+        int cols = 1 + rand() % 100, rows = 1 + rand() % 1000;
+
         Mat a, b;
         gen(cols, rows, a);
         gen(cols, rows, b);
 
         Mat c_gold;
-        mulSpectrums(a, b, c_gold, 0, true);
+        mulSpectrums(a, b, c_gold, flags, true);
 
         GpuMat d_c;
-        mulSpectrums(GpuMat(a), GpuMat(b), d_c, 0, true);
+        mulSpectrums(GpuMat(a), GpuMat(b), d_c, flags, true);
 
-        return cmp(c_gold, Mat(d_c)) 
-            || (ts->printf(CvTS::CONSOLE, "testConj failed: cols=%d, rows=%d\n", cols, rows), false);
+        if (!cmp(c_gold, Mat(d_c)))
+            ts->printf(CvTS::CONSOLE, "testConj failed: cols=%d, rows=%d, flags=%d\n", cols, rows, flags);
     }
 
-    bool testScaled(int cols, int rows)
+    void testScaled(int flags)
     {
+        int cols = 1 + rand() % 100, rows = 1 + rand() % 1000;
+
         Mat a, b;
         gen(cols, rows, a);
         gen(cols, rows, b);
         float scale = 1.f / a.size().area();
 
         Mat c_gold;
-        mulSpectrums(a, b, c_gold, 0, false);
+        mulSpectrums(a, b, c_gold, flags, false);
 
         GpuMat d_c;
-        mulAndScaleSpectrums(GpuMat(a), GpuMat(b), d_c, 0, scale, false);
+        mulAndScaleSpectrums(GpuMat(a), GpuMat(b), d_c, flags, scale, false);
 
-        return cmpScaled(c_gold, Mat(d_c), scale) 
-            || (ts->printf(CvTS::CONSOLE, "testScaled failed: cols=%d, rows=%d\n", cols, rows), false);
+        if (!cmpScaled(c_gold, Mat(d_c), scale))
+            ts->printf(CvTS::CONSOLE, "testScaled failed: cols=%d, rows=%d, flags=%d\n", cols, rows, flags);
     }
 
-    bool testScaledConj(int cols, int rows)
+    void testScaledConj(int flags)
     {
+        int cols = 1 + rand() % 100, rows = 1 + rand() % 1000;
+
         Mat a, b;
         gen(cols, rows, a);
         gen(cols, rows, b);
         float scale = 1.f / a.size().area();
 
         Mat c_gold;
-        mulSpectrums(a, b, c_gold, 0, true);
+        mulSpectrums(a, b, c_gold, flags, true);
 
         GpuMat d_c;
-        mulAndScaleSpectrums(GpuMat(a), GpuMat(b), d_c, 0, scale, true);
+        mulAndScaleSpectrums(GpuMat(a), GpuMat(b), d_c, flags, scale, true);
+
+        if (!cmpScaled(c_gold, Mat(d_c), scale))
+            ts->printf(CvTS::CONSOLE, "testScaledConj failed: cols=%d, rows=%d, flags=%D\n", cols, rows, flags);
+    }
+} CV_GpuMulSpectrumsTest_inst;
+
+
+struct CV_GpuDftTest: CvTest
+{
+    CV_GpuDftTest(): CvTest("GPU-DftTest", "dft") {}
+
+    void run(int)
+    {
+        try
+        {
+            int cols = 1 + rand() % 100, rows = 1 + rand() % 100;
+
+            testC2C(cols, rows, 0, "no flags");
+            testC2C(cols, rows + 1, 0, "no flags 0 1");
+            testC2C(cols, rows + 1, 0, "no flags 1 0");
+            testC2C(cols + 1, rows, 0, "no flags 1 1");
+            testC2C(cols, rows, DFT_INVERSE, "DFT_INVERSE");
+            testC2C(cols, rows, DFT_ROWS, "DFT_ROWS");
+            testC2C(1, rows, 0, "single col");
+            testC2C(cols, 1, 0, "single row");
+            testC2C(1, rows, DFT_INVERSE, "single col inversed");
+            testC2C(cols, 1, DFT_INVERSE, "single row inversed");
+            testC2C(cols, 1, DFT_ROWS, "single row DFT_ROWS");
+            testC2C(1, 2, 0, "size 1 2");
+            testC2C(2, 1, 0, "size 2 1");
+
+            testR2CThenC2R(cols, rows, "sanity");
+            testR2CThenC2R(cols, rows + 1, "sanity 0 1");
+            testR2CThenC2R(cols + 1, rows, "sanity 1 0");
+            testR2CThenC2R(cols + 1, rows + 1, "sanity 1 1");
+            testR2CThenC2R(1, rows, "single col");
+            testR2CThenC2R(1, rows + 1, "single col 1");
+            testR2CThenC2R(cols, 1, "single row" );;
+            testR2CThenC2R(cols + 1, 1, "single row 1" );;
+        }
+        catch (const Exception& e)
+        {
+            ts->printf(CvTS::CONSOLE, e.what());
+            if (!check_and_treat_gpu_exception(e, ts)) throw;
+            return;
+        }
+    }
+
+    void gen(int cols, int rows, int cn, Mat& mat)
+    {
+        RNG rng;
+        mat.create(rows, cols, CV_MAKETYPE(CV_32F, cn));
+        rng.fill(mat, RNG::UNIFORM, Scalar::all(0.f), Scalar::all(10.f));
+    }
 
-        return cmpScaled(c_gold, Mat(d_c), scale) 
-            || (ts->printf(CvTS::CONSOLE, "testScaledConj failed: cols=%d, rows=%d\n", cols, rows), false);
+    bool cmp(const Mat& gold, const Mat& mine, float max_err=1e-3f, float scale=1.f)
+    {
+        if (gold.size() != mine.size())
+        {
+            ts->printf(CvTS::CONSOLE, "bad sizes: gold: %d %d, mine: %d %d\n", gold.cols, gold.rows, mine.cols, mine.rows);
+            ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+            return false;
+        }
+        if (gold.depth() != mine.depth())
+        {
+            ts->printf(CvTS::CONSOLE, "bad depth: gold=%d, mine=%d\n", gold.depth(), mine.depth());
+            ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+            return false;
+        }
+        if (gold.channels() != mine.channels())
+        {
+            ts->printf(CvTS::CONSOLE, "bad channel count: gold=%d, mine=%d\n", gold.channels(), mine.channels());
+            ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+            return false;
+        }
+        for (int i = 0; i < gold.rows; ++i)
+        {
+            for (int j = 0; j < gold.cols * gold.channels(); ++j)
+            {
+                float gold_ = gold.at<float>(i, j);
+                float mine_ = mine.at<float>(i, j) * scale;
+                if (fabs(gold_ - mine_) > max_err)
+                {
+                    ts->printf(CvTS::CONSOLE, "bad values at %d %d: gold=%f, mine=%f\n", j / gold.channels(), i, gold_, mine_);
+                    ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+                    return false;
+                }
+            }
+        }
+        return true;
+    }
+
+    void testC2C(int cols, int rows, int flags, const std::string& hint)
+    {
+        Mat a;
+        gen(cols, rows, 2, a);
+
+        Mat b_gold;
+        dft(a, b_gold, flags);
+
+        GpuMat d_b;
+        dft(GpuMat(a), d_b, flags);
+
+        bool ok = true;
+        if (ok && d_b.depth() != CV_32F)
+        {
+            ts->printf(CvTS::CONSOLE, "bad depth: %d\n", d_b.depth());
+            ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+            ok = false;
+        }
+        if (ok && d_b.channels() != 2)
+        {
+            ts->printf(CvTS::CONSOLE, "bad channel count: %d\n", d_b.channels());
+            ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+            ok = false;
+        }
+        if (ok) ok = cmp(b_gold, Mat(d_b), rows * cols * 1e-5f);
+        if (!ok) 
+            ts->printf(CvTS::CONSOLE, "testC2C failed: hint=%s, cols=%d, rows=%d, flags=%d\n", hint.c_str(), cols, rows, flags);
+    }
+
+    void testR2CThenC2R(int cols, int rows, const std::string& hint)
+    {
+        Mat a;
+        gen(cols, rows, 1, a);
+
+        bool odd = false;
+        if (a.cols == 1) odd = a.rows % 2 == 1;
+        else odd = a.cols % 2 == 1;
+        bool ok = true;
+
+        GpuMat d_b;
+        GpuMat d_c;
+        dft(GpuMat(a), d_b, 0);
+        dft(d_b, d_c, DFT_REAL_OUTPUT, 0, odd);
+
+        if (ok && d_c.depth() != CV_32F)
+        {
+            ts->printf(CvTS::CONSOLE, "bad depth: %d\n", d_c.depth());
+            ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+            ok = false;
+        }
+        if (ok && d_c.channels() != 1)
+        {
+            ts->printf(CvTS::CONSOLE, "bad channel count: %d\n", d_c.channels());
+            ts->set_failed_test_info(CvTS::FAIL_INVALID_OUTPUT);
+            ok = false;
+        }
+        if (ok) ok = cmp(a, Mat(d_c), rows * cols * 1e-5f, 1.f / (rows * cols));
+        if (!ok) 
+            ts->printf(CvTS::CONSOLE, "testR2CThenC2R failed: hint=%s, cols=%d, rows=%d\n", hint.c_str(), cols, rows);
     }
-} CV_GpuMulSpectrumsTest_inst;
+} CV_GpuDftTest_inst;