fixed a bug

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

@@ -27,8 +27,11 @@ import androidx.camera.core.ExperimentalGetImage
 import androidx.camera.core.ImageAnalysis
 import androidx.camera.core.ImageProxy
 import androidx.camera.core.Preview
+import androidx.camera.core.resolutionselector.ResolutionSelector
+import androidx.camera.core.resolutionselector.ResolutionStrategy
 import androidx.camera.lifecycle.ProcessCameraProvider
 import androidx.camera.view.PreviewView
+import androidx.core.content.edit
 import androidx.core.content.ContextCompat
 import androidx.lifecycle.lifecycleScope
 import com.example.studentfaceregistry.data.Student
@@ -98,8 +101,8 @@ class MainActivity : AppCompatActivity() {
                 startRecognitionSession()
             }
         } else if (currentMode == AppMode.RECOGNITION) {
-            recognitionStatusText.text = "需要相机权限才能识别学生身份。"
+            recognitionStatusText.setText(R.string.camera_permission_required)
-            toast("需要相机权限才能识别学生身份。")
+            toast(getString(R.string.camera_permission_required))
         }
     }
 
@@ -111,7 +114,7 @@ class MainActivity : AppCompatActivity() {
         lifecycleScope.launch {
             repository.students.collectLatest { list ->
                 students = list
-                countText.text = "已入库 ${list.size} 名学生"
+                countText.text = getString(R.string.registered_student_count, list.size)
             }
         }
 
@@ -354,7 +357,7 @@ class MainActivity : AppCompatActivity() {
             addView(uploadStatusText)
 
             addView(TextView(this@MainActivity).apply {
-                text = "在同一 Wi-Fi 下，用电脑浏览器打开下面的地址，就可以上传学生图片或视频。"
+                setText(R.string.upload_instructions)
                 textSize = 16f
                 setTextColor(0xFF475569.toInt())
                 gravity = Gravity.CENTER
@@ -460,8 +463,8 @@ class MainActivity : AppCompatActivity() {
                 if (faceProcessor == null) {
                     val error = created.exceptionOrNull()
                     val message = error?.message ?: error?.javaClass?.simpleName ?: "unknown error"
-                    recognitionStatusText.text = "模型初始化失败：$message"
+                    recognitionStatusText.text = getString(R.string.model_init_failed, message)
-                    toast("模型初始化失败：$message")
+                    toast(getString(R.string.model_init_failed, message))
                     return@withContext
                 }
                 processor = faceProcessor
@@ -482,11 +485,11 @@ class MainActivity : AppCompatActivity() {
                 }
 
                 val preview = Preview.Builder()
-                    .setTargetResolution(ANALYSIS_SIZE)
+                    .setResolutionSelector(analysisResolutionSelector())
                     .build()
-                    .also { it.setSurfaceProvider(previewView.surfaceProvider) }
+                    .also { it.surfaceProvider = previewView.surfaceProvider }
                 val analysis = ImageAnalysis.Builder()
-                    .setTargetResolution(ANALYSIS_SIZE)
+                    .setResolutionSelector(analysisResolutionSelector())
                     .setBackpressureStrategy(ImageAnalysis.STRATEGY_KEEP_ONLY_LATEST)
                     .build()
 
@@ -630,7 +633,10 @@ class MainActivity : AppCompatActivity() {
                 Log.e("MainActivity", "Recognition failed", e)
                 withContext(Dispatchers.Main) {
                     if (currentMode == AppMode.RECOGNITION) {
-                        recognitionStatusText.text = "识别失败：${e.message ?: e.javaClass.simpleName}"
+                        recognitionStatusText.text = getString(
+                            R.string.recognition_failed,
+                            e.message ?: e.javaClass.simpleName
+                        )
                     }
                 }
             } finally {
@@ -642,7 +648,7 @@ class MainActivity : AppCompatActivity() {
 
     private fun updateRecognitionStatus(detections: List<DetectionUi>) {
         if (detections.isEmpty()) {
-            recognitionStatusText.text = "未检测到人脸"
+            recognitionStatusText.setText(R.string.no_face_detected)
             return
         }
 
@@ -656,30 +662,35 @@ class MainActivity : AppCompatActivity() {
             if (matched.size == 1 && total == 1) {
                 val student = matched[0].result.student!!
                 val confidence = (matched[0].confidence!! * 100).toInt()
-                recognitionStatusText.text = "识别到：${student.name}（${student.studentNo}）置信度${confidence}%"
+                recognitionStatusText.text = getString(
+                    R.string.single_student_recognized,
+                    student.name,
+                    student.studentNo,
+                    confidence
+                )
             } else {
                 val names = matched.joinToString(", ") {
                     val student = it.result.student!!
                     val confidence = (it.confidence!! * 100).toInt()
-                    "${student.name}(${confidence}%)"
+                    getString(R.string.student_confidence_item, student.name, confidence)
                 }
                 val remaining = total - matched.size
                 recognitionStatusText.text = if (remaining > 0) {
-                    "识别到 ${matched.size}/$total 人：$names，另有 $remaining 人跟踪中"
+                    getString(R.string.multi_student_recognized_with_tracking, matched.size, total, names, remaining)
                 } else {
-                    "识别到 ${matched.size}/$total 人：$names"
+                    getString(R.string.multi_student_recognized, matched.size, total, names)
                 }
             }
         } else if (unsure.isNotEmpty()) {
-            recognitionStatusText.text = "疑似检测到 ${unsure.size} 人（不确定）"
+            recognitionStatusText.text = getString(R.string.unsure_faces_detected, unsure.size)
         } else if (tracking > 0) {
             recognitionStatusText.text = if (noMatch > 0) {
-                "跟踪到 $total 人，识别中 $tracking 人，$noMatch 人未匹配"
+                getString(R.string.tracking_with_no_match, total, tracking, noMatch)
             } else {
-                "跟踪到 $total 人，识别中 $tracking 人"
+                getString(R.string.tracking_faces, total, tracking)
             }
         } else {
-            recognitionStatusText.text = "检测到 $total 张未入库人脸"
+            recognitionStatusText.text = getString(R.string.unregistered_faces_detected, total)
         }
     }
 
@@ -700,7 +711,7 @@ class MainActivity : AppCompatActivity() {
             uploadUrlText.text = server.accessUrl()
         }.onFailure {
             val message = it.message ?: "unknown error"
-            uploadStatusText.text = "上传服务启动失败：$message"
+            uploadStatusText.text = getString(R.string.upload_service_start_failed, message)
             uploadUrlText.text = "-"
         }
     }
@@ -748,10 +759,10 @@ class MainActivity : AppCompatActivity() {
         euclideanThreshold = parsedEuclidean
         cosineThreshold = parsedCosine
         matcher = FaceMatcher(euclideanThreshold, cosineThreshold)
-        matcherPrefs.edit()
+        matcherPrefs.edit {
-            .putFloat(KEY_EUCLIDEAN_THRESHOLD, euclideanThreshold)
+            putFloat(KEY_EUCLIDEAN_THRESHOLD, euclideanThreshold)
-            .putFloat(KEY_COSINE_THRESHOLD, cosineThreshold)
+            putFloat(KEY_COSINE_THRESHOLD, cosineThreshold)
-            .apply()
+        }
 
         matcherConfigSummaryText.text = matcherConfigSummary()
         recognitionStatusText.text = "识别参数已更新"
@@ -759,7 +770,11 @@ class MainActivity : AppCompatActivity() {
     }
 
     private fun matcherConfigSummary(): String {
-        return "当前参数：欧氏 <= ${formatThreshold(euclideanThreshold)}，余弦 >= ${formatThreshold(cosineThreshold)}"
+        return getString(
+            R.string.matcher_config_summary,
+            formatThreshold(euclideanThreshold),
+            formatThreshold(cosineThreshold)
+        )
     }
 
     private fun applySuggestedThresholds() {
@@ -770,9 +785,12 @@ class MainActivity : AppCompatActivity() {
         val suggested = matcher.suggestThresholds(students)
         euclideanThresholdInput.setText(formatThreshold(suggested.euclidean))
         cosineThresholdInput.setText(formatThreshold(suggested.cosine))
-        matcherConfigSummaryText.text =
+        matcherConfigSummaryText.text = getString(
-            "建议参数（基于 ${students.size} 名学生）：欧氏 <= ${formatThreshold(suggested.euclidean)}，" +
+            R.string.suggested_matcher_config_summary,
-                "余弦 >= ${formatThreshold(suggested.cosine)}，点击“保存识别参数”生效"
+            students.size,
+            formatThreshold(suggested.euclidean),
+            formatThreshold(suggested.cosine)
+        )
         toast("已填入建议阈值，确认后点击保存")
     }
 
@@ -780,6 +798,17 @@ class MainActivity : AppCompatActivity() {
         return String.format(java.util.Locale.US, "%.2f", value)
     }
 
+    private fun analysisResolutionSelector(): ResolutionSelector {
+        return ResolutionSelector.Builder()
+            .setResolutionStrategy(
+                ResolutionStrategy(
+                    ANALYSIS_SIZE,
+                    ResolutionStrategy.FALLBACK_RULE_CLOSEST_HIGHER_THEN_LOWER
+                )
+            )
+            .build()
+    }
+
     private fun mapDetectionsToPreview(image: ImageProxy, rawDetections: List<RawDetection>): List<DetectionUi> {
         val previewWidth = previewView.width.toFloat()
         val previewHeight = previewView.height.toFloat()

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

@@ -13,8 +13,6 @@ import com.google.mlkit.vision.face.FaceDetectorOptions
 import com.google.mlkit.vision.face.FaceLandmark
 import kotlinx.coroutines.tasks.await
 import kotlin.math.abs
-import kotlin.math.PI
-import kotlin.math.atan2
 import kotlin.math.roundToInt
 import kotlin.math.sqrt
 
@@ -240,26 +238,14 @@ class SmartEnrollment(context: Context) : AutoCloseable {
      * 计算偏航角（左右转头）
      */
     private fun yawAngle(face: Face): Float {
-        val leftCheek = face.getLandmark(FaceLandmark.LEFT_CHEEK) ?: return 0f
+        return face.headEulerAngleY
-        val rightCheek = face.getLandmark(FaceLandmark.RIGHT_CHEEK) ?: return 0f
-
-        val dx = rightCheek.position.x - leftCheek.position.x
-        val dy = rightCheek.position.y - leftCheek.position.y
-        return atan2(dy.toDouble(), dx.toDouble()).toFloat() * 180f / PI.toFloat()
     }
 
     /**
      * 计算俯仰角（上下点头）
      */
     private fun pitchAngle(face: Face): Float {
-        val nose = face.getLandmark(FaceLandmark.NOSE_BASE) ?: return 0f
+        return face.headEulerAngleX
-        val leftEye = face.getLandmark(FaceLandmark.LEFT_EYE) ?: return 0f
-        val rightEye = face.getLandmark(FaceLandmark.RIGHT_EYE) ?: return 0f
-
-        val eyeCenterY = (leftEye.position.y + rightEye.position.y) / 2f
-        val dx = nose.position.x - (leftEye.position.x + rightEye.position.x) / 2f
-        val dy = nose.position.y - eyeCenterY
-        return atan2(dy.toDouble(), dx.toDouble()).toFloat() * 180f / PI.toFloat()
     }
 
     /**

app/src/main/res/values/strings.xml

@@ -1,4 +1,21 @@
 <?xml version="1.0" encoding="utf-8"?>
 <resources>
     <string name="app_name">学生人脸识别</string>
+    <string name="camera_permission_required">需要相机权限才能识别学生身份。</string>
+    <string name="registered_student_count">已入库 %1$d 名学生</string>
+    <string name="upload_instructions">在同一 Wi-Fi 下，用电脑浏览器打开下面的地址，就可以上传学生图片或视频。</string>
+    <string name="model_init_failed">模型初始化失败：%1$s</string>
+    <string name="recognition_failed">识别失败：%1$s</string>
+    <string name="no_face_detected">未检测到人脸</string>
+    <string name="single_student_recognized">识别到：%1$s（%2$s）置信度%3$d%%</string>
+    <string name="student_confidence_item">%1$s(%2$d%%)</string>
+    <string name="multi_student_recognized_with_tracking">识别到 %1$d/%2$d 人：%3$s，另有 %4$d 人跟踪中</string>
+    <string name="multi_student_recognized">识别到 %1$d/%2$d 人：%3$s</string>
+    <string name="unsure_faces_detected">疑似检测到 %1$d 人（不确定）</string>
+    <string name="tracking_with_no_match">跟踪到 %1$d 人，识别中 %2$d 人，%3$d 人未匹配</string>
+    <string name="tracking_faces">跟踪到 %1$d 人，识别中 %2$d 人</string>
+    <string name="unregistered_faces_detected">检测到 %1$d 张未入库人脸</string>
+    <string name="upload_service_start_failed">上传服务启动失败：%1$s</string>
+    <string name="matcher_config_summary">当前参数：欧氏 &lt;= %1$s，余弦 &gt;= %2$s</string>
+    <string name="suggested_matcher_config_summary">建议参数（基于 %1$d 名学生）：欧氏 &lt;= %2$s，余弦 &gt;= %3$s，点击“保存识别参数”生效</string>
 </resources>