// (C) Copyright 2017, Google Inc. // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // http://www.apache.org/licenses/LICENSE-2.0 // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. #include "include_gunit.h" #include "networkio.h" #include "stridemap.h" #ifdef INCLUDE_TENSORFLOW #include // for xla::Array2D #endif namespace tesseract { class NetworkioTest : public ::testing::Test { protected: void SetUp() override { std::locale::global(std::locale("")); } #ifdef INCLUDE_TENSORFLOW // Sets up an Array2d object of the given size, initialized to increasing // values starting with start. std::unique_ptr> SetupArray(int ysize, int xsize, int start) { std::unique_ptr> a(new xla::Array2D(ysize, xsize)); int value = start; for (int y = 0; y < ysize; ++y) { for (int x = 0; x < xsize; ++x) { (*a)(y, x) = value++; } } return a; } // Sets up a NetworkIO with a batch of 2 "images" of known values. void SetupNetworkIO(NetworkIO* nio) { std::vector>> arrays; arrays.push_back(SetupArray(3, 4, 0)); arrays.push_back(SetupArray(4, 5, 12)); std::vector> h_w_sizes; for (size_t i = 0; i < arrays.size(); ++i) { h_w_sizes.emplace_back(arrays[i].get()->height(), arrays[i].get()->width()); } StrideMap stride_map; stride_map.SetStride(h_w_sizes); nio->ResizeToMap(true, stride_map, 2); // Iterate over the map, setting nio's contents from the arrays. StrideMap::Index index(stride_map); do { int value = (*arrays[index.index(FD_BATCH)])(index.index(FD_HEIGHT), index.index(FD_WIDTH)); nio->SetPixel(index.t(), 0, 128 + value, 0.0f, 128.0f); nio->SetPixel(index.t(), 1, 128 - value, 0.0f, 128.0f); } while (index.Increment()); } #endif }; // Tests that the initialization via SetPixel works and the resize correctly // fills with zero where image sizes don't match. TEST_F(NetworkioTest, InitWithZeroFill) { #ifdef INCLUDE_TENSORFLOW NetworkIO nio; nio.Resize2d(true, 32, 2); int width = nio.Width(); for (int t = 0; t < width; ++t) { nio.SetPixel(t, 0, 0, 0.0f, 128.0f); nio.SetPixel(t, 1, 0, 0.0f, 128.0f); } // The initialization will wipe out all previously set values. SetupNetworkIO(&nio); nio.ZeroInvalidElements(); StrideMap::Index index(nio.stride_map()); int next_t = 0; int pos = 0; do { int t = index.t(); // The indexed values just increase monotonically. int value = nio.i(t)[0]; EXPECT_EQ(value, pos); value = nio.i(t)[1]; EXPECT_EQ(value, -pos); // When we skip t values, the data is always 0. while (next_t < t) { EXPECT_EQ(nio.i(next_t)[0], 0); EXPECT_EQ(nio.i(next_t)[1], 0); ++next_t; } ++pos; ++next_t; } while (index.Increment()); EXPECT_EQ(pos, 32); EXPECT_EQ(next_t, 40); #else LOG(INFO) << "Skip test because of missing xla::Array2D"; GTEST_SKIP(); #endif } // Tests that CopyWithYReversal works. TEST_F(NetworkioTest, CopyWithYReversal) { #ifdef INCLUDE_TENSORFLOW NetworkIO nio; SetupNetworkIO(&nio); NetworkIO copy; copy.CopyWithYReversal(nio); StrideMap::Index index(copy.stride_map()); int next_t = 0; int pos = 0; std::vector expected_values = { 8, 9, 10, 11, 4, 5, 6, 7, 0, 1, 2, 3, 27, 28, 29, 30, 31, 22, 23, 24, 25, 26, 17, 18, 19, 20, 21, 12, 13, 14, 15, 16}; do { int t = index.t(); // The indexed values match the expected values. int value = copy.i(t)[0]; EXPECT_EQ(value, expected_values[pos]); value = copy.i(t)[1]; EXPECT_EQ(value, -expected_values[pos]); // When we skip t values, the data is always 0. while (next_t < t) { EXPECT_EQ(copy.i(next_t)[0], 0) << "Failure t = " << next_t; EXPECT_EQ(copy.i(next_t)[1], 0) << "Failure t = " << next_t; ++next_t; } ++pos; ++next_t; } while (index.Increment()); EXPECT_EQ(pos, 32); EXPECT_EQ(next_t, 40); #else LOG(INFO) << "Skip test because of missing xla::Array2D"; GTEST_SKIP(); #endif } // Tests that CopyWithXReversal works. TEST_F(NetworkioTest, CopyWithXReversal) { #ifdef INCLUDE_TENSORFLOW NetworkIO nio; SetupNetworkIO(&nio); NetworkIO copy; copy.CopyWithXReversal(nio); StrideMap::Index index(copy.stride_map()); int next_t = 0; int pos = 0; std::vector expected_values = { 3, 2, 1, 0, 7, 6, 5, 4, 11, 10, 9, 8, 16, 15, 14, 13, 12, 21, 20, 19, 18, 17, 26, 25, 24, 23, 22, 31, 30, 29, 28, 27}; do { int t = index.t(); // The indexed values match the expected values. int value = copy.i(t)[0]; EXPECT_EQ(value, expected_values[pos]); value = copy.i(t)[1]; EXPECT_EQ(value, -expected_values[pos]); // When we skip t values, the data is always 0. while (next_t < t) { EXPECT_EQ(copy.i(next_t)[0], 0) << "Failure t = " << next_t; EXPECT_EQ(copy.i(next_t)[1], 0) << "Failure t = " << next_t; ++next_t; } ++pos; ++next_t; } while (index.Increment()); EXPECT_EQ(pos, 32); EXPECT_EQ(next_t, 40); #else LOG(INFO) << "Skip test because of missing xla::Array2D"; GTEST_SKIP(); #endif } // Tests that CopyWithXYTranspose works. TEST_F(NetworkioTest, CopyWithXYTranspose) { #ifdef INCLUDE_TENSORFLOW NetworkIO nio; SetupNetworkIO(&nio); NetworkIO copy; copy.CopyWithXYTranspose(nio); StrideMap::Index index(copy.stride_map()); int next_t = 0; int pos = 0; std::vector expected_values = { 0, 4, 8, 1, 5, 9, 2, 6, 10, 3, 7, 11, 12, 17, 22, 27, 13, 18, 23, 28, 14, 19, 24, 29, 15, 20, 25, 30, 16, 21, 26, 31}; do { int t = index.t(); // The indexed values match the expected values. int value = copy.i(t)[0]; EXPECT_EQ(value, expected_values[pos]); value = copy.i(t)[1]; EXPECT_EQ(value, -expected_values[pos]); // When we skip t values, the data is always 0. while (next_t < t) { EXPECT_EQ(copy.i(next_t)[0], 0); EXPECT_EQ(copy.i(next_t)[1], 0); ++next_t; } ++pos; ++next_t; } while (index.Increment()); EXPECT_EQ(pos, 32); EXPECT_EQ(next_t, 40); #else LOG(INFO) << "Skip test because of missing xla::Array2D"; GTEST_SKIP(); #endif } } // namespace