Add TensorsToSegmentationCalculator test utilities.
PiperOrigin-RevId: 586817713
This commit is contained in:
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7013b23785
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@ -1555,12 +1555,37 @@ cc_library(
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],
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)
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cc_library(
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name = "tensors_to_segmentation_calculator_test_utils",
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testonly = 1,
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srcs = ["tensors_to_segmentation_calculator_test_utils.cc"],
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hdrs = ["tensors_to_segmentation_calculator_test_utils.h"],
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deps = [
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":tensors_to_segmentation_calculator_cc_proto",
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"//mediapipe/framework:calculator_cc_proto",
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"//mediapipe/framework/port:parse_text_proto",
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"@com_google_absl//absl/log:absl_log",
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"@com_google_absl//absl/strings",
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],
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)
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cc_test(
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name = "tensors_to_segmentation_calculator_test_utils_test",
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srcs = ["tensors_to_segmentation_calculator_test_utils_test.cc"],
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deps = [
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":tensors_to_segmentation_calculator_cc_proto",
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":tensors_to_segmentation_calculator_test_utils",
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"//mediapipe/framework/port:gtest_main",
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],
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)
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cc_test(
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name = "tensors_to_segmentation_calculator_test",
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srcs = ["tensors_to_segmentation_calculator_test.cc"],
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deps = [
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":tensors_to_segmentation_calculator",
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":tensors_to_segmentation_calculator_cc_proto",
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":tensors_to_segmentation_calculator_test_utils",
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"//mediapipe/framework:calculator_framework",
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"//mediapipe/framework:calculator_runner",
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"//mediapipe/framework:packet",
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@ -1571,10 +1596,6 @@ cc_test(
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"//mediapipe/framework/formats:rect_cc_proto",
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"//mediapipe/framework/formats:tensor",
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"//mediapipe/framework/port:gtest_main",
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"//mediapipe/framework/port:parse_text_proto",
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"@com_google_absl//absl/log",
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"@com_google_absl//absl/log:absl_log",
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"@com_google_absl//absl/strings",
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],
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)
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@ -17,10 +17,8 @@
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#include <utility>
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#include <vector>
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#include "absl/log/absl_log.h"
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#include "absl/log/log.h"
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#include "absl/strings/substitute.h"
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#include "mediapipe/calculators/tensor/tensors_to_segmentation_calculator.pb.h"
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#include "mediapipe/calculators/tensor/tensors_to_segmentation_calculator_test_utils.h"
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#include "mediapipe/framework/calculator_framework.h"
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#include "mediapipe/framework/calculator_runner.h"
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#include "mediapipe/framework/formats/image.h"
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@ -30,7 +28,6 @@
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#include "mediapipe/framework/formats/tensor.h"
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#include "mediapipe/framework/packet.h"
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#include "mediapipe/framework/port/gtest.h"
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#include "mediapipe/framework/port/parse_text_proto.h"
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#include "mediapipe/framework/port/status_matchers.h"
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#include "mediapipe/framework/timestamp.h"
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@ -40,58 +37,17 @@ namespace {
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using ::testing::SizeIs;
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using ::testing::TestWithParam;
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using Options = mediapipe::TensorsToSegmentationCalculatorOptions;
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namespace test_utils = ::mediapipe::tensors_to_segmentation_utils;
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std::string ActivationTypeToString(Options::Activation activation) {
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switch (activation) {
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case Options::NONE:
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return "NONE";
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case Options::SIGMOID:
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return "SIGMOID";
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case Options::SOFTMAX:
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return "SOFTMAX";
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default:
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ABSL_LOG(FATAL) << "Unknown activation type: " << activation;
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return "UNKNOWN";
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}
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}
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struct FormattingTestCase {
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std::string test_name;
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std::vector<float> inputs;
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std::vector<float> expected_outputs;
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Options::Activation activation;
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int rows = 1;
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int cols = 1;
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int rows_new = 1;
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int cols_new = 1;
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int channels = 1;
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double max_abs_diff = 1e-7;
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};
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using TensorsToSegmentationCalculatorTest = TestWithParam<FormattingTestCase>;
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using TensorsToSegmentationCalculatorTest =
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TestWithParam<test_utils::FormattingTestCase>;
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TEST_P(TensorsToSegmentationCalculatorTest, ParameterizedTests) {
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const auto& [test_name, inputs, expected_outputs, activation, rows, cols,
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rows_new, cols_new, channels, max_abs_diff] = GetParam();
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auto graph_config =
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mediapipe::ParseTextProtoOrDie<CalculatorGraphConfig>(absl::Substitute(
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R"pb(
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input_stream: "tensors"
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input_stream: "size"
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node {
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calculator: "TensorsToSegmentationCalculator"
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input_stream: "TENSORS:tensors"
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input_stream: "OUTPUT_SIZE:size"
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output_stream: "MASK:image_as_mask"
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options: {
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[mediapipe.TensorsToSegmentationCalculatorOptions.ext] {
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activation: $0
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}
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}
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}
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)pb",
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ActivationTypeToString(activation)));
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test_utils::CreateGraphConfigForTest(/*test_gpu=*/false, activation);
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std::vector<Packet> output_packets;
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tool::AddVectorSink("image_as_mask", &graph_config, &output_packets);
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@ -151,7 +107,7 @@ TEST_P(TensorsToSegmentationCalculatorTest, ParameterizedTests) {
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INSTANTIATE_TEST_SUITE_P(
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TensorsToSegmentationCalculatorTests, TensorsToSegmentationCalculatorTest,
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testing::ValuesIn<FormattingTestCase>({
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testing::ValuesIn<test_utils::FormattingTestCase>({
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{.test_name = "NoActivationAndNoOutputResize",
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.inputs = {1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0,
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12.0, 13.0, 14.0, 15.0, 16.0},
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@ -0,0 +1,111 @@
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// Copyright 2023 The MediaPipe Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// 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>
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#include <vector>
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#include "absl/log/absl_log.h"
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#include "absl/strings/substitute.h"
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#include "mediapipe/calculators/tensor/tensors_to_segmentation_calculator.pb.h"
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#include "mediapipe/framework/calculator.pb.h"
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#include "mediapipe/framework/port/parse_text_proto.h"
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namespace mediapipe {
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namespace tensors_to_segmentation_utils {
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std::string ActivationTypeToString(
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const TensorsToSegmentationCalculatorOptions::Activation& activation) {
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switch (activation) {
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case TensorsToSegmentationCalculatorOptions::NONE:
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return "NONE";
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case TensorsToSegmentationCalculatorOptions::SIGMOID:
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return "SIGMOID";
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case TensorsToSegmentationCalculatorOptions::SOFTMAX:
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return "SOFTMAX";
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}
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ABSL_LOG(FATAL) << "Unknown activation type: " << activation;
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return "UNKNOWN";
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}
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std::vector<unsigned char> ArrayFloatToUnsignedChar(
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const std::vector<float>& array) {
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std::vector<unsigned char> result;
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result.reserve(array.size());
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for (int i = 0; i < array.size(); ++i) {
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result.push_back(static_cast<unsigned char>(array[i]));
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}
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return result;
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}
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std::vector<float> MakeRedAlphaMatrix(const std::vector<float>& values) {
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std::vector<float> result;
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result.reserve(values.size() * 4);
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for (const float& value : values) {
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result.push_back(value);
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result.push_back(0);
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result.push_back(0);
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result.push_back(value);
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}
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return result;
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}
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// For GPU tests, the input tensor needs to be moved to GPU, using
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// TensorViewRequestor. After calculation, the output needs to be moved back
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// to CPU, using ToImageCalculator. The output is an ImageFrame.
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mediapipe::CalculatorGraphConfig CreateGraphConfigForTest(
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bool test_gpu,
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const TensorsToSegmentationCalculatorOptions::Activation& activation) {
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std::string pre_process = R"pb(
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node {
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calculator: "mediapipe.aimatter.TensorViewRequestor"
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input_stream: "TENSORS:tensors"
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output_stream: "TENSORS:tensors_gpu"
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options {
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[mediapipe.aimatter.TensorViewRequestorOptions.ext] { gpu {} }
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}
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}
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)pb";
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std::string post_process = R"pb(
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node {
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calculator: "FromImageCalculator"
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input_stream: "IMAGE:image_as_mask_gpu"
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output_stream: "IMAGE_CPU:image_as_mask"
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}
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)pb";
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return mediapipe::ParseTextProtoOrDie<mediapipe::CalculatorGraphConfig>(
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absl::Substitute(
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R"pb(
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input_stream: "tensors"
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input_stream: "size" $0
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node {
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calculator: "TensorsToSegmentationCalculator"
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input_stream: "TENSORS:tensors$1"
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input_stream: "OUTPUT_SIZE:size"
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output_stream: "MASK:image_as_mask$2"
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options: {
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[mediapipe.TensorsToSegmentationCalculatorOptions.ext] {
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activation: $3
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gpu_origin: TOP_LEFT
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}
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}
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} $4
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)pb",
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test_gpu ? pre_process : "", test_gpu ? "_gpu" : "",
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test_gpu ? "_gpu" : "", ActivationTypeToString(activation),
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test_gpu ? post_process : ""));
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}
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} // namespace tensors_to_segmentation_utils
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} // namespace mediapipe
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@ -0,0 +1,57 @@
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// Copyright 2023 The MediaPipe Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#ifndef MEDIAPIPE_CALCULATORS_TENSOR_TENSORS_TO_SEGMENTATION_CALCULATOR_TEST_UTILS_H_
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#define MEDIAPIPE_CALCULATORS_TENSOR_TENSORS_TO_SEGMENTATION_CALCULATOR_TEST_UTILS_H_
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#include <memory>
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#include <string>
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#include <utility>
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#include <vector>
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#include "mediapipe/calculators/tensor/tensors_to_segmentation_calculator.pb.h"
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#include "mediapipe/framework/calculator.pb.h"
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namespace mediapipe {
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namespace tensors_to_segmentation_utils {
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std::string ActivationTypeToString(
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const mediapipe::TensorsToSegmentationCalculatorOptions::Activation&
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activation);
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std::vector<unsigned char> ArrayFloatToUnsignedChar(
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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(
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bool test_gpu,
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const mediapipe::TensorsToSegmentationCalculatorOptions::Activation&
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activation);
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struct FormattingTestCase {
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std::string test_name;
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std::vector<float> inputs;
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std::vector<float> expected_outputs;
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mediapipe::TensorsToSegmentationCalculatorOptions::Activation activation;
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int rows = 1;
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int cols = 1;
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int rows_new = 1;
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int cols_new = 1;
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int channels = 1;
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double max_abs_diff = 1e-7;
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};
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} // namespace tensors_to_segmentation_utils
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} // namespace mediapipe
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#endif // MEDIAPIPE_CALCULATORS_TENSOR_TENSORS_TO_SEGMENTATION_CALCULATOR_TEST_UTILS_H_
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@ -0,0 +1,50 @@
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// Copyright 2023 The MediaPipe Authors.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// 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"
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#include "mediapipe/framework/port/gtest.h"
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namespace mediapipe::tensors_to_segmentation_utils {
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namespace {
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using Options = ::mediapipe::TensorsToSegmentationCalculatorOptions;
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TEST(TensorsToSegmentationCalculatorTestUtilsTest,
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ActivationTypeToStringWorksCorrectly) {
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EXPECT_EQ(ActivationTypeToString(Options::NONE), "NONE");
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EXPECT_EQ(ActivationTypeToString(Options::SIGMOID), "SIGMOID");
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EXPECT_EQ(ActivationTypeToString(Options::SOFTMAX), "SOFTMAX");
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}
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TEST(TensorsToSegmentationCalculatorTestUtilsTest,
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ArrayFloatToUnsignedCharWorksCorrectly) {
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std::vector<float> input = {1.0, 2.0, 3.0};
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std::vector<unsigned char> expected = {1, 2, 3};
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EXPECT_EQ(ArrayFloatToUnsignedChar(input), expected);
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}
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TEST(TensorsToSegmentationCalculatorTestUtilsTest,
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MakeRedAlphaMatrixWorksCorrectly) {
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std::vector<float> input = {1.0, 2.0, 3.0};
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std::vector<float> expected = {1.0, 0.0, 0.0, 1.0, 2.0, 0.0,
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0.0, 2.0, 3.0, 0.0, 0.0, 3.0};
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EXPECT_EQ(MakeRedAlphaMatrix(input), expected);
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}
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} // namespace
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} // namespace mediapipe::tensors_to_segmentation_utils
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