我正在使用 CameraX Analyzer 用例使用 OpenCV Hough Circles 检测图像中的圆圈，但即使我相信我正在使用单独的线程进行此分析，当检测到的圆圈过多时，相机预览有时会变得非常慢。
我知道我的检测器实现不是最有效的，但是这个处理时间不应该只反映在分析率上，而不是预览上吗？
从 crysxd CameraX-Object-Tracking获得了大部分代码。
这是我的主要活动：
class MainActivity : AppCompatActivity() {
private lateinit var overlayTextureView: DetectionOverlayView
private val camera
get() = supportFragmentManager.findFragmentById(R.id.cameraFragment) as CameraFragment
override fun onCreate(savedInstanceState: Bundle?) {
OpenCVLoader.initDebug()
super.onCreate(savedInstanceState)
setContentView(R.layout.activity_main)
if (Timber.treeCount() == 0) {
Timber.plant(Timber.DebugTree())
}
overlayTextureView = findViewById(R.id.detectionOverlayView)
camera.imageAnalyzer = ViewModelProviders.of(this).get(HoughPupilDetector::class.java)
}
}
这是我的 CameraFragment 初始化：
open class CameraFragment : Fragment() {
var cameraRunning = false
private set
var imageAnalyzer: ThreadedImageAnalyzer? = null
set(value) {
field = value
if (cameraRunning) {
startCamera()
}
}
override fun onCreateView(inflater: LayoutInflater, container: ViewGroup?, savedInstanceState: Bundle?): View =
inflater.inflate(R.layout.fragment_camera, container, false)
override fun onViewCreated(view: View, savedInstanceState: Bundle?) {
super.onViewCreated(view, savedInstanceState)
CameraPermissionHelper().requestCameraPermission(childFragmentManager) {
if (it) {
startCamera()
} else {
activity?.finish()
}
}
}
override fun onDestroyView() {
super.onDestroyView()
if (cameraRunning) {
CameraX.unbindAll()
cameraRunning = false
Timber.i("Stopping camera")
}
}
private fun startCamera() {
preview.post {
try {
val usesCases = mutableListOf<UseCase>()
// Make sure that there are no other use cases bound to CameraX
CameraX.unbindAll()
// Create configuration object for the viewfinder use case
val previewConfig = onCreatePreivewConfigBuilder().build()
usesCases.add(AutoFitPreviewBuilder.build(previewConfig, preview))
// Setup image analysis pipeline that computes average pixel luminance in real time
if (imageAnalyzer != null) {
val analyzerConfig = onCreateAnalyzerConfigBuilder().build()
usesCases.add(ImageAnalysis(analyzerConfig).apply {
analyzer = imageAnalyzer
})
}
// Bind use cases to lifecycle
CameraX.bindToLifecycle(this, *usesCases.toTypedArray())
cameraRunning = true
Timber.i("Started camera with useCases=$usesCases")
} catch (e: Exception) {
Timber.e(e)
AlertDialog.Builder(context)
.setMessage(getString(R.string.camera_error))
.setPositiveButton(android.R.string.ok) { _, _ ->
activity?.finish()
}
.create()
}
}
}
@Suppress("MemberVisibilityCanBePrivate")
protected open fun onCreateAnalyzerConfigBuilder() = ImageAnalysisConfig.Builder().apply {
// Use a worker thread for image analysis to prevent preview glitches
setCallbackHandler(imageAnalyzer!!.getHandler())
// In our analysis, we care more about the latest image than analyzing *every* image
setImageReaderMode(ImageAnalysis.ImageReaderMode.ACQUIRE_LATEST_IMAGE)
setTargetAspectRatio(Rational(1, 1))
setTargetResolution(Size(preview.width, preview.height))
}
@Suppress("MemberVisibilityCanBePrivate")
protected open fun onCreatePreivewConfigBuilder() = PreviewConfig.Builder().apply {
setTargetAspectRatio(Rational(1, 1))
setTargetResolution(Size(preview.width, preview.height))
}
}
这是我的分析器接口初始化：
abstract class PupilDetector(listener: PupilDetectionListener? = null) : ViewModel(), ThreadedImageAnalyzer {
private val listeners = ArrayList<PupilDetectionListener>().apply { listener?.let { add(it) } }
private val isBusy = AtomicBoolean(false)
private val handlerThread = HandlerThread("PupilDetector").apply { start() }
fun addListener(listener: PupilDetectionListener) = listeners.add(listener)
override fun analyze(image: ImageProxy, rotationDegrees: Int) {
if (isBusy.compareAndSet(false, true)) {
Timber.d("Running analysis...")
val pupil = detect(image, rotationDegrees)
Timber.d("Analysis done.")
isBusy.set(false)
// listeners.forEach { it(pupil) }
}
}
override fun getHandler() = Handler(handlerThread.looper)
abstract fun detect(image: ImageProxy, rotationDegrees: Int): Pupil?
}
这是我的霍夫圆分析器：
class HoughPupilDetector(listener: PupilDetectionListener? = null): PupilDetector(listener) {
val maxCircles = 5
override fun detect(image: ImageProxy, rotationDegrees: Int): Pupil? {
val bitmap = image.toBitmap(rotationDegrees)
val circles = detectCircles(bitmap)
if(circles.isNotEmpty()) {
return Pupil(circles[0].point, circles[0].r)
} else {
return null
}
}
private fun detectCircles(bitmap: Bitmap): List<Circle> {
// Generate Mat object
val img = Mat()
Utils.bitmapToMat(bitmap, img)
// Detect circles
val cannyUpperThreshold = 100.0
val minRadius = 10
val maxRadius = 400
val accumulator = 100.0
val circles = Mat()
Imgproc.cvtColor(img, img, Imgproc.COLOR_RGB2GRAY)
Imgproc.GaussianBlur(img, img, org.opencv.core.Size(3.0, 3.0), 1.0)
Imgproc.HoughCircles(img, circles, Imgproc.CV_HOUGH_GRADIENT,
2.0, 2.0 / 8.0, cannyUpperThreshold, accumulator,
minRadius, maxRadius)
Imgproc.cvtColor(img, img, Imgproc.COLOR_GRAY2BGR)
// Convert Mat to list of circles
val result = toCircles(circles)
// Return detection
return result
}
private fun toCircles(circles: Mat): List<Circle>{
if (circles.cols() > 0){
return (0 until circles.cols().coerceAtMost(maxCircles)).map {
val vCircle = circles.get(0, it)
val pt = Point(vCircle[0].toInt(), vCircle[1].toInt())
val radius = Math.round(vCircle[2]).toInt()
// return circle
Circle(pt, radius)
}
} else {
return emptyList()
}
}
}