优化性能第一版

app/src/main/java/com/example/studentfaceregistry/MainActivity.kt

@@ -86,6 +86,7 @@ class MainActivity : AppCompatActivity() {
     private var cosineThreshold = DEFAULT_COSINE_THRESHOLD
     @Volatile private var matcher = FaceMatcher(DEFAULT_EUCLIDEAN_THRESHOLD, DEFAULT_COSINE_THRESHOLD)
     private val recognitionHistory = mutableMapOf<Int, ArrayDeque<RecognitionResult>>()
+    private val recognitionCache = mutableMapOf<Int, CachedRecognition>()
 
     private val permissionLauncher = registerForActivityResult(
         ActivityResultContracts.RequestMultiplePermissions()
@@ -415,6 +416,8 @@ class MainActivity : AppCompatActivity() {
         matcherConfigSummaryText.text = matcherConfigSummary()
         euclideanThresholdInput.setText(formatThreshold(euclideanThreshold))
         cosineThresholdInput.setText(formatThreshold(cosineThreshold))
+        recognitionHistory.clear()
+        recognitionCache.clear()
         overlayView.update(emptyList())
 
         if (hasCameraPermission()) {
@@ -473,6 +476,8 @@ class MainActivity : AppCompatActivity() {
         analysisUseCase = null
         cameraProvider?.unbindAll()
         cameraProvider = null
+        recognitionHistory.clear()
+        recognitionCache.clear()
         overlayView.update(emptyList())
         processor?.close()
         processor = null
@@ -513,6 +518,7 @@ class MainActivity : AppCompatActivity() {
                     withContext(Dispatchers.Main) {
                         if (currentMode == AppMode.RECOGNITION) {
                             recognitionHistory.clear()
+                            recognitionCache.clear()
                             overlayView.update(emptyList())
                             updateRecognitionStatus(emptyList())
                         }
@@ -520,11 +526,26 @@ class MainActivity : AppCompatActivity() {
                     return@launch
                 }
 
-                val bitmap = ImageUtils.imageProxyToBitmap(image)
                 val activeTrackIds = faces.mapNotNull { it.trackingId }.toSet()
-                val rawDetections = faces.map { face ->
+                val facesNeedingRefresh = faces.mapIndexedNotNull { index, face ->
-                    val embedding = faceProcessor.embedFace(bitmap, face)
+                    if (shouldRefreshRecognition(face.trackingId, now)) index to face else null
-                    val result = stabilizeRecognition(face, matcher.findNearest(embedding, students))
+                }
+                val refreshedResults = mutableMapOf<Int, RecognitionResult>()
+
+                if (facesNeedingRefresh.isNotEmpty()) {
+                    val bitmap = ImageUtils.imageProxyToBitmap(image)
+                    facesNeedingRefresh.forEach { (index, face) ->
+                        val embedding = faceProcessor.embedFace(bitmap, face)
+                        val refreshed = matcher.findNearest(embedding, students)
+                        refreshedResults[index] = refreshed
+                        face.trackingId?.let { trackId ->
+                            recognitionCache[trackId] = CachedRecognition(refreshed, now)
+                        }
+                    }
+                }
+
+                val rawDetections = faces.mapIndexed { index, face ->
+                    val result = resolveRecognitionResult(face, refreshedResults[index], now)
                     RawDetection(
                         bounds = face.boundingBox,
                         result = result,
@@ -532,6 +553,7 @@ class MainActivity : AppCompatActivity() {
                     )
                 }
                 recognitionHistory.keys.retainAll(activeTrackIds)
+                recognitionCache.keys.retainAll(activeTrackIds)
 
                 withContext(Dispatchers.Main) {
                     if (currentMode == AppMode.RECOGNITION) {
@@ -710,12 +732,37 @@ class MainActivity : AppCompatActivity() {
         return if (best.value.size >= 2) best.value.last() else result
     }
 
+    private fun shouldRefreshRecognition(trackId: Int?, now: Long): Boolean {
+        if (trackId == null) return true
+        val cached = recognitionCache[trackId] ?: return true
+        return now - cached.updatedAtMs >= RECOGNITION_REFRESH_MS
+    }
+
+    private fun resolveRecognitionResult(
+        face: Face,
+        refreshedResult: RecognitionResult?,
+        now: Long
+    ): RecognitionResult {
+        val trackId = face.trackingId
+        val directResult = when {
+            refreshedResult != null -> refreshedResult
+            trackId != null && recognitionCache.containsKey(trackId) -> recognitionCache.getValue(trackId).result
+            else -> RecognitionResult(null, Float.MAX_VALUE, 0f, MatchType.NO_DATA)
+        }
+        val stabilized = stabilizeRecognition(face, directResult)
+        if (trackId != null) {
+            recognitionCache[trackId] = CachedRecognition(stabilized, now)
+        }
+        return stabilized
+    }
+
     companion object {
         private const val MATCHER_PREFS_NAME = "face_matcher_config"
         private const val KEY_EUCLIDEAN_THRESHOLD = "euclidean_threshold"
         private const val KEY_COSINE_THRESHOLD = "cosine_threshold"
         private const val DEFAULT_EUCLIDEAN_THRESHOLD = 1.0f
         private const val DEFAULT_COSINE_THRESHOLD = 0.6f
+        private const val RECOGNITION_REFRESH_MS = 400L
         private const val ANALYSIS_INTERVAL_MS = 120L
         private val ANALYSIS_SIZE = Size(640, 480)
     }
@@ -732,3 +779,8 @@ private data class RawDetection(
     val result: RecognitionResult,
     val confidence: Float?
 )
+
+private data class CachedRecognition(
+    val result: RecognitionResult,
+    val updatedAtMs: Long
+)

app/src/main/java/com/example/studentfaceregistry/face/FaceProcessor.kt

@@ -128,7 +128,7 @@ class FaceProcessor(context: Context) : AutoCloseable {
     fun embedFace(bitmap: Bitmap, face: Face): FloatArray {
         val cropped = cropFace(bitmap, face.boundingBox)
         val aligned = alignFaceWithLandmarks(cropped, face, 0, 0)
-        val preprocessed = preprocessor.preprocess(aligned)
+        val preprocessed = preprocessor.preprocessRealtime(aligned)
         return embedder.embed(preprocessed)
     }
 

app/src/main/java/com/example/studentfaceregistry/face/ImagePreprocessor.kt

@@ -28,6 +28,13 @@ class ImagePreprocessor {
         return histogramEqualize(enhanced)
     }
 
+    /**
+     * 实时识别场景使用轻量预处理，减少每帧 CPU 开销。
+     */
+    fun preprocessRealtime(bitmap: Bitmap): Bitmap {
+        return enhanceBrightnessContrast(bitmap, brightness = 0.06f, contrast = 1.08f)
+    }
+
     /**
      * 亮度对比度增强
      * @param brightness 亮度调整 (-1 到 1，0 为不调整)