Internal change
PiperOrigin-RevId: 506053206
This commit is contained in:
MediaPipe Team
committed by
Copybara-Service
Copybara-Service
parent
0863a8a1e7
commit
5730dec260
+24
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<?xml version="1.0" encoding="utf-8"?>
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<manifest xmlns:android="http://schemas.android.com/apk/res/android"
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package="com.google.mediapipe.tasks.vision.imagesegmentertest"
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android:versionCode="1"
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android:versionName="1.0" >
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<uses-permission android:name="android.permission.READ_EXTERNAL_STORAGE"/>
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<uses-permission android:name="android.permission.WRITE_EXTERNAL_STORAGE"/>
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<uses-sdk android:minSdkVersion="24"
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android:targetSdkVersion="30" />
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<application
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android:label="imagesegmentertest"
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android:name="android.support.multidex.MultiDexApplication"
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android:taskAffinity="">
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<uses-library android:name="android.test.runner" />
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</application>
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<instrumentation
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android:name="com.google.android.apps.common.testing.testrunner.GoogleInstrumentationTestRunner"
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android:targetPackage="com.google.mediapipe.tasks.vision.imagesegmentertest" />
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</manifest>
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@@ -0,0 +1,19 @@
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# Copyright 2023 The MediaPipe Authors. All Rights Reserved.
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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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package(default_visibility = ["//mediapipe/tasks:internal"])
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licenses(["notice"])
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# TODO: Enable this in OSS
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+427
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// Copyright 2023 The MediaPipe Authors. All Rights Reserved.
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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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package com.google.mediapipe.tasks.vision.imagesegmenter;
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import static com.google.common.truth.Truth.assertThat;
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import static org.junit.Assert.assertThrows;
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import android.content.res.AssetManager;
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import android.graphics.Bitmap;
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import android.graphics.BitmapFactory;
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import android.graphics.Color;
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import androidx.test.core.app.ApplicationProvider;
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import androidx.test.ext.junit.runners.AndroidJUnit4;
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import com.google.mediapipe.framework.MediaPipeException;
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import com.google.mediapipe.framework.image.BitmapExtractor;
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import com.google.mediapipe.framework.image.BitmapImageBuilder;
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import com.google.mediapipe.framework.image.ByteBufferExtractor;
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import com.google.mediapipe.framework.image.MPImage;
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import com.google.mediapipe.tasks.core.BaseOptions;
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import com.google.mediapipe.tasks.vision.core.RunningMode;
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import com.google.mediapipe.tasks.vision.imagesegmenter.ImageSegmenter.ImageSegmenterOptions;
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import java.io.InputStream;
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import java.nio.ByteBuffer;
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import java.nio.FloatBuffer;
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import java.util.List;
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import org.junit.Test;
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import org.junit.runner.RunWith;
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import org.junit.runners.Suite;
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import org.junit.runners.Suite.SuiteClasses;
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/** Test for {@link ImageSegmenter}. */
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@RunWith(Suite.class)
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@SuiteClasses({ImageSegmenterTest.General.class, ImageSegmenterTest.RunningModeTest.class})
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public class ImageSegmenterTest {
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private static final String DEEPLAB_MODEL_FILE = "deeplabv3.tflite";
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private static final String SELFIE_128x128_MODEL_FILE = "selfie_segm_128_128_3.tflite";
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private static final String SELFIE_144x256_MODEL_FILE = "selfie_segm_144_256_3.tflite";
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private static final String CAT_IMAGE = "cat.jpg";
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private static final float GOLDEN_MASK_SIMILARITY = 0.96f;
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private static final int MAGNIFICATION_FACTOR = 10;
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@RunWith(AndroidJUnit4.class)
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public static final class General extends ImageSegmenterTest {
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@Test
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public void segment_successWithCategoryMask() throws Exception {
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final String inputImageName = "segmentation_input_rotation0.jpg";
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final String goldenImageName = "segmentation_golden_rotation0.png";
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MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
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ImageSegmenterOptions options =
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ImageSegmenterOptions.builder()
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.setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
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.setOutputType(ImageSegmenterOptions.OutputType.CATEGORY_MASK)
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.setResultListener(
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(actualResult, inputImage) -> {
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List<MPImage> segmentations = actualResult.segmentations();
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assertThat(segmentations.size()).isEqualTo(1);
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MPImage actualMaskBuffer = actualResult.segmentations().get(0);
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verifyCategoryMask(
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actualMaskBuffer,
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expectedMaskBuffer,
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GOLDEN_MASK_SIMILARITY,
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MAGNIFICATION_FACTOR);
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})
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.build();
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ImageSegmenter imageSegmenter =
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ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
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imageSegmenter.segment(getImageFromAsset(inputImageName));
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}
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@Test
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public void segment_successWithConfidenceMask() throws Exception {
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final String inputImageName = "cat.jpg";
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final String goldenImageName = "cat_mask.jpg";
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MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
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ImageSegmenterOptions options =
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ImageSegmenterOptions.builder()
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.setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
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.setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
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.setResultListener(
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(actualResult, inputImage) -> {
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List<MPImage> segmentations = actualResult.segmentations();
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assertThat(segmentations.size()).isEqualTo(21);
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// Cat category index 8.
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MPImage actualMaskBuffer = actualResult.segmentations().get(8);
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verifyConfidenceMask(
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actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
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})
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.build();
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ImageSegmenter imageSegmenter =
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ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
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imageSegmenter.segment(getImageFromAsset(inputImageName));
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}
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@Test
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public void segment_successWith128x128Segmentation() throws Exception {
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final String inputImageName = "mozart_square.jpg";
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final String goldenImageName = "selfie_segm_128_128_3_expected_mask.jpg";
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MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
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ImageSegmenterOptions options =
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ImageSegmenterOptions.builder()
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.setBaseOptions(
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BaseOptions.builder().setModelAssetPath(SELFIE_128x128_MODEL_FILE).build())
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.setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
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.setResultListener(
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(actualResult, inputImage) -> {
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List<MPImage> segmentations = actualResult.segmentations();
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assertThat(segmentations.size()).isEqualTo(2);
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// Selfie category index 1.
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MPImage actualMaskBuffer = actualResult.segmentations().get(1);
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verifyConfidenceMask(
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actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
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})
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.build();
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ImageSegmenter imageSegmenter =
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ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
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imageSegmenter.segment(getImageFromAsset(inputImageName));
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}
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// TODO: enable this unit test once activation option is supported in metadata.
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// @Test
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// public void segment_successWith144x256Segmentation() throws Exception {
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// final String inputImageName = "mozart_square.jpg";
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// final String goldenImageName = "selfie_segm_144_256_3_expected_mask.jpg";
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// MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
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// ImageSegmenterOptions options =
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// ImageSegmenterOptions.builder()
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// .setBaseOptions(
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// BaseOptions.builder().setModelAssetPath(SELFIE_144x256_MODEL_FILE).build())
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// .setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
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// .setActivation(ImageSegmenterOptions.Activation.NONE)
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// .setResultListener(
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// (actualResult, inputImage) -> {
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// List<MPImage> segmentations = actualResult.segmentations();
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// assertThat(segmentations.size()).isEqualTo(1);
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// MPImage actualMaskBuffer = actualResult.segmentations().get(0);
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// verifyConfidenceMask(
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// actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
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// })
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// .build();
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// ImageSegmenter imageSegmenter =
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// ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(),
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// options);
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// imageSegmenter.segment(getImageFromAsset(inputImageName));
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// }
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}
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@RunWith(AndroidJUnit4.class)
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public static final class RunningModeTest extends ImageSegmenterTest {
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@Test
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public void segment_failsWithCallingWrongApiInImageMode() throws Exception {
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ImageSegmenterOptions options =
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ImageSegmenterOptions.builder()
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.setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
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.setRunningMode(RunningMode.IMAGE)
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.build();
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ImageSegmenter imageSegmenter =
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ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
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MediaPipeException exception =
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assertThrows(
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MediaPipeException.class,
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() ->
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imageSegmenter.segmentForVideo(
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getImageFromAsset(CAT_IMAGE), /* timestampsMs= */ 0));
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assertThat(exception).hasMessageThat().contains("not initialized with the video mode");
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exception =
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assertThrows(
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MediaPipeException.class,
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() ->
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imageSegmenter.segmentAsync(getImageFromAsset(CAT_IMAGE), /* timestampsMs= */ 0));
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assertThat(exception).hasMessageThat().contains("not initialized with the live stream mode");
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}
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@Test
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public void segment_failsWithCallingWrongApiInVideoMode() throws Exception {
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ImageSegmenterOptions options =
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ImageSegmenterOptions.builder()
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.setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
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.setRunningMode(RunningMode.VIDEO)
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.build();
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ImageSegmenter imageSegmenter =
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ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
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MediaPipeException exception =
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assertThrows(
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MediaPipeException.class, () -> imageSegmenter.segment(getImageFromAsset(CAT_IMAGE)));
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assertThat(exception).hasMessageThat().contains("not initialized with the image mode");
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exception =
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assertThrows(
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MediaPipeException.class,
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() ->
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imageSegmenter.segmentAsync(getImageFromAsset(CAT_IMAGE), /* timestampsMs= */ 0));
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assertThat(exception).hasMessageThat().contains("not initialized with the live stream mode");
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}
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@Test
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public void segment_failsWithCallingWrongApiInLiveSteamMode() throws Exception {
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ImageSegmenterOptions options =
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ImageSegmenterOptions.builder()
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.setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
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.setRunningMode(RunningMode.LIVE_STREAM)
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.setResultListener((result, inputImage) -> {})
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.build();
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ImageSegmenter imageSegmenter =
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ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
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MediaPipeException exception =
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assertThrows(
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MediaPipeException.class, () -> imageSegmenter.segment(getImageFromAsset(CAT_IMAGE)));
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assertThat(exception).hasMessageThat().contains("not initialized with the image mode");
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exception =
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assertThrows(
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MediaPipeException.class,
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() ->
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imageSegmenter.segmentForVideo(
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getImageFromAsset(CAT_IMAGE), /* timestampsMs= */ 0));
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assertThat(exception).hasMessageThat().contains("not initialized with the video mode");
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}
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@Test
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public void segment_successWithImageMode() throws Exception {
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final String inputImageName = "cat.jpg";
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final String goldenImageName = "cat_mask.jpg";
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MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
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ImageSegmenterOptions options =
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ImageSegmenterOptions.builder()
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.setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
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.setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
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.setRunningMode(RunningMode.IMAGE)
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.setResultListener(
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(actualResult, inputImage) -> {
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List<MPImage> segmentations = actualResult.segmentations();
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assertThat(segmentations.size()).isEqualTo(21);
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// Cat category index 8.
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MPImage actualMaskBuffer = actualResult.segmentations().get(8);
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verifyConfidenceMask(
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actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
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})
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.build();
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ImageSegmenter imageSegmenter =
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ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
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imageSegmenter.segment(getImageFromAsset(inputImageName));
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}
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@Test
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public void segment_successWithVideoMode() throws Exception {
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final String inputImageName = "cat.jpg";
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final String goldenImageName = "cat_mask.jpg";
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MPImage expectedMaskBuffer = getImageFromAsset(goldenImageName);
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ImageSegmenterOptions options =
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ImageSegmenterOptions.builder()
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.setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
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.setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
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.setRunningMode(RunningMode.VIDEO)
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.setResultListener(
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(actualResult, inputImage) -> {
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List<MPImage> segmentations = actualResult.segmentations();
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assertThat(segmentations.size()).isEqualTo(21);
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// Cat category index 8.
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MPImage actualMaskBuffer = actualResult.segmentations().get(8);
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verifyConfidenceMask(
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actualMaskBuffer, expectedMaskBuffer, GOLDEN_MASK_SIMILARITY);
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})
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.build();
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ImageSegmenter imageSegmenter =
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ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options);
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for (int i = 0; i < 3; i++) {
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imageSegmenter.segmentForVideo(getImageFromAsset(inputImageName), /* timestampsMs= */ i);
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}
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}
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@Test
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public void segment_successWithLiveStreamMode() throws Exception {
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final String inputImageName = "cat.jpg";
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final String goldenImageName = "cat_mask.jpg";
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MPImage image = getImageFromAsset(inputImageName);
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MPImage expectedResult = getImageFromAsset(goldenImageName);
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ImageSegmenterOptions options =
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ImageSegmenterOptions.builder()
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.setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
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.setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
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.setRunningMode(RunningMode.LIVE_STREAM)
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.setResultListener(
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(segmenterResult, inputImage) -> {
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verifyConfidenceMask(
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segmenterResult.segmentations().get(8),
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expectedResult,
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GOLDEN_MASK_SIMILARITY);
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})
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.build();
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try (ImageSegmenter imageSegmenter =
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ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options)) {
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for (int i = 0; i < 3; i++) {
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imageSegmenter.segmentAsync(image, /* timestampsMs= */ i);
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}
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}
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}
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@Test
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public void segment_failsWithOutOfOrderInputTimestamps() throws Exception {
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final String inputImageName = "cat.jpg";
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final String goldenImageName = "cat_mask.jpg";
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MPImage image = getImageFromAsset(inputImageName);
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MPImage expectedResult = getImageFromAsset(goldenImageName);
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ImageSegmenterOptions options =
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ImageSegmenterOptions.builder()
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.setBaseOptions(BaseOptions.builder().setModelAssetPath(DEEPLAB_MODEL_FILE).build())
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.setOutputType(ImageSegmenterOptions.OutputType.CONFIDENCE_MASK)
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.setRunningMode(RunningMode.LIVE_STREAM)
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.setResultListener(
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(segmenterResult, inputImage) -> {
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verifyConfidenceMask(
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segmenterResult.segmentations().get(8),
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expectedResult,
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GOLDEN_MASK_SIMILARITY);
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})
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.build();
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try (ImageSegmenter imageSegmenter =
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ImageSegmenter.createFromOptions(ApplicationProvider.getApplicationContext(), options)) {
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imageSegmenter.segmentAsync(image, /* timestampsMs= */ 1);
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MediaPipeException exception =
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assertThrows(
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MediaPipeException.class,
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() -> imageSegmenter.segmentAsync(image, /* timestampsMs= */ 0));
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assertThat(exception)
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.hasMessageThat()
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.contains("having a smaller timestamp than the processed timestamp");
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}
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}
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}
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private static void verifyCategoryMask(
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MPImage actualMask, MPImage goldenMask, float similarityThreshold, int magnificationFactor) {
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assertThat(actualMask.getWidth()).isEqualTo(goldenMask.getWidth());
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assertThat(actualMask.getHeight()).isEqualTo(goldenMask.getHeight());
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ByteBuffer actualMaskBuffer = ByteBufferExtractor.extract(actualMask);
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Bitmap goldenMaskBitmap = BitmapExtractor.extract(goldenMask);
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int consistentPixels = 0;
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final int numPixels = actualMask.getWidth() * actualMask.getHeight();
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actualMaskBuffer.rewind();
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for (int y = 0; y < actualMask.getHeight(); y++) {
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for (int x = 0; x < actualMask.getWidth(); x++) {
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// RGB values are the same in the golden mask image.
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consistentPixels +=
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actualMaskBuffer.get() * magnificationFactor
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== Color.red(goldenMaskBitmap.getPixel(x, y))
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? 1
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: 0;
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}
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}
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assertThat((float) consistentPixels / numPixels).isGreaterThan(similarityThreshold);
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}
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private static void verifyConfidenceMask(
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MPImage actualMask, MPImage goldenMask, float similarityThreshold) {
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assertThat(actualMask.getWidth()).isEqualTo(goldenMask.getWidth());
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assertThat(actualMask.getHeight()).isEqualTo(goldenMask.getHeight());
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FloatBuffer actualMaskBuffer = ByteBufferExtractor.extract(actualMask).asFloatBuffer();
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Bitmap goldenMaskBitmap = BitmapExtractor.extract(goldenMask);
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FloatBuffer goldenMaskBuffer = getByteBufferFromBitmap(goldenMaskBitmap).asFloatBuffer();
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assertThat(
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calculateSoftIOU(
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actualMaskBuffer, goldenMaskBuffer, actualMask.getWidth() * actualMask.getHeight()))
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.isGreaterThan((double) similarityThreshold);
|
||||
}
|
||||
|
||||
private static MPImage getImageFromAsset(String filePath) throws Exception {
|
||||
AssetManager assetManager = ApplicationProvider.getApplicationContext().getAssets();
|
||||
InputStream istr = assetManager.open(filePath);
|
||||
return new BitmapImageBuilder(BitmapFactory.decodeStream(istr)).build();
|
||||
}
|
||||
|
||||
private static ByteBuffer getByteBufferFromBitmap(Bitmap bitmap) {
|
||||
ByteBuffer byteBuffer = ByteBuffer.allocateDirect(bitmap.getWidth() * bitmap.getHeight() * 4);
|
||||
for (int y = 0; y < bitmap.getHeight(); y++) {
|
||||
for (int x = 0; x < bitmap.getWidth(); x++) {
|
||||
byteBuffer.putFloat((float) Color.red(bitmap.getPixel(x, y)) / 255.f);
|
||||
}
|
||||
}
|
||||
byteBuffer.rewind();
|
||||
return byteBuffer;
|
||||
}
|
||||
|
||||
private static double calculateSum(FloatBuffer m) {
|
||||
m.rewind();
|
||||
double sum = 0;
|
||||
while (m.hasRemaining()) {
|
||||
sum += m.get();
|
||||
}
|
||||
m.rewind();
|
||||
return sum;
|
||||
}
|
||||
|
||||
private static FloatBuffer multiply(FloatBuffer m1, FloatBuffer m2, int bufferSize) {
|
||||
m1.rewind();
|
||||
m2.rewind();
|
||||
FloatBuffer buffer = FloatBuffer.allocate(bufferSize);
|
||||
while (m1.hasRemaining()) {
|
||||
buffer.put(m1.get() * m2.get());
|
||||
}
|
||||
m1.rewind();
|
||||
m2.rewind();
|
||||
buffer.rewind();
|
||||
return buffer;
|
||||
}
|
||||
|
||||
private static double calculateSoftIOU(FloatBuffer m1, FloatBuffer m2, int bufferSize) {
|
||||
double intersectionSum = calculateSum(multiply(m1, m2, bufferSize));
|
||||
double m1m1 = calculateSum(multiply(m1, m1.duplicate(), bufferSize));
|
||||
double m2m2 = calculateSum(multiply(m2, m2.duplicate(), bufferSize));
|
||||
double unionSum = m1m1 + m2m2 - intersectionSum;
|
||||
return unionSum > 0.0 ? intersectionSum / unionSum : 0.0;
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user