Complete (but inefficient) implementation of the image retargetting method.

skia/ext/convolver_unittest.cc

Index: skia/ext/convolver_unittest.cc
diff --git a/skia/ext/convolver_unittest.cc b/skia/ext/convolver_unittest.cc
index f61b685daf5e748da8e9f584dcf3d427c1d0f6f4..9acba1c2233a89d0bb3f3be21083ffe324f6b75b 100644
--- a/skia/ext/convolver_unittest.cc
+++ b/skia/ext/convolver_unittest.cc
@@ -318,4 +318,57 @@ TEST(Convolver, SIMDVerification) {
 #endif
 }
 
+TEST(Convolver, SeparableSingleConvolution) {
+  static const int kSize = 1024;
+  static const int kChannelCount = 3;
+  static const int kStrideSlack = 22;
+  ConvolutionFilter1D filter;
+  const float box[5] = { 0.2, 0.2, 0.2, 0.2, 0.2 };
+  filter.AddFilter(0, box, 5);
+
+  // Allocate a source image and set to 0.
+  int img_width = kSize;
+  int img_height = kSize;
+  int src_row_stride = img_width * kChannelCount + kStrideSlack;
+  int src_byte_count = src_row_stride * img_height;
+  std::vector<unsigned char> input;
+  int signal_x = img_width / 2;
+  int signal_y = img_height / 2;
+  input.resize(src_byte_count, 0);
+  // The image has a single impulse pixel in channel 1, smack in the middle.
+  int non_zero_pixel_index =
+      signal_y * src_row_stride + signal_x * kChannelCount + 1;
+  input[non_zero_pixel_index] = 255;
+
+  // Destination will be a single channel image with stide matching width.
+  int dest_row_stride = img_width;
+  int dest_byte_count = dest_row_stride * img_height;
+  std::vector<unsigned char> output;
+  output.resize(dest_byte_count);
+
+  // Apply convolution in X.
+  SingleChannelConvolve1D_X(&input[0], src_row_stride, 1, kChannelCount,
+                            filter, SkISize::Make(img_width, img_height),
+                            &output[0], dest_row_stride, 0, 1, false);
+  for (int x = signal_x - 2; x <= signal_x + 2; ++x) {
+    EXPECT_GT(output[signal_y * dest_row_stride + x], 0);
+  }
+  EXPECT_EQ(output[signal_y * dest_row_stride + signal_x - 3], 0);
+  EXPECT_EQ(output[signal_y * dest_row_stride + signal_x + 3], 0);
+
+  // Apply convolution in Y.
+  SingleChannelConvolve1D_Y(&input[0], src_row_stride, 1, kChannelCount,
+                            filter, SkISize::Make(img_width, img_height),
+                            &output[0], dest_row_stride, 0, 1, false);
+  for (int y = signal_y - 2; y <= signal_y + 2; ++y) {
+    EXPECT_GT(output[y * dest_row_stride + signal_x], 0);
+  }
+
+  EXPECT_EQ(output[(signal_y - 3) * dest_row_stride + signal_x], 0);
+  EXPECT_EQ(output[(signal_y + 3) * dest_row_stride + signal_x], 0);
+
+  EXPECT_EQ(output[signal_y * dest_row_stride + signal_x - 1], 0);
+  EXPECT_EQ(output[signal_y * dest_row_stride + signal_x + 1], 0);
+}
+
 }  // namespace skia