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Add TensorsToSegmentationCalculator test utilities.
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111 changes: 111 additions & 0 deletions
111
mediapipe/calculators/tensor/tensors_to_segmentation_calculator_test_utils.cc
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| // Copyright 2023 The MediaPipe Authors. | ||
| // | ||
| // 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. | ||
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| #include "mediapipe/calculators/tensor/tensors_to_segmentation_calculator_test_utils.h" | ||
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| #include <string> | ||
| #include <vector> | ||
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| #include "absl/log/absl_log.h" | ||
| #include "absl/strings/substitute.h" | ||
| #include "mediapipe/calculators/tensor/tensors_to_segmentation_calculator.pb.h" | ||
| #include "mediapipe/framework/calculator.pb.h" | ||
| #include "mediapipe/framework/port/parse_text_proto.h" | ||
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| namespace mediapipe { | ||
| namespace tensors_to_segmentation_utils { | ||
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| std::string ActivationTypeToString( | ||
| const TensorsToSegmentationCalculatorOptions::Activation& activation) { | ||
| switch (activation) { | ||
| case TensorsToSegmentationCalculatorOptions::NONE: | ||
| return "NONE"; | ||
| case TensorsToSegmentationCalculatorOptions::SIGMOID: | ||
| return "SIGMOID"; | ||
| case TensorsToSegmentationCalculatorOptions::SOFTMAX: | ||
| return "SOFTMAX"; | ||
| } | ||
| ABSL_LOG(FATAL) << "Unknown activation type: " << activation; | ||
| return "UNKNOWN"; | ||
| } | ||
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| std::vector<unsigned char> ArrayFloatToUnsignedChar( | ||
| const std::vector<float>& array) { | ||
| std::vector<unsigned char> result; | ||
| result.reserve(array.size()); | ||
| for (int i = 0; i < array.size(); ++i) { | ||
| result.push_back(static_cast<unsigned char>(array[i])); | ||
| } | ||
| return result; | ||
| } | ||
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| std::vector<float> MakeRedAlphaMatrix(const std::vector<float>& values) { | ||
| std::vector<float> result; | ||
| result.reserve(values.size() * 4); | ||
| for (const float& value : values) { | ||
| result.push_back(value); | ||
| result.push_back(0); | ||
| result.push_back(0); | ||
| result.push_back(value); | ||
| } | ||
| return result; | ||
| } | ||
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| // For GPU tests, the input tensor needs to be moved to GPU, using | ||
| // TensorViewRequestor. After calculation, the output needs to be moved back | ||
| // to CPU, using ToImageCalculator. The output is an ImageFrame. | ||
| mediapipe::CalculatorGraphConfig CreateGraphConfigForTest( | ||
| bool test_gpu, | ||
| const TensorsToSegmentationCalculatorOptions::Activation& activation) { | ||
| std::string pre_process = R"pb( | ||
| node { | ||
| calculator: "mediapipe.aimatter.TensorViewRequestor" | ||
| input_stream: "TENSORS:tensors" | ||
| output_stream: "TENSORS:tensors_gpu" | ||
| options { | ||
| [mediapipe.aimatter.TensorViewRequestorOptions.ext] { gpu {} } | ||
| } | ||
| } | ||
| )pb"; | ||
| std::string post_process = R"pb( | ||
| node { | ||
| calculator: "FromImageCalculator" | ||
| input_stream: "IMAGE:image_as_mask_gpu" | ||
| output_stream: "IMAGE_CPU:image_as_mask" | ||
| } | ||
| )pb"; | ||
| return mediapipe::ParseTextProtoOrDie<mediapipe::CalculatorGraphConfig>( | ||
| absl::Substitute( | ||
| R"pb( | ||
| input_stream: "tensors" | ||
| input_stream: "size" $0 | ||
| node { | ||
| calculator: "TensorsToSegmentationCalculator" | ||
| input_stream: "TENSORS:tensors$1" | ||
| input_stream: "OUTPUT_SIZE:size" | ||
| output_stream: "MASK:image_as_mask$2" | ||
| options: { | ||
| [mediapipe.TensorsToSegmentationCalculatorOptions.ext] { | ||
| activation: $3 | ||
| gpu_origin: TOP_LEFT | ||
| } | ||
| } | ||
| } $4 | ||
| )pb", | ||
| test_gpu ? pre_process : "", test_gpu ? "_gpu" : "", | ||
| test_gpu ? "_gpu" : "", ActivationTypeToString(activation), | ||
| test_gpu ? post_process : "")); | ||
| } | ||
| } // namespace tensors_to_segmentation_utils | ||
| } // namespace mediapipe |
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mediapipe/calculators/tensor/tensors_to_segmentation_calculator_test_utils.h
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| // Copyright 2023 The MediaPipe Authors. | ||
| // | ||
| // 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. | ||
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| #ifndef MEDIAPIPE_CALCULATORS_TENSOR_TENSORS_TO_SEGMENTATION_CALCULATOR_TEST_UTILS_H_ | ||
| #define MEDIAPIPE_CALCULATORS_TENSOR_TENSORS_TO_SEGMENTATION_CALCULATOR_TEST_UTILS_H_ | ||
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| #include <memory> | ||
| #include <string> | ||
| #include <utility> | ||
| #include <vector> | ||
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| #include "mediapipe/calculators/tensor/tensors_to_segmentation_calculator.pb.h" | ||
| #include "mediapipe/framework/calculator.pb.h" | ||
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| namespace mediapipe { | ||
| namespace tensors_to_segmentation_utils { | ||
| std::string ActivationTypeToString( | ||
| const mediapipe::TensorsToSegmentationCalculatorOptions::Activation& | ||
| activation); | ||
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| std::vector<unsigned char> ArrayFloatToUnsignedChar( | ||
| const std::vector<float>& array); | ||
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| std::vector<float> MakeRedAlphaMatrix(const std::vector<float>& values); | ||
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| mediapipe::CalculatorGraphConfig CreateGraphConfigForTest( | ||
| bool test_gpu, | ||
| const mediapipe::TensorsToSegmentationCalculatorOptions::Activation& | ||
| activation); | ||
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| struct FormattingTestCase { | ||
| std::string test_name; | ||
| std::vector<float> inputs; | ||
| std::vector<float> expected_outputs; | ||
| mediapipe::TensorsToSegmentationCalculatorOptions::Activation activation; | ||
| int rows = 1; | ||
| int cols = 1; | ||
| int rows_new = 1; | ||
| int cols_new = 1; | ||
| int channels = 1; | ||
| double max_abs_diff = 1e-7; | ||
| }; | ||
| } // namespace tensors_to_segmentation_utils | ||
| } // namespace mediapipe | ||
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| #endif // MEDIAPIPE_CALCULATORS_TENSOR_TENSORS_TO_SEGMENTATION_CALCULATOR_TEST_UTILS_H_ |
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mediapipe/calculators/tensor/tensors_to_segmentation_calculator_test_utils_test.cc
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| @@ -0,0 +1,50 @@ | ||
| // Copyright 2023 The MediaPipe Authors. | ||
| // | ||
| // 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. | ||
|
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| #include "mediapipe/calculators/tensor/tensors_to_segmentation_calculator_test_utils.h" | ||
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| #include <vector> | ||
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| #include "mediapipe/calculators/tensor/tensors_to_segmentation_calculator.pb.h" | ||
| #include "mediapipe/framework/port/gtest.h" | ||
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| namespace mediapipe::tensors_to_segmentation_utils { | ||
| namespace { | ||
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| using Options = ::mediapipe::TensorsToSegmentationCalculatorOptions; | ||
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| TEST(TensorsToSegmentationCalculatorTestUtilsTest, | ||
| ActivationTypeToStringWorksCorrectly) { | ||
| EXPECT_EQ(ActivationTypeToString(Options::NONE), "NONE"); | ||
| EXPECT_EQ(ActivationTypeToString(Options::SIGMOID), "SIGMOID"); | ||
| EXPECT_EQ(ActivationTypeToString(Options::SOFTMAX), "SOFTMAX"); | ||
| } | ||
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| TEST(TensorsToSegmentationCalculatorTestUtilsTest, | ||
| ArrayFloatToUnsignedCharWorksCorrectly) { | ||
| std::vector<float> input = {1.0, 2.0, 3.0}; | ||
| std::vector<unsigned char> expected = {1, 2, 3}; | ||
| EXPECT_EQ(ArrayFloatToUnsignedChar(input), expected); | ||
| } | ||
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| TEST(TensorsToSegmentationCalculatorTestUtilsTest, | ||
| MakeRedAlphaMatrixWorksCorrectly) { | ||
| std::vector<float> input = {1.0, 2.0, 3.0}; | ||
| std::vector<float> expected = {1.0, 0.0, 0.0, 1.0, 2.0, 0.0, | ||
| 0.0, 2.0, 3.0, 0.0, 0.0, 3.0}; | ||
| EXPECT_EQ(MakeRedAlphaMatrix(input), expected); | ||
| } | ||
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| } // namespace | ||
| } // namespace mediapipe::tensors_to_segmentation_utils |