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refactor: allow posibiliy of gpu
author
nate
date
(Feb 5, 2026, 5:55 PM +0200)
commit
ca92e5a2
ca92e5a27107d9e80475d31823d2f20969d2c89b
parent
0913646a
0913646ad19d0d1256b6e7d9f2bd00bf983654fe
+31
-8
+1
posedetection/build.gradle.kts
+1
posedetection/build.gradle.kts
+2
-2
posedetection/src/androidMain/kotlin/com.performancecoachlab/posedetection/camera/CameraView.android.kt
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-2
posedetection/src/androidMain/kotlin/com.performancecoachlab/posedetection/camera/CameraView.android.kt
···
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// Throttle detectors to avoid doing heavy work every frame.
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// Tune these to balance smoothness vs CPU usage.
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val objectIntervalMs = 66L // ~10 FPS
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val poseIntervalMs = 66L // ~10 FPS
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val objectIntervalMs = 20L
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val poseIntervalMs = 20L
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val lastObjectRunAtMs = remember { AtomicLong(0L) }
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val lastPoseRunAtMs = remember { AtomicLong(0L) }
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-3
posedetection/src/androidMain/kotlin/com/performancecoachlab/posedetection/camera/Utils.android.kt
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posedetection/src/androidMain/kotlin/com/performancecoachlab/posedetection/camera/Utils.android.kt
···
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)
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fun ModelInfo.label(cls: Int): String{
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Logger.d{ "ModelInfo.label: cls=$cls" }
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this.labels.let { labelsList ->
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if (cls in labelsList.indices) {
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Logger.d{ "ModelInfo.label: $cls = ${labelsList[cls]}" }
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return labelsList[cls]
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}
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}
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Logger.d{ "ModelInfo.label: $cls not in labels" }
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return "$cls"
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}
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-3
posedetection/src/androidMain/kotlin/com/performancecoachlab/posedetection/custom/CustomObjectModel.android.kt
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posedetection/src/androidMain/kotlin/com/performancecoachlab/posedetection/custom/CustomObjectModel.android.kt
···
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import androidx.compose.ui.platform.LocalContext
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import co.touchlab.kermit.Logger
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import org.tensorflow.lite.Interpreter
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import org.tensorflow.lite.gpu.CompatibilityList
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import org.tensorflow.lite.gpu.GpuDelegate
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import org.tensorflow.lite.gpu.GpuDelegateFactory
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import org.tensorflow.lite.support.common.FileUtil
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import org.tensorflow.lite.support.metadata.MetadataExtractor
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import java.nio.MappedByteBuffer
···
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if (modelPath.androidModelPath == null) {
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throw IllegalArgumentException("Android model path cannot be null")
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}
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val options = Interpreter.Options().apply {
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this.setNumThreads(4)
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// Prefer GPU if available, fall back to CPU.
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val (options, gpuDelegate) = runCatching {
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val delegate = GpuDelegate()
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val opts = Interpreter.Options().apply {
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addDelegate(delegate)
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// Threads often don’t matter with GPU delegate; keep small to reduce contention.
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setNumThreads(2)
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}
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Logger.d{ "TFLite GPU delegate available" }
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opts to delegate
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}.onFailure { t ->
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Logger.w(t) { "TFLite GPU delegate not available; falling back to CPU" }
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}.getOrElse {
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Interpreter.Options().apply { setNumThreads(4) } to null
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}
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val model = FileUtil.loadMappedFile(LocalContext.current, modelPath.androidModelPath)
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val labels = labels(model)
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val interpreter = Interpreter(model, options)
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val interpreter = runCatching {
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Interpreter(model, options)
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}.onFailure { t ->
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// If GPU interpreter creation fails, retry on CPU.
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Logger.w(t) { "TFLite GPU Failed to create GPU TFLite interpreter; retrying on CPU" }
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gpuDelegate?.close()
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}.getOrElse {
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val cpuOptions = Interpreter.Options().apply { setNumThreads(4) }
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Interpreter(model, cpuOptions)
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}
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val inputShape = interpreter.getInputTensor(0)?.shape()
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val outputShape = interpreter.getOutputTensor(0)?.shape()