This repository has no description
fix: resolve mirroring issue
author
nathan holland
date
(Sep 7, 2025, 11:38 PM +0300)
commit
cb909961
cb9099616643eaca0be111fd1f28426ce3a744ab
parent
1c073bde
1c073bde485e602ae6eaea758f394830428e4e98
+38
-37
+1
-1
README.md
+1
-1
README.md
+1
-1
posedetection/build.gradle.kts
+1
-1
posedetection/build.gradle.kts
···
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mavenPublishing {
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publishToMavenCentral(SonatypeHost.CENTRAL_PORTAL)
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coordinates("com.performancecoachlab.posedetection", "posedetection-compose", "4.1.0")
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coordinates("com.performancecoachlab.posedetection", "posedetection-compose", "4.1.3")
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pom {
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name.set("Pose Detection")
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-3
posedetection/src/androidMain/kotlin/com.performancecoachlab/posedetection/camera/CameraView.android.kt
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-3
posedetection/src/androidMain/kotlin/com.performancecoachlab/posedetection/camera/CameraView.android.kt
···
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val path = builder.finalize()
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onVideoSaved(id, path)
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} catch (e: Exception) {
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println("Error finalizing recording $id: ${e.message}")
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//println("Error finalizing recording $id: ${e.message}")
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}
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}
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activeRecordings = activeRecordings - id
···
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}
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} catch (e: Exception) {
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// Handle recording errors gracefully
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println("Error recording frame for ID $id: ${e.message}")
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//println("Error recording frame for ID $id: ${e.message}")
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}
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}
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}
···
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){
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customObjectRepository.updateCustomObject(it.objects)
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it.skeleton?.let { skel ->
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skeletonRepository.updateSkeleton(skel.mirror())
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skeletonRepository.updateSkeleton(skel)
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}
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bitmap =
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imageProxy.toBitmap().rotate(imageProxy.imageInfo.rotationDegrees.toFloat())
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-1
posedetection/src/androidMain/kotlin/com/performancecoachlab/posedetection/camera/Utils.android.kt
+1
-1
posedetection/src/androidMain/kotlin/com/performancecoachlab/posedetection/camera/Utils.android.kt
···
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poseDetector?.process(it)?.addOnSuccessListener { pose ->
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skeleton = skeleton(pose, timestamp, width, height)
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}?.addOnFailureListener { e ->
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println(e)
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//println(e)
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}
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}
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Tasks.whenAllComplete(listOfNotNull(poseDetectionTask)).addOnCompleteListener {
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posedetection/src/androidMain/kotlin/com/performancecoachlab/posedetection/encoding/VideoBuilder.android.kt
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-1
posedetection/src/androidMain/kotlin/com/performancecoachlab/posedetection/encoding/VideoBuilder.android.kt
···
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inputBuffer.put(yuvData)
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} else {
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inputBuffer.put(yuvData, 0, bufferCapacity)
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println("Warning: YUV data (${yuvData.size} bytes) exceeded buffer capacity ($bufferCapacity bytes)")
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//println("Warning: YUV data (${yuvData.size} bytes) exceeded buffer capacity ($bufferCapacity bytes)")
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}
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}
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val dataSize = minOf(yuvData.size, inputBuffer?.capacity() ?: 0)
+12
-5
posedetection/src/iosMain/kotlin/com/performancecoachlab/posedetection/camera/CameraEngine.kt
+12
-5
posedetection/src/iosMain/kotlin/com/performancecoachlab/posedetection/camera/CameraEngine.kt
···
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import com.performancecoachlab.posedetection.custom.CustomObjectRespository
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import com.performancecoachlab.posedetection.custom.ObjectModel
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import com.performancecoachlab.posedetection.recording.AnalysisObject
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import com.performancecoachlab.posedetection.recording.FrameSize
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import com.performancecoachlab.posedetection.skeleton.Skeleton
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import com.performancecoachlab.posedetection.skeleton.SkeletonRepository
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import kotlinx.cinterop.ExperimentalForeignApi
···
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cameraController.setupPreviewLayer(view)
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startSession()
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cameraController.onError = { error ->
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println("Camera Error: $error")
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//println("Camera Error: $error")
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}
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}
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···
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it.copy(
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boundingBox = mapBoxToPreview(
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it.boundingBox, preview, width = 480f, height = 360f
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-
)
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)
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), frameSize = it.frameSize.let {
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mapBoxToPreview(
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Rect(Offset.Zero, Size(480f, 360f)),
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preview,
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width = 480f,
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height = 360f
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).let { FrameSize(it.width.toInt(), it.height.toInt()) }
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})
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}
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previewObjects?.also{ objects->
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previewObjects?.also { objects ->
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customObjectRepository?.updateCustomObject(objects)
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}
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···
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}
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}
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} catch (e: Exception) {
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println(e.message ?: "Unknown error in frame processing")
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//println(e.message ?: "Unknown error in frame processing")
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}
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}
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}
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-4
posedetection/src/iosMain/kotlin/com/performancecoachlab/posedetection/camera/Conversions.kt
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-4
posedetection/src/iosMain/kotlin/com/performancecoachlab/posedetection/camera/Conversions.kt
···
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// Lock the pixel buffer
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val lockResult = CVPixelBufferLockBaseAddress(this, CVPixelBufferLockFlags.MAX_VALUE)
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if (lockResult != 0) {
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println("Error: Failed to lock pixel buffer")
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//println("Error: Failed to lock pixel buffer")
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return null
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}
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···
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)
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return videoImage
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}catch (e: Exception) {
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println("Error: Failed to create CGImage from CVImageBufferRef: ${e.message}")
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//println("Error: Failed to create CGImage from CVImageBufferRef: ${e.message}")
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return null
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}
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}
···
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)
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return videoImage
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}catch (e: Exception) {
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println("Error: Failed to create CGImage from CVImageBufferRef: ${e.message}")
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//println("Error: Failed to create CGImage from CVImageBufferRef: ${e.message}")
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return null
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}
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}
···
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// Call a function to process the UIImage
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return image.toImageBitmap()
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}catch (e: Exception) {
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println("Error: Failed to create CGImage from CVImageBufferRef: ${e.message}")
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//println("Error: Failed to create CGImage from CVImageBufferRef: ${e.message}")
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return null
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}finally {
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-6
posedetection/src/iosMain/kotlin/com/performancecoachlab/posedetection/camera/FrameProcessor.kt
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-6
posedetection/src/iosMain/kotlin/com/performancecoachlab/posedetection/camera/FrameProcessor.kt
···
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// Process each observation to find the recognized body pose points.
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return observations.map { processObservation(it) }
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} catch (e: Exception) {
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println("Error processing observations: ${e.message}")
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//println("Error processing observations: ${e.message}")
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return null
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}
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}
···
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}
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requests = mutableListOf(objectRecognition)
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} catch (e: Throwable) {
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println("Vision setup error: ${e.message}")
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//println("Vision setup error: ${e.message}")
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}
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}
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}
···
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listOfNotNull(requestForObjects, requestForSkeleton), errorPtr.ptr
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)
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if (errorPtr.value != null) {
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println("Error performing object detection request: ${errorPtr.value}")
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//println("Error performing object detection request: ${errorPtr.value}")
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onObjectsProcessed(emptyList())
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onSkeletonProcessed(null)
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}
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} catch (e: Throwable) {
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println("Unable to perform the object detection request: ${e.message}")
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//println("Unable to perform the object detection request: ${e.message}")
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onObjectsProcessed(emptyList())
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onSkeletonProcessed(null)
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}
···
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listOfNotNull(requestForObjects, requestForSkeleton), errorPtr.ptr
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)
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if (errorPtr.value != null) {
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println("Error performing object detection request: ${errorPtr.value}")
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//println("Error performing object detection request: ${errorPtr.value}")
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onObjectsProcessed(emptyList())
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onSkeletonProcessed(null)
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}
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} catch (e: Throwable) {
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println("Unable to perform the object detection request: ${e.message}")
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//println("Unable to perform the object detection request: ${e.message}")
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onObjectsProcessed(emptyList())
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onSkeletonProcessed(null)
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}
+5
-6
posedetection/src/iosMain/kotlin/com/performancecoachlab/posedetection/custom/CustomObjectModel.ios.kt
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-6
posedetection/src/iosMain/kotlin/com/performancecoachlab/posedetection/custom/CustomObjectModel.ios.kt
···
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@OptIn(ExperimentalForeignApi::class)
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fun createObjectDetector(model: String?): VNCoreMLModel? {
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if(model == null) {
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println("Model path is null")
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return null
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}
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println("Model input: $model")
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//println("Model input: $model")
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val path = NSBundle.mainBundle.pathForResource(model, "mlmodelc")
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println("Model path: $path")
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//println("Model path: $path")
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val url = path?.let { NSURL.fileURLWithPath(it) }
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println("Model URL: $url")
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//println("Model URL: $url")
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val modelCont = url?.let {MLModel.modelWithContentsOfURL(it, null)}
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println("Model content: $modelCont")
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//println("Model content: $modelCont")
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val modelObj = modelCont?.let {VNCoreMLModel.modelForMLModel(it,null)}
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println("Model: $modelObj")
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//println("Model: $modelObj")
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return modelObj
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}
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+2
-2
posedetection/src/iosMain/kotlin/com/performancecoachlab/posedetection/encoding/VideoBuilder.ios.kt
+2
-2
posedetection/src/iosMain/kotlin/com/performancecoachlab/posedetection/encoding/VideoBuilder.ios.kt
···
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pixelBufferAdaptor.appendPixelBuffer(pixelBuffer, withPresentationTime = presentationTime)
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CVPixelBufferRelease(pixelBuffer)
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} else {
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println("Failed to allocate pixel buffer: $status")
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//println("Failed to allocate pixel buffer: $status")
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}
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}
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frameCount++
···
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if (started) {
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input?.markAsFinished()
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writer?.finishWritingWithCompletionHandler {
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println("[VideoBuilder] Finished writing video!")
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//println("[VideoBuilder] Finished writing video!")
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}
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// Wait for writing to finish
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while (writer?.status == AVAssetWriterStatusWriting) {}
+2
-7
sample/composeApp/src/commonMain/kotlin/com/nate/posedetection/App.kt
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-7
sample/composeApp/src/commonMain/kotlin/com/nate/posedetection/App.kt
···
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import com.performancecoachlab.posedetection.permissions.PermissionProvider
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import com.performancecoachlab.posedetection.recording.AnalysisObject
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import com.performancecoachlab.posedetection.recording.FrameAnalyser
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import com.performancecoachlab.posedetection.recording.FrameSize
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import com.performancecoachlab.posedetection.recording.InputFrame
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import com.performancecoachlab.posedetection.recording.Label
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import com.performancecoachlab.posedetection.recording.extractFrame
···
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val extractedFrame = extractFrame(url, frame)
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extractedFrame?.let { frame ->
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frameAnalyser.analyseFrame(frame).let { analysisResults ->
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analysisResults.objects.let {
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if (it.isNotEmpty()) {
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it.forEach { obj ->
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println("Detected Objects: ${obj.labels}")
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}
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}
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}
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frame.drawAnalysisResults(analysisResults).also {
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if (!isRecording) {
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size = Pair(it.width, it.height)
···
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detectMode = DetectMode.BOTH,
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drawSkeleton = true,
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drawObjects = { obj ->
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+
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obj.map {
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DrawableObject(
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obj = it,