继续优化

AGENTS.md

@@ -0,0 +1,65 @@
+# AGENTS.md
+
+Behavioral guidelines to reduce common LLM coding mistakes. Merge with project-specific instructions as needed.
+
+**Tradeoff:** These guidelines bias toward caution over speed. For trivial tasks, use judgment.
+
+## 1. Think Before Coding
+
+**Don't assume. Don't hide confusion. Surface tradeoffs.**
+
+Before implementing:
+- State your assumptions explicitly.
+- If multiple interpretations exist, present them - don't pick silently.
+- If a simpler approach exists, say so. Push back when warranted.
+- If something is unclear, stop. Name what's confusing. Ask.
+
+## 2. Simplicity First
+
+**Minimum code that solves the problem. Nothing speculative.**
+
+- No features beyond what was asked.
+- No abstractions for single-use code.
+- No "flexibility" or "configurability" that wasn't requested.
+- No error handling for impossible scenarios.
+- If you write 200 lines and it could be 50, rewrite it.
+
+Ask yourself: "Would a senior engineer say this is overcomplicated?" If yes, simplify.
+
+## 3. Surgical Changes
+
+**Touch only what you must. Clean up only your own mess.**
+
+When editing existing code:
+- Don't "improve" adjacent code, comments, or formatting.
+- Don't refactor things that aren't broken.
+- Match existing style, even if you'd do it differently.
+- If you notice unrelated dead code, mention it - don't delete it.
+
+When your changes create orphans:
+- Remove imports/variables/functions that YOUR changes made unused.
+- Don't remove pre-existing dead code unless asked.
+
+The test: Every changed line should trace directly to the user's request.
+
+## 4. Goal-Driven Execution
+
+**Define success criteria. Loop until verified.**
+
+Transform tasks into verifiable goals:
+- "Add validation" → "Write tests for invalid inputs, then make them pass"
+- "Fix the bug" → "Write a test that reproduces it, then make it pass"
+- "Refactor X" → "Ensure tests pass before and after"
+
+For multi-step tasks, state a brief plan:
+```
+1. [Step] → verify: [check]
+2. [Step] → verify: [check]
+3. [Step] → verify: [check]
+```
+
+Strong success criteria let you loop independently. Weak criteria ("make it work") require constant clarification.
+
+---
+
+**These guidelines are working if:** fewer unnecessary changes in diffs, fewer rewrites due to overcomplication, and clarifying questions come before implementation rather than after mistakes.

README.md

@@ -28,13 +28,12 @@ http://192.168.1.23:8080
 
 让电脑和手机连接同一个 Wi-Fi，然后在电脑浏览器打开这个地址。网页里可以一次选择多张学生头像，点击上传后，手机会本地检测人脸、生成 embedding 并写入本地数据库。
 
-网页同时支持两种批量导入方式：
+网页支持按文件夹批量导入：
 
-- 选择一个文件夹，自动上传文件夹里的所有图片
+- 选择一个文件夹，自动上传文件夹里的图片或视频
-- 上传一个 `.zip` 压缩包，手机端自动解压后入库
 
 文件夹选择在 Chrome / Edge 这类支持目录选择的浏览器里效果最好。
-大批量导入时优先选择文件夹上传；网页会逐张发送图片，手机端内存压力更小。
+网页会逐个发送文件，手机端内存压力更小。
 
 ## 头像命名规则
 

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

@@ -0,0 +1,484 @@
+package com.example.studentfaceregistry.face
+
+import android.content.Context
+import android.graphics.Bitmap
+import android.graphics.BitmapFactory
+import android.graphics.Rect
+import android.media.MediaDataSource
+import android.media.MediaMetadataRetriever
+import com.google.mlkit.vision.common.InputImage
+import com.google.mlkit.vision.face.Face
+import com.google.mlkit.vision.face.FaceDetection
+import com.google.mlkit.vision.face.FaceDetectorOptions
+import kotlinx.coroutines.tasks.await
+import kotlin.math.atan2
+import kotlin.math.sqrt
+
+/**
+ * 智能注册器
+ * 支持图片和视频两种输入方式，自动选择最大人脸进行注册
+ *
+ * 功能特性：
+ * 1. 自动识别输入类型（图片或视频）
+ * 2. 自动检测并选择最大的人脸
+ * 3. 视频注册时自动提取多角度帧并融合特征
+ */
+class SmartEnrollment(context: Context) {
+
+    // 高精度人脸检测器（用于注册）
+    private val detector = FaceDetection.getClient(
+        FaceDetectorOptions.Builder()
+            .setPerformanceMode(FaceDetectorOptions.PERFORMANCE_MODE_ACCURATE)
+            .setLandmarkMode(FaceDetectorOptions.LANDMARK_MODE_ALL)
+            .setMinFaceSize(0.03f)
+            .build()
+    )
+
+    private val embedder = FaceEmbedder(context, FaceEmbedder.ModelType.ARCFACE)
+    private val aligner = FaceAligner()
+    private val preprocessor = ImagePreprocessor()
+
+    /**
+     * 智能注册入口
+     * @param data 数据字节（图片或视频）
+     * @param mimeType MIME 类型，如 "image/jpeg", "video/mp4"
+     * @param fileName 文件名（用于提取学号和姓名）
+     * @return 注册结果
+     */
+    suspend fun enroll(
+        data: ByteArray,
+        mimeType: String?,
+        fileName: String
+    ): EnrollmentResult {
+        return if (isVideo(mimeType, fileName)) {
+            enrollFromVideo(data)
+        } else {
+            enrollFromImage(data)
+        }
+    }
+
+    /**
+     * 从图片注册
+     */
+    private suspend fun enrollFromImage(data: ByteArray): EnrollmentResult {
+        return try {
+            // 解码图片
+            val bitmap = decodeBitmap(data)
+
+            // 检测人脸并只保留可安全裁剪的人脸区域
+            val faces = detectUsableFaces(bitmap)
+
+            if (faces.isEmpty()) {
+                return EnrollmentResult.Failure("未检测到人脸，请换更清晰或更正面的照片。")
+            }
+
+            // 选择最大的人脸
+            val largestFace = faces.maxBy { faceInfo ->
+                faceInfo.faceArea
+            }
+
+            // 裁剪人脸
+            val croppedFace = cropFace(bitmap, largestFace.cropRect)
+
+            // 对齐
+            val alignedFace = alignFace(croppedFace, largestFace.face, largestFace.cropRect)
+
+            // 预处理
+            val preprocessedFace = preprocessor.preprocess(alignedFace)
+
+            // 提取特征
+            val embedding = embedder.embed(preprocessedFace)
+
+            EnrollmentResult.Success(embedding, EnrollmentSourceType.IMAGE)
+        } catch (e: Exception) {
+            EnrollmentResult.Failure("图片处理失败：${e.message}")
+        }
+    }
+
+    /**
+     * 从视频注册
+     * @param data 视频字节
+     * @param minFrames 最少帧数
+     * @param maxFrames 最大帧数（用于融合）
+     */
+    private suspend fun enrollFromVideo(
+        data: ByteArray,
+        minFrames: Int = 10,
+        maxFrames: Int = 30
+    ): EnrollmentResult {
+        return try {
+            // 提取视频帧
+            val frames = extractVideoFrames(data, maxFrames * 2)
+
+            if (frames.size < minFrames) {
+                return EnrollmentResult.Failure(
+                    "视频有效帧数不足（检测到 ${frames.size} 帧，需要至少 $minFrames 帧），" +
+                    "请确保视频中人脸清晰且持续展示足够时间。"
+                )
+            }
+
+            // 对每帧选择最大人脸
+            val faceFrames = frames.mapNotNull { bitmap ->
+                val faces = detectUsableFaces(bitmap)
+                if (faces.isEmpty()) return@mapNotNull null
+
+                val largestFace = faces.maxBy { faceInfo ->
+                    faceInfo.faceArea
+                }
+
+                FaceFrameInfo(bitmap, largestFace.face, largestFace.cropRect, largestFace.faceArea)
+            }
+
+            if (faceFrames.size < minFrames) {
+                return EnrollmentResult.Failure(
+                    "视频有效人脸帧数不足（检测到 ${faceFrames.size} 帧，需要至少 $minFrames 帧）"
+                )
+            }
+
+            // 计算每帧的角度并分组
+            val groupedFrames = groupFramesByAngle(faceFrames)
+
+            // 从每组选择质量最好的帧
+            val selectedFrames = selectBestFramesFromGroups(groupedFrames, maxFrames)
+
+            // 提取每帧的特征
+            val embeddings = selectedFrames.map { frameInfo ->
+                val cropped = cropFace(frameInfo.bitmap, frameInfo.cropRect)
+                val aligned = alignFace(cropped, frameInfo.face, frameInfo.cropRect)
+                val preprocessed = preprocessor.preprocess(aligned)
+                embedder.embed(preprocessed)
+            }
+
+            // 融合特征
+            val fusedEmbedding = fuseEmbeddings(embeddings)
+
+            // 计算角度覆盖
+            val yawRange = calculateAngleRange(selectedFrames, { f -> yawAngle(f.face) })
+            val pitchRange = calculateAngleRange(selectedFrames, { f -> pitchAngle(f.face) })
+
+            EnrollmentResult.Success(
+                embedding = fusedEmbedding,
+                sourceType = EnrollmentSourceType.VIDEO,
+                frameCount = selectedFrames.size,
+                yawRange = yawRange,
+                pitchRange = pitchRange
+            )
+        } catch (e: Exception) {
+            EnrollmentResult.Failure("视频处理失败：${e.message}")
+        }
+    }
+
+    /**
+     * 提取视频帧
+     */
+    private fun extractVideoFrames(videoData: ByteArray, maxFrames: Int): List<Bitmap> {
+        val retriever = MediaMetadataRetriever()
+        val dataSource = ByteArrayVideoDataSource(videoData)
+
+        return try {
+            retriever.setDataSource(dataSource)
+
+            val duration = retriever.extractMetadata(MediaMetadataRetriever.METADATA_KEY_DURATION)?.toLongOrNull() ?: 0
+            val frameInterval = maxOf(100, (duration / maxFrames).toInt())  // 至少每 100ms 一帧
+
+            val frames = mutableListOf<Bitmap>()
+            var timeUs = 0L
+
+            while (timeUs < duration * 1000) {
+                try {
+                    val bitmap = retriever.getFrameAtTime(timeUs, MediaMetadataRetriever.OPTION_CLOSEST)
+                    if (bitmap != null && !bitmap.isRecycled) {
+                        frames.add(bitmap)
+                    }
+                } catch (e: Exception) {
+                    // 跳过错误帧
+                }
+                timeUs += (frameInterval * 1000).toLong()  // 转换为微秒
+            }
+
+            frames
+        } finally {
+            retriever.release()
+            dataSource.close()
+        }
+    }
+
+    /**
+     * 计算偏航角（左右转头）
+     */
+    private fun yawAngle(face: Face): Float {
+        val leftCheek = face.leftCheek ?: return 0f
+        val rightCheek = face.rightCheek ?: return 0f
+        if (!leftCheek.visible || !rightCheek.visible) 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 / 3.14159
+    }
+
+    /**
+     * 计算俯仰角（上下点头）
+     */
+    private fun pitchAngle(face: Face): Float {
+        val nose = face.nose ?: return 0f
+        val leftEye = face.leftEye ?: return 0f
+        val rightEye = face.rightEye ?: return 0f
+        if (!nose.visible || !leftEye.visible || !rightEye.visible) 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 / 3.14159
+    }
+
+    /**
+     * 按角度分组
+     */
+    private fun groupFramesByAngle(frames: List<FaceFrameInfo>): Map<AngleBucket, List<FaceFrameInfo>> {
+        val buckets = mutableMapOf<AngleBucket, MutableList<FaceFrameInfo>>()
+
+        for (frame in frames) {
+            val yaw = yawAngle(frame.face)
+            val pitch = pitchAngle(frame.face)
+            val bucket = AngleBucket(
+                yawBucket = when {
+                    yaw < -30 -> -2
+                    yaw < -10 -> -1
+                    yaw < 10 -> 0
+                    yaw < 30 -> 1
+                    else -> 2
+                },
+                pitchBucket = when {
+                    pitch < -15 -> -1
+                    pitch < 15 -> 0
+                    else -> 1
+                }
+            )
+            if (!buckets.containsKey(bucket)) buckets[bucket] = mutableListOf()
+            buckets[bucket]!!.add(frame)
+        }
+
+        return buckets
+    }
+
+    /**
+     * 从每组选择最佳帧
+     */
+    private fun selectBestFramesFromGroups(
+        groups: Map<AngleBucket, List<FaceFrameInfo>>,
+        maxFrames: Int
+    ): List<FaceFrameInfo> {
+        val selected = mutableListOf<FaceFrameInfo>()
+
+        // 按组内最大人脸面积排序
+        val sortedGroups = groups.entries.sortedByDescending { entry ->
+            entry.value.maxOfOrNull {
+                it.faceArea
+            } ?: 0
+        }
+
+        for ((_, frames) in sortedGroups) {
+            val sortedFrames = frames.sortedByDescending {
+                it.faceArea
+            }
+            for (frame in sortedFrames) {
+                if (selected.size >= maxFrames) break
+                selected.add(frame)
+            }
+        }
+
+        return selected
+    }
+
+    /**
+     * 融合多个特征向量
+     */
+    private fun fuseEmbeddings(embeddings: List<FloatArray>): FloatArray {
+        if (embeddings.isEmpty()) throw IllegalArgumentException("embeddings is empty")
+        if (embeddings.size == 1) return embeddings[0]
+
+        val size = embeddings[0].size
+        val sum = FloatArray(size)
+
+        for (embedding in embeddings) {
+            for (i in 0 until size) {
+                sum[i] += embedding[i]
+            }
+        }
+
+        // 平均
+        for (i in 0 until size) {
+            sum[i] /= embeddings.size
+        }
+
+        // L2 归一化
+        return l2Normalize(sum)
+    }
+
+    /**
+     * 计算角度范围
+     */
+    private fun calculateAngleRange(
+        frames: List<FaceFrameInfo>,
+        angleExtractor: (FaceFrameInfo) -> Float
+    ): Float {
+        if (frames.isEmpty()) return 0f
+        val angles = frames.map(angleExtractor)
+        return angles.maxOrNull()!! - angles.minOrNull()!!
+    }
+
+    /**
+     * 裁剪人脸
+     */
+    private fun cropFace(bitmap: Bitmap, box: Rect): Bitmap {
+        return Bitmap.createBitmap(bitmap, box.left, box.top, box.width(), box.height())
+    }
+
+    private suspend fun detectUsableFaces(bitmap: Bitmap): List<DetectedFace> {
+        return detector.process(InputImage.fromBitmap(bitmap, 0)).await()
+            .mapNotNull { face ->
+                val cropRect = safeCropRect(bitmap, face.boundingBox) ?: return@mapNotNull null
+                val faceArea = face.boundingBox.width() * face.boundingBox.height()
+                DetectedFace(face, cropRect, faceArea)
+            }
+    }
+
+    private fun safeCropRect(bitmap: Bitmap, box: Rect): Rect? {
+        if (box.width() <= 0 || box.height() <= 0) return null
+
+        val padding = (maxOf(box.width(), box.height()) * 0.25f).toInt()
+        val left = (box.left - padding).coerceIn(0, bitmap.width)
+        val top = (box.top - padding).coerceIn(0, bitmap.height)
+        val right = (box.right + padding).coerceIn(0, bitmap.width)
+        val bottom = (box.bottom + padding).coerceIn(0, bitmap.height)
+        if (right - left <= 1 || bottom - top <= 1) return null
+
+        return Rect(left, top, right, bottom)
+    }
+
+    /**
+     * 对齐人脸
+     */
+    private fun alignFace(bitmap: Bitmap, face: Face, cropRect: Rect): Bitmap {
+        val leftEye = face.leftEye ?: return bitmap
+        val rightEye = face.rightEye ?: return bitmap
+        if (!leftEye.visible || !rightEye.visible) return bitmap
+
+        return aligner.align(
+            bitmap = bitmap,
+            leftEyeX = leftEye.position.x,
+            leftEyeY = leftEye.position.y,
+            rightEyeX = rightEye.position.x,
+            rightEyeY = rightEye.position.y,
+            faceLeft = cropRect.left,
+            faceTop = cropRect.top
+        )
+    }
+
+    /**
+     * 解码 Bitmap
+     */
+    private fun decodeBitmap(data: ByteArray): Bitmap {
+        val bounds = BitmapFactory.Options().apply { inJustDecodeBounds = true }
+        BitmapFactory.decodeByteArray(data, 0, data.size, bounds)
+
+        val maxSide = maxOf(bounds.outWidth, bounds.outHeight).coerceAtLeast(1)
+        var sampleSize = 1
+        while (maxSide / sampleSize > 1280) sampleSize *= 2
+
+        val options = BitmapFactory.Options().apply {
+            inSampleSize = sampleSize
+            inPreferredConfig = Bitmap.Config.ARGB_8888
+        }
+        return BitmapFactory.decodeByteArray(data, 0, data.size, options)
+            ?: throw IllegalArgumentException("Unable to decode image")
+    }
+
+    /**
+     * L2 归一化
+     */
+    private fun l2Normalize(values: FloatArray): FloatArray {
+        var sum = 0f
+        for (value in values) sum += value * value
+        val norm = sqrt(sum.coerceAtLeast(1e-12f))
+        return FloatArray(values.size) { values[it] / norm }
+    }
+
+    /**
+     * 判断是否为视频
+     */
+    private fun isVideo(mimeType: String?, fileName: String): Boolean {
+        val lowerMimeType = mimeType?.lowercase().orEmpty()
+        val lowerFileName = fileName.lowercase()
+        return lowerMimeType.startsWith("video/") ||
+               lowerMimeType in VIDEO_MIME_TYPES ||
+               VIDEO_EXTENSIONS.any { lowerFileName.endsWith(it) }
+    }
+
+    override fun close() {
+        detector.close()
+        embedder.close()
+    }
+
+    companion object {
+        private val VIDEO_EXTENSIONS = setOf(".mp4", ".avi", ".mov", ".wmv", ".flv", ".mkv", ".webm", ".3gp")
+        private val VIDEO_MIME_TYPES = setOf("application/mp4")
+    }
+}
+
+private data class DetectedFace(
+    val face: Face,
+    val cropRect: Rect,
+    val faceArea: Int
+)
+
+/**
+ * 人脸帧信息
+ */
+private data class FaceFrameInfo(
+    val bitmap: Bitmap,
+    val face: Face,
+    val cropRect: Rect,
+    val faceArea: Int
+)
+
+private class ByteArrayVideoDataSource(private val data: ByteArray) : MediaDataSource() {
+    override fun readAt(position: Long, buffer: ByteArray, offset: Int, size: Int): Int {
+        if (position >= data.size) return -1
+        val length = minOf(size, data.size - position.toInt())
+        System.arraycopy(data, position.toInt(), buffer, offset, length)
+        return length
+    }
+
+    override fun getSize(): Long = data.size.toLong()
+
+    override fun close() = Unit
+}
+
+/**
+ * 角度分组
+ */
+private data class AngleBucket(val yawBucket: Int, val pitchBucket: Int)
+
+/**
+ * 注册结果
+ */
+sealed class EnrollmentResult {
+    data class Success(
+        val embedding: FloatArray,
+        val sourceType: EnrollmentSourceType = EnrollmentSourceType.IMAGE,
+        val frameCount: Int = 1,
+        val yawRange: Float = 0f,
+        val pitchRange: Float = 0f
+    ) : EnrollmentResult()
+
+    data class Failure(val reason: String) : EnrollmentResult()
+}
+
+/**
+ * 注册源类型
+ */
+enum class EnrollmentSourceType {
+    IMAGE,   // 图片注册
+    VIDEO    // 视频注册
+}

app/src/main/java/com/example/studentfaceregistry/upload/UploadServer.kt

@@ -1,15 +1,14 @@
 package com.example.studentfaceregistry.upload
 
 import android.content.Context
-import android.graphics.BitmapFactory
 import android.util.Base64
 import com.example.studentfaceregistry.data.Student
 import com.example.studentfaceregistry.data.StudentRepository
 import com.example.studentfaceregistry.face.FaceProcessor
+import com.example.studentfaceregistry.face.SmartEnrollment
 import kotlinx.coroutines.runBlocking
 import org.json.JSONObject
 import java.io.BufferedInputStream
-import java.io.ByteArrayInputStream
 import java.io.ByteArrayOutputStream
 import java.io.OutputStream
 import java.net.Inet4Address
@@ -17,7 +16,6 @@ import java.net.NetworkInterface
 import java.net.ServerSocket
 import java.net.Socket
 import java.nio.charset.StandardCharsets
-import java.util.zip.ZipInputStream
 import kotlin.concurrent.thread
 
 class UploadServer(
@@ -27,10 +25,12 @@ class UploadServer(
 ) : AutoCloseable {
     private var serverSocket: ServerSocket? = null
     @Volatile private var running = false
+    private lateinit var smartEnrollment: SmartEnrollment
 
     fun start() {
         if (running) return
         running = true
+        smartEnrollment = SmartEnrollment(context)
         serverSocket = ServerSocket(8080)
         thread(name = "upload-server", isDaemon = true) {
             while (running) {
@@ -52,6 +52,7 @@ class UploadServer(
     override fun close() {
         running = false
         runCatching { serverSocket?.close() }
+        runCatching { smartEnrollment.close() }
     }
 
     private fun handle(socket: Socket) {
@@ -70,8 +71,7 @@ class UploadServer(
     }
 
     private fun handleUpload(request: HttpRequest, output: OutputStream) {
-        val processor = processorProvider()
+        if (processorProvider() == null) {
-        if (processor == null) {
             respondText(output, 503, "Missing facenet.tflite model", "text/plain; charset=utf-8")
             return
         }
@@ -82,10 +82,10 @@ class UploadServer(
 
         runCatching {
             val payload = JSONObject(bodyText)
-            val zipBase64 = payload.optString("zipBase64", "")
+            // 单文件或文件列表上传（支持图片和视频）
-            if (zipBase64.isNotBlank()) {
+            val items = parseUploadItems(payload)
-                val zipBytes = Base64.decode(zipBase64, Base64.DEFAULT)
+            items.forEachIndexed { index, item ->
-                processZip(zipBytes, processor) { ok, name, error ->
+                processUploadItem(item.fileName.ifBlank { "student_$index" }, item.base64, item.mimeType) { ok, name, error ->
                     if (ok) {
                         accepted += 1
                         notices += "OK $name"
@@ -94,19 +94,6 @@ class UploadServer(
                         notices += "FAIL $name: $error"
                     }
                 }
-            } else {
-                val images = parseImages(payload)
-                images.forEachIndexed { index, item ->
-                    processImage(item.fileName.ifBlank { "student_$index.jpg" }, item.base64, processor) { ok, name, error ->
-                        if (ok) {
-                            accepted += 1
-                            notices += "OK $name"
-                        } else {
-                            rejected += 1
-                            notices += "FAIL $name: $error"
-                        }
-                    }
-                }
             }
         }.onFailure {
             respondText(output, 400, """{"accepted":0,"rejected":0,"message":${jsonString(it.message ?: "invalid request")}}""", "application/json; charset=utf-8")
@@ -126,7 +113,7 @@ class UploadServer(
             <head>
               <meta charset="utf-8">
               <meta name="viewport" content="width=device-width, initial-scale=1">
-              <title>学生头像上传</title>
+              <title>学生人脸注册上传</title>
               <style>
                 body { font-family: -apple-system, BlinkMacSystemFont, sans-serif; margin: 24px; max-width: 920px; }
                 input, button { font-size: 16px; padding: 10px; margin: 8px 0; }
@@ -135,18 +122,13 @@ class UploadServer(
               </style>
             </head>
             <body>
-              <h2>学生头像批量上传</h2>
+              <h2>学生人脸注册上传</h2>
-              <p class="hint">在电脑上选择头像，点击上传后，手机会本地生成人脸特征并保存。文件名建议使用 学号_姓名.jpg。</p>
+              <p class="hint">选择学生图片或视频后上传，手机会自动按文件类型注册，并优先使用画面中最大的人脸。文件名建议使用 学号_姓名.jpg 或 学号_姓名.mp4。</p>
               <div>
                 <label>上传文件夹</label><br>
-                <input id="folderFiles" type="file" multiple webkitdirectory directory accept="image/*"><br>
+                <input id="folderFiles" type="file" multiple webkitdirectory directory accept="image/*,video/*"><br>
                 <button id="uploadFolderBtn">上传文件夹</button>
               </div>
-              <div>
-                <label>上传压缩包</label><br>
-                <input id="zipFile" type="file" accept=".zip,application/zip"><br>
-                <button id="uploadZipBtn">上传 zip</button>
-              </div>
               <pre id="result"></pre>
               <script>
                 const result = document.getElementById('result');
@@ -163,7 +145,7 @@ class UploadServer(
                     const resp = await fetch('/upload', {
                       method: 'POST',
                       headers: { 'Content-Type': 'application/json' },
-                      body: JSON.stringify({ images: [{ fileName: file.name, base64 }] })
+                      body: JSON.stringify({ items: [{ fileName: file.name, base64, mimeType: file.type }] })
                     });
                     const text = await resp.text();
                     logs.push(text);
@@ -177,21 +159,6 @@ class UploadServer(
                   }
                   result.textContent = `完成：成功 ${'$'}{ok}，失败 ${'$'}{fail}\n\n` + logs.join('\n');
                 };
-                document.getElementById('uploadZipBtn').onclick = async () => {
-                  result.textContent = '上传中...';
-                  const file = document.getElementById('zipFile').files[0];
-                  if (!file) {
-                    result.textContent = '请选择 zip 文件';
-                    return;
-                  }
-                  const base64 = await toBase64(file);
-                  const resp = await fetch('/upload', {
-                    method: 'POST',
-                    headers: { 'Content-Type': 'application/json' },
-                    body: JSON.stringify({ zipFileName: file.name, zipBase64: base64 })
-                  });
-                  result.textContent = await resp.text();
-                };
                 function toBase64(file) {
                   return new Promise((resolve, reject) => {
                     const reader = new FileReader();
@@ -207,105 +174,66 @@ class UploadServer(
         respondText(output, 200, html, "text/html; charset=utf-8")
     }
 
-    private fun parseImages(root: JSONObject): List<UploadedImage> {
+    private fun parseUploadItems(root: JSONObject): List<UploadItem> {
-        val array = root.optJSONArray("images") ?: org.json.JSONArray()
+        val array = root.optJSONArray("items") ?: root.optJSONArray("images") ?: org.json.JSONArray()
         return buildList {
             for (index in 0 until array.length()) {
                 val item = array.optJSONObject(index) ?: continue
                 add(
-                    UploadedImage(
+                    UploadItem(
-                        fileName = item.optString("fileName", "student_$index.jpg"),
+                        fileName = item.optString("fileName", "student_$index"),
-                        base64 = item.optString("base64", "")
+                        base64 = item.optString("base64", ""),
+                        mimeType = item.optString("mimeType", "")
                     )
                 )
             }
         }
     }
 
-    private fun processZip(
+    private fun processUploadItem(fileName: String, base64: String, mimeType: String, report: (ok: Boolean, name: String, error: String?) -> Unit) {
-        zipBytes: ByteArray,
+        runCatching {
-        processor: FaceProcessor,
+            val data = Base64.decode(base64, Base64.DEFAULT)
-        report: (ok: Boolean, name: String, error: String?) -> Unit
+            processBytes(fileName, data, mimeType, report)
-    ) {
+        }.onFailure {
-        ZipInputStream(ByteArrayInputStream(zipBytes)).use { zip ->
+            report(false, fileName, it.message)
-            var entry = zip.nextEntry
+        }
-            while (entry != null) {
+    }
-                val entryName = entry.name
+
-                if (!entry.isDirectory && isImageFile(entryName)) {
+    private fun processBytes(fileName: String, data: ByteArray, mimeType: String, report: (ok: Boolean, name: String, error: String?) -> Unit) {
-                    val imageBytes = zip.readBytes()
+        runCatching {
-                    processImageBytes(entryName, imageBytes, processor, report)
+            val result = runBlocking {
-                }
+                smartEnrollment.enroll(data, mimeType, fileName)
-                zip.closeEntry()
-                entry = zip.nextEntry
             }
-        }
-    }
 
-    private fun processImage(
+            when (result) {
-        fileName: String,
+                is com.example.studentfaceregistry.face.EnrollmentResult.Success -> {
-        base64: String,
+                    val (studentNo, name) = parseStudent(fileName)
-        processor: FaceProcessor,
+                    repository.add(
-        report: (ok: Boolean, name: String, error: String?) -> Unit
+                        Student(
-    ) {
+                            studentNo = studentNo,
-        runCatching {
+                            name = name,
-            val imageBytes = Base64.decode(base64, Base64.DEFAULT)
+                            photoUri = "upload://$fileName",
-            processImageBytes(fileName, imageBytes, processor, report)
+                            embedding = result.embedding
+                        )
+                    )
+                    val sourceInfo = if (result.sourceType == com.example.studentfaceregistry.face.EnrollmentSourceType.VIDEO) {
+                        "（视频${result.frameCount}帧）"
+                    } else ""
+                    report(true, fileName + sourceInfo, null)
+                }
+                is com.example.studentfaceregistry.face.EnrollmentResult.Failure -> {
+                    report(false, fileName, result.reason)
+                }
+            }
         }.onFailure {
             report(false, fileName, it.message)
         }
     }
 
-    private fun processImageBytes(
-        fileName: String,
-        imageBytes: ByteArray,
-        processor: FaceProcessor,
-        report: (ok: Boolean, name: String, error: String?) -> Unit
-    ) {
-        runCatching {
-            val bitmap = decodeBitmap(imageBytes)
-            val embedding = runBlocking { processor.embedSingleFace(bitmap) }
-            val (studentNo, name) = parseStudent(fileName)
-            repository.add(
-                Student(
-                    studentNo = studentNo,
-                    name = name,
-                    photoUri = "upload://$fileName",
-                    embedding = embedding
-                )
-            )
-            report(true, fileName, null)
-        }.onFailure {
-            report(false, fileName, it.message)
-        }
-    }
-
-    private fun isImageFile(name: String): Boolean {
-        val lower = name.lowercase()
-        return lower.endsWith(".jpg") || lower.endsWith(".jpeg") || lower.endsWith(".png") || lower.endsWith(".webp")
-    }
-
-    private fun decodeBitmap(imageBytes: ByteArray): android.graphics.Bitmap {
-        val bounds = BitmapFactory.Options().apply {
-            inJustDecodeBounds = true
-        }
-        BitmapFactory.decodeByteArray(imageBytes, 0, imageBytes.size, bounds)
-        val maxSide = maxOf(bounds.outWidth, bounds.outHeight).coerceAtLeast(1)
-        var sampleSize = 1
-        while (maxSide / sampleSize > 1280) {
-            sampleSize *= 2
-        }
-        val options = BitmapFactory.Options().apply {
-            inSampleSize = sampleSize
-            inPreferredConfig = android.graphics.Bitmap.Config.ARGB_8888
-        }
-        return BitmapFactory.decodeByteArray(imageBytes, 0, imageBytes.size, options)
-            ?: error("Unable to decode image")
-    }
-
     private fun parseStudent(filename: String): Pair<String, String> {
         val base = filename.substringBeforeLast(".")
         val parts = base.split(Regex("[_\\-\\s]+"), limit = 2).map { it.trim() }
-        return if (parts.size == 2 && parts[0].isNotBlank() && parts[1].isNotBlank()) {
+        return if (parts.size == 2 && parts[0].isNotEmpty() && parts[1].isNotEmpty()) {
             parts[0] to parts[1]
         } else {
             base to base
@@ -334,7 +262,7 @@ class UploadServer(
             previous = current
         }
         val headerText = headerBytes.toString(StandardCharsets.ISO_8859_1.name())
-        val lines = headerText.split("\r\n").filter { it.isNotBlank() }
+        val lines = headerText.split("\r\n").filter { it.isNotEmpty() }
         val requestLine = lines.firstOrNull().orEmpty().split(" ")
         val method = requestLine.getOrNull(0).orEmpty()
         val path = requestLine.getOrNull(1).orEmpty()
@@ -399,7 +327,8 @@ private data class HttpRequest(
     val body: ByteArray
 )
 
-private data class UploadedImage(
+private data class UploadItem(
     val fileName: String,
-    val base64: String
+    val base64: String,
+    val mimeType: String = ""
 )