79 lines
3.2 KiB
Kotlin
79 lines
3.2 KiB
Kotlin
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package com.example.jnicpp.bowling
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import android.media.MediaMetadataRetriever
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import androidx.test.ext.junit.runners.AndroidJUnit4
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import androidx.test.platform.app.InstrumentationRegistry
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import com.google.android.gms.tasks.Tasks
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import com.google.mlkit.vision.common.InputImage
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import com.google.mlkit.vision.pose.PoseDetection
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import com.google.mlkit.vision.pose.accurate.AccuratePoseDetectorOptions
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import org.junit.Test
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import org.junit.runner.RunWith
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/**
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* Replays a pre-recorded reference video through the exact same
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* detection/smoothing/step-counting pipeline the live camera screen uses
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* (PoseAnalyzer's detector config -> PoseLandmarkSmoother ->
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* AnkleHipMovingAverageFilter -> buildPoseFrame -> LiveStepDetector), so the
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* algorithm can be validated against a video with a known, hand-counted
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* step count without needing a live device recording session each time.
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*
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* Not run as part of the normal test suite -- this is a diagnostic tool,
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* invoked directly via `connectedAndroidTest` with a specific video pushed
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* to the device first.
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*/
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@RunWith(AndroidJUnit4::class)
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class VideoStepReplayTest {
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@Test
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fun replayReferenceVideo() {
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val context = InstrumentationRegistry.getInstrumentation().targetContext
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val videoPath = context.getExternalFilesDir(null)!!.resolve("reference_test.mp4").absolutePath
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val retriever = MediaMetadataRetriever()
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retriever.setDataSource(videoPath)
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val durationMs = retriever.extractMetadata(MediaMetadataRetriever.METADATA_KEY_DURATION)
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?.toLongOrNull() ?: 0L
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val detector = PoseDetection.getClient(
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AccuratePoseDetectorOptions.Builder()
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.setDetectorMode(AccuratePoseDetectorOptions.STREAM_MODE)
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.build()
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)
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val landmarkSmoother = PoseLandmarkSmoother()
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val ankleHipSmoother = AnkleHipMovingAverageFilter()
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val liveStepDetector = LiveStepDetector()
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val logger = DebugSessionLogger(context)
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logger.start()
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val stepMs = 33L
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var t = 0L
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var finalStepCount = 0
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var framesProcessed = 0
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while (t < durationMs) {
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val bitmap = retriever.getFrameAtTime(t * 1000, MediaMetadataRetriever.OPTION_CLOSEST)
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if (bitmap != null) {
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val inputImage = InputImage.fromBitmap(bitmap, 0)
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val pose = Tasks.await(detector.process(inputImage))
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val landmarks = landmarkSmoother.smooth(pose)
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val angles = PoseAngleCalculator.compute(landmarks)
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val smoothedAnkleHip = ankleHipSmoother.smooth(landmarks)
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val frame = buildPoseFrame(t, landmarks, smoothedAnkleHip, angles)
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val result = liveStepDetector.update(frame)
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finalStepCount = result.stepCount
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logger.log(landmarks, t, finalStepCount)
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framesProcessed++
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}
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t += stepMs
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}
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logger.stop()
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detector.close()
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retriever.release()
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println(
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"VideoStepReplayTest: processed $framesProcessed frames over ${durationMs}ms, " +
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"final step count = $finalStepCount"
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)
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}
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}
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