It is the true, the image size is not a hard limitation, that is why we put the comment in the java doc.

“This is not a hard limit on face size; the detector may find faces slightly smaller than specified.“

You could increase the minFaceSize if you only have interests in larger faces. Or you could do a filtering for the size in your end. By increasing the minFaceSize, the performance will be improved.

Currently i am using ML Kit to detect face in my application.
It’s working but has one problem. I want to set minimum face size on it but it seems to have no effect. It always detects a face no matter what size is it.

Here is my code:

private fun setupCamera(cameraProviderFuture: ListenableFuture<ProcessCameraProvider>, mainView: MainView) {
    val cameraProvider = cameraProviderFuture.get()

    preview = Preview.Builder().build()

    val cameraSelector = CameraSelector.Builder().requireLensFacing(CameraSelector.LENS_FACING_FRONT).build()

    val realTimeOpts = FaceDetectorOptions.Builder()
        .setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_FAST)
        .setMinFaceSize(0.5f)
        .enableTracking()
        .build()

    detector = FaceDetection.getClient(realTimeOpts)

    val imageAnalysis = ImageAnalysis.Builder()
        .setBackpressureStrategy(ImageAnalysis.STRATEGY_KEEP_ONLY_LATEST)
        .build()
        .apply { setAnalyzer(Executors.newSingleThreadExecutor(), FaceDetectAnalyzer(detector!!, mainView))}

    try {
        cameraProvider.unbindAll()

        camera = cameraProvider.bindToLifecycle(this as LifecycleOwner, cameraSelector, imageAnalysis, preview)
        preview?.setSurfaceProvider(binding.pvCameraPreview.createSurfaceProvider())
    } catch (e: Exception) {
        Log.e(TAG, "Use case binding failed", e)
    }
}

Could someone point me any clues or suggestions? Thank you.