diff --git a/mediapipe/calculators/tensor/tensors_to_segmentation_calculator_test.cc b/mediapipe/calculators/tensor/tensors_to_segmentation_calculator_test.cc index 14c132e77..e5c6b8ade 100644 --- a/mediapipe/calculators/tensor/tensors_to_segmentation_calculator_test.cc +++ b/mediapipe/calculators/tensor/tensors_to_segmentation_calculator_test.cc @@ -152,103 +152,96 @@ TEST_P(TensorsToSegmentationCalculatorTest, ParameterizedTests) { INSTANTIATE_TEST_SUITE_P( TensorsToSegmentationCalculatorTests, TensorsToSegmentationCalculatorTest, testing::ValuesIn({ - {/*test_name=*/"NoActivationAndNoOutputResize", - /*inputs=*/ - {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, - 14.0, 15.0, 16.0}, - /*expected_outputs=*/ - {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, - 14.0, 15.0, 16.0}, - /*activation=*/Options::NONE, - /*rows=*/4, - /*cols=*/4, - /*rows_new=*/4, - /*cols_new=*/4, - /*channels=*/1, - /*max_abs_diff=*/1e-7}, - {/*test_name=*/"OutputResizeOnly", - /*inputs=*/ - {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, - 14.0, 15.0, 16.0}, - /*expected_outputs=*/ - {1, 1.5, 2.166667, 2.833333, 3.5, 4, - 3.8, 4.3, 4.966667, 5.633333, 6.3, 6.8, - 7, 7.5, 8.166667, 8.833333, 9.5, 10, - 10.2, 10.7, 11.366667, 12.033333, 12.7, 13.2, - 13, 13.5, 14.166667, 14.833333, 15.5, 16}, - /*activation=*/Options::NONE, - /*rows=*/4, - /*cols=*/4, - /*rows_new=*/5, - /*cols_new=*/6, - /*channels=*/1, - /*max_abs_diff=*/1e-6}, - {/*test_name=*/"SigmoidActivationWithNoOutputResize", - /*inputs=*/ - {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, - 14.0, 15.0, 16.0}, - /*expected_outputs=*/ - {0.731059, 0.880797, 0.952574, 0.982014, 0.993307, 0.997527, 0.999089, - 0.999665, 0.999877, 0.999955, 0.999983, 0.999994, 0.999998, 0.999999, - 1.0, 1.0}, - /*activation=*/Options::SIGMOID, - /*rows=*/4, - /*cols=*/4, - /*rows_new=*/4, - /*cols_new=*/4, - /*channels=*/1, - /*max_abs_diff=*/1e-6}, - {/*test_name=*/"SigmoidActivationWithOutputResize", - /*inputs=*/ - {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0, 13.0, - 14.0, 15.0, 16.0}, - /*expected_outputs=*/ - {0.731059, 0.805928, 0.89276, 0.940611, 0.967294, 0.982014, - 0.914633, 0.93857, 0.966279, 0.981363, 0.989752, 0.994369, - 0.996592, 0.997666, 0.998873, 0.999404, 0.999683, 0.999829, - 0.999913, 0.99994, 0.999971, 0.999985, 0.999992, 0.999996, - 0.999998, 0.999998, 0.999999, 1.0, 1.0, 1.0}, - /*activation=*/Options::SIGMOID, - /*rows=*/4, - /*cols=*/4, - /*rows_new=*/5, - /*cols_new=*/6, - /*channels=*/1, - /*max_abs_diff=*/1e-6}, - {/*test_name=*/"SoftmaxActivationWithNoOutputResize", - /*inputs=*/ - {1.0, 2.0, 4.0, 2.0, 3.0, 5.0, 6.0, 1.5, 7.0, 10.0, 11.0, - 4.0, 12.0, 15.0, 16.0, 18.5, 19.0, 20.0, 22.0, 23.0, 24.5, 23.4, - 25.6, 28.3, 29.2, 30.0, 24.6, 29.2, 30.0, 24.9, 31.2, 30.3}, - /*expected_outputs=*/ - {0.731059, 0.119203, 0.880797, 0.0109869, 0.952574, 0.000911051, - 0.952574, 0.924142, 0.731059, 0.731059, 0.24974, 0.937027, 0.689974, - 0.990048, 0.0060598, 0.28905}, - /*activation=*/Options::SOFTMAX, - /*rows=*/4, - /*cols=*/4, - /*rows_new=*/4, - /*cols_new=*/4, - /*channels=*/2, - /*max_abs_diff=*/1e-6}, - {/*test_name=*/"SoftmaxActivationWithOutputResize", - /*inputs=*/ - {1.0, 2.0, 4.0, 2.0, 3.0, 5.0, 6.0, 1.5, 7.0, 10.0, 11.0, - 4.0, 12.0, 15.0, 16.0, 18.5, 19.0, 20.0, 22.0, 23.0, 24.5, 23.4, - 25.6, 28.3, 29.2, 30.0, 24.6, 29.2, 30.0, 24.9, 31.2, 30.3}, - /*expected_outputs=*/ - {0.731059, 0.425131, 0.246135, 0.753865, 0.445892, 0.0109869, - 0.886119, 0.461259, 0.185506, 0.781934, 0.790618, 0.650195, - 0.841816, 0.603901, 0.40518, 0.561962, 0.765871, 0.930584, - 0.718733, 0.763744, 0.703402, 0.281989, 0.459635, 0.742634, - 0.689974, 0.840011, 0.82605, 0.170058, 0.147555, 0.28905}, - /*activation=*/Options::SOFTMAX, - /*rows=*/4, - /*cols=*/4, - /*rows_new=*/5, - /*cols_new=*/6, - /*channels=*/2, - /*max_abs_diff=*/1e-6}, + {.test_name = "NoActivationAndNoOutputResize", + .inputs = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, + 12.0, 13.0, 14.0, 15.0, 16.0}, + .expected_outputs = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, + 11.0, 12.0, 13.0, 14.0, 15.0, 16.0}, + .activation = Options::NONE, + .rows = 4, + .cols = 4, + .rows_new = 4, + .cols_new = 4, + .channels = 1, + .max_abs_diff = 1e-7}, + {.test_name = "OutputResizeOnly", + .inputs = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, + 12.0, 13.0, 14.0, 15.0, 16.0}, + .expected_outputs = {1, 1.5, 2.166667, 2.833333, 3.5, 4, + 3.8, 4.3, 4.966667, 5.633333, 6.3, 6.8, + 7, 7.5, 8.166667, 8.833333, 9.5, 10, + 10.2, 10.7, 11.366667, 12.033333, 12.7, 13.2, + 13, 13.5, 14.166667, 14.833333, 15.5, 16}, + .activation = Options::NONE, + .rows = 4, + .cols = 4, + .rows_new = 5, + .cols_new = 6, + .channels = 1, + .max_abs_diff = 1e-6}, + {.test_name = "SigmoidActivationWithNoOutputResize", + .inputs = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, + 12.0, 13.0, 14.0, 15.0, 16.0}, + .expected_outputs = {0.731059, 0.880797, 0.952574, 0.982014, 0.993307, + 0.997527, 0.999089, 0.999665, 0.999877, 0.999955, + 0.999983, 0.999994, 0.999998, 0.999999, 1.0, 1.0}, + .activation = Options::SIGMOID, + .rows = 4, + .cols = 4, + .rows_new = 4, + .cols_new = 4, + .channels = 1, + .max_abs_diff = 1e-6}, + {.test_name = "SigmoidActivationWithOutputResize", + .inputs = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, + 12.0, 13.0, 14.0, 15.0, 16.0}, + .expected_outputs = {0.731059, 0.805928, 0.89276, 0.940611, 0.967294, + 0.982014, 0.914633, 0.93857, 0.966279, 0.981363, + 0.989752, 0.994369, 0.996592, 0.997666, 0.998873, + 0.999404, 0.999683, 0.999829, 0.999913, 0.99994, + 0.999971, 0.999985, 0.999992, 0.999996, 0.999998, + 0.999998, 0.999999, 1.0, 1.0, 1.0}, + .activation = Options::SIGMOID, + .rows = 4, + .cols = 4, + .rows_new = 5, + .cols_new = 6, + .channels = 1, + .max_abs_diff = 1e-6}, + {.test_name = "SoftmaxActivationWithNoOutputResize", + .inputs = {1.0, 2.0, 4.0, 2.0, 3.0, 5.0, 6.0, 1.5, + 7.0, 10.0, 11.0, 4.0, 12.0, 15.0, 16.0, 18.5, + 19.0, 20.0, 22.0, 23.0, 24.5, 23.4, 25.6, 28.3, + 29.2, 30.0, 24.6, 29.2, 30.0, 24.9, 31.2, 30.3}, + .expected_outputs = {0.731059, 0.119203, 0.880797, 0.0109869, 0.952574, + 0.000911051, 0.952574, 0.924142, 0.731059, + 0.731059, 0.24974, 0.937027, 0.689974, 0.990048, + 0.0060598, 0.28905}, + .activation = Options::SOFTMAX, + .rows = 4, + .cols = 4, + .rows_new = 4, + .cols_new = 4, + .channels = 2, + .max_abs_diff = 1e-6}, + {.test_name = "SoftmaxActivationWithOutputResize", + .inputs = {1.0, 2.0, 4.0, 2.0, 3.0, 5.0, 6.0, 1.5, + 7.0, 10.0, 11.0, 4.0, 12.0, 15.0, 16.0, 18.5, + 19.0, 20.0, 22.0, 23.0, 24.5, 23.4, 25.6, 28.3, + 29.2, 30.0, 24.6, 29.2, 30.0, 24.9, 31.2, 30.3}, + .expected_outputs = {0.731059, 0.425131, 0.246135, 0.753865, 0.445892, + 0.0109869, 0.886119, 0.461259, 0.185506, 0.781934, + 0.790618, 0.650195, 0.841816, 0.603901, 0.40518, + 0.561962, 0.765871, 0.930584, 0.718733, 0.763744, + 0.703402, 0.281989, 0.459635, 0.742634, 0.689974, + 0.840011, 0.82605, 0.170058, 0.147555, 0.28905}, + .activation = Options::SOFTMAX, + .rows = 4, + .cols = 4, + .rows_new = 5, + .cols_new = 6, + .channels = 2, + .max_abs_diff = 1e-6}, }), [](const testing::TestParamInfo< TensorsToSegmentationCalculatorTest::ParamType>& info) {