feat: 扫描整理并行化、WebSocket 实时进度与统计看板
- 移动阶段并行处理文件，按原子计数上报累计进度 - 扫描遍历阶段实时上报已发现文件数，界面不再卡在 0/0 - 新增 /api/scan/ws WebSocket 实时推送扫描状态；前端断线指数退避自动重连，并以低频轮询兜底 - 新增统计看板与媒体库筛选/排序，目录选择器路径不存在时回退到最近可用父目录 - 存放目录支持自定义并持久化，默认输出到 KMP已整理
This commit is contained in:
+250
-54
@@ -5,7 +5,10 @@ import (
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"fmt"
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"os"
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"path/filepath"
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"runtime"
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"strings"
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"sync"
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"sync/atomic"
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"kenaito-media-picker/internal/classify"
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"kenaito-media-picker/internal/digest"
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@@ -34,6 +37,10 @@ type Organizer struct {
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mover *mover.Mover
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buckets map[string][]string // 目标目录 → 文件路径
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order []string // 目标目录的创建顺序（保证输出稳定）
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seenMd5 map[string]bool // 本次扫描已入库的 MD5（同一扫描内去重）
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onProgress func(done, total int)
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pending []*store.MediaInfo // 待批量入库的媒体记录
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pendingDup []*store.MediaInfo // 待批量入库的重复文件记录
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}
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// New 创建整理器；store 可为 nil（数据库初始化失败时仅不记录信息）
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@@ -44,9 +51,69 @@ func New(pickerDir, ffprobePath string, st *store.Store) *Organizer {
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store: st,
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mover: &mover.Mover{},
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buckets: make(map[string][]string),
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seenMd5: make(map[string]bool),
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}
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}
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// SetProgress 设置进度回调（done/total 为已处理文件数与总数）
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func (o *Organizer) SetProgress(fn func(done, total int)) {
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o.onProgress = fn
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}
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// report 上报进度
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func (o *Organizer) report(done, total int) {
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if o.onProgress != nil && total > 0 {
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o.onProgress(done, total)
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}
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}
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// workerCount 并行探测的 worker 数量：不超过 CPU 核数，且限制在 1~8 之间
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func workerCount() int {
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n := runtime.NumCPU()
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if n < 1 {
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return 1
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}
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if n > 8 {
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return 8
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}
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return n
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}
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// runParallel 用固定 worker 数并行处理切片，按原顺序收集结果。
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// onProgress 在每次完成一个任务后调用（done 为已完成任务数，并发安全）。
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// 返回 results[i] 对应 items[i] 的处理结果。
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func runParallel[T any, R any](items []T, fn func(T) R, onProgress func(done int)) []R {
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results := make([]R, len(items))
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if len(items) == 0 {
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return results
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}
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workers := workerCount()
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if workers > len(items) {
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workers = len(items)
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}
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var wg sync.WaitGroup
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var doneCount int32
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jobs := make(chan int)
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for w := 0; w < workers; w++ {
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wg.Add(1)
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go func() {
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defer wg.Done()
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for i := range jobs {
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results[i] = fn(items[i])
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if onProgress != nil {
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onProgress(int(atomic.AddInt32(&doneCount, 1)))
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}
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}
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}()
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}
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for i := range items {
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jobs <- i
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}
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close(jobs)
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wg.Wait()
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return results
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}
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// add 将文件归入某个子目录
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func (o *Organizer) add(f scanner.File, subDir string) {
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dir := filepath.Join(o.pickerDir, subDir)
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@@ -86,25 +153,66 @@ func (o *Organizer) calcFileInfo(f scanner.File) (md5Str, headMd5, tailMd5 strin
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return md5Str, headMd5, tailMd5, size
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}
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// isDuplicate 判断文件是否与已入库记录重复（按 MD5）
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// isDuplicate 判断文件是否重复：
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// 1. 本次扫描已入库的 MD5 → 重复（同一扫描内去重）
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// 2. 库中已有记录且其副本在磁盘上仍存在（DestPath）→ 重复
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// 若库中副本已被移动/改名/删除，说明是同一文件被重新扫描，不算重复。
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func (o *Organizer) isDuplicate(md5Str string) bool {
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if o.store == nil || md5Str == "" {
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if md5Str == "" {
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return false
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}
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_, ok := o.store.FindMediaByMd5(md5Str)
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return ok
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if o.seenMd5[md5Str] {
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return true
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}
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if o.store == nil {
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return false
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}
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existing, ok := o.store.FindMediaByMd5(md5Str)
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if !ok {
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return false
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}
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if existing.DestPath != "" {
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if _, err := os.Stat(existing.DestPath); err == nil {
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return true
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}
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}
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return false
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}
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// record 将媒体信息写入数据库
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// markSeen 记录本次扫描已入库的 MD5（去重用）
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func (o *Organizer) markSeen(md5Str string) {
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if md5Str != "" {
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o.seenMd5[md5Str] = true
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}
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}
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// record 收集媒体信息到待入库缓冲（不立即写库，ProcessImages/ProcessMedia 结束统一批量提交）
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func (o *Organizer) record(f scanner.File, mediaType string, res *probe.ProbeResult, md5Str, headMd5, tailMd5 string, size int64) {
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if o.store == nil || md5Str == "" {
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return
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}
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o.pending = append(o.pending, buildMediaInfo(f, mediaType, res, md5Str, headMd5, tailMd5, size))
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}
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// recordDuplicate 收集重复文件信息到待入库缓冲
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func (o *Organizer) recordDuplicate(f scanner.File, mediaType string, res *probe.ProbeResult, md5Str, headMd5, tailMd5 string, size int64) {
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if o.store == nil || md5Str == "" {
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return
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}
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o.pendingDup = append(o.pendingDup, buildMediaInfo(f, mediaType, res, md5Str, headMd5, tailMd5, size))
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}
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// buildMediaInfo 构造入库记录
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func buildMediaInfo(f scanner.File, mediaType string, res *probe.ProbeResult, md5Str, headMd5, tailMd5 string, size int64) *store.MediaInfo {
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codec := res.VideoCodec
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if mediaType == "audio" {
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codec = res.AudioCodec
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}
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info := &store.MediaInfo{
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format := res.Format
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if format == "" && f.Ext != "" {
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format = strings.TrimPrefix(f.Ext, ".")
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}
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return &store.MediaInfo{
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FileMd5: md5Str,
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FilePath: f.Path,
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FileName: f.Name,
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@@ -116,69 +224,144 @@ func (o *Organizer) record(f scanner.File, mediaType string, res *probe.ProbeRes
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Height: res.Height,
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Duration: res.Duration,
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Codec: codec,
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Format: res.Format,
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Format: format,
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RawInfo: res.RawJSON,
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HeadMd5: headMd5,
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TailMd5: tailMd5,
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}
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if err := o.store.SaveMedia(info); err != nil {
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fmt.Printf("=== 保存媒体信息失败: %s, 错误: %v\n", f.Path, err)
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}
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// flushRecords 将缓冲的媒体/重复记录批量提交入库
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func (o *Organizer) flushRecords() {
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if o.store == nil {
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return
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}
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if len(o.pending) > 0 {
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if err := o.store.SaveMediaBatch(o.pending); err != nil {
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fmt.Printf("=== 批量保存媒体信息失败: %v\n", err)
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}
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o.pending = nil
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}
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if len(o.pendingDup) > 0 {
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if err := o.store.InsertDuplicateBatch(o.pendingDup); err != nil {
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fmt.Printf("=== 批量保存重复文件信息失败: %v\n", err)
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}
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o.pendingDup = nil
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}
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}
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// ProcessImages 处理全部图片：去重 → 探测尺寸并归类
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// imageProbeResult 图片探测结果（并行阶段产出，串行阶段归类）
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type imageProbeResult struct {
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psd bool // PSD 特殊归类
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unsupported bool // 非白名单且无 ffprobe 兜底，忽略
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probeErr bool // 探测失败，归入异常
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res *probe.ProbeResult
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md5Str string
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headMd5 string
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tailMd5 string
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size int64
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darkScore float64
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lightScore float64
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}
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// probeImage 并行探测一张图片：探测尺寸 + MD5 + 明暗分析（不含重复判断/归类/入库）。
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// 注意：不访问 o.seenMd5 等共享可变状态，仅读 store（指纹复用），并行安全。
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func (o *Organizer) probeImage(f scanner.File) imageProbeResult {
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r := imageProbeResult{}
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if strings.EqualFold(f.Ext, ".psd") {
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r.psd = true
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return r
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}
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if !probe.IsSupportImage(f.Ext) && o.ffprobePath == "" {
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r.unsupported = true
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return r
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}
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res, err := probe.ProbeImage(f.Path, o.ffprobePath)
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if err != nil {
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r.probeErr = true
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return r
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}
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r.res = res
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r.md5Str, r.headMd5, r.tailMd5, r.size = o.calcFileInfo(f)
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if !strings.EqualFold(f.Ext, ".gif") {
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dark, light, berr := probe.AnalyzeBrightness(f.Path)
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if berr != nil {
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fmt.Printf("=== 明暗分析失败(按中性mid归类): %s \n", f.Path)
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} else {
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r.darkScore, r.lightScore = dark, light
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}
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}
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return r
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}
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// ProcessImages 处理全部图片：并行探测（尺寸/MD5/明暗）→ 串行去重归类
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func (o *Organizer) ProcessImages(images []scanner.File) {
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success, fail, ignore, dup := 0, 0, 0, 0
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for _, f := range images {
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total := len(images)
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results := runParallel(images, o.probeImage, func(done int) {
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o.report(done, total)
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})
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for i, r := range results {
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f := images[i]
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switch {
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case strings.EqualFold(f.Ext, ".psd"):
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case r.psd:
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o.add(f, dirImagePSD)
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success++
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continue
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case !probe.IsSupportImage(f.Ext) && o.ffprobePath == "":
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// 非白名单扩展名且无 ffprobe 兜底时直接忽略
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case r.unsupported:
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o.add(f, dirImageIgnored)
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ignore++
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continue
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}
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res, err := probe.ProbeImage(f.Path, o.ffprobePath)
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if err != nil {
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case r.probeErr:
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o.add(f, dirImageErr)
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fail++
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fmt.Printf("=== 异常图片: %s \n", f.Path)
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continue
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}
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md5Str, headMd5, tailMd5, size := o.calcFileInfo(f)
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if o.isDuplicate(md5Str) {
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case o.isDuplicate(r.md5Str):
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o.recordDuplicate(f, "image", r.res, r.md5Str, r.headMd5, r.tailMd5, r.size)
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o.add(f, dirDuplicate)
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dup++
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fmt.Printf("=== 重复图片: %s \n", f.Path)
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continue
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default:
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o.record(f, "image", r.res, r.md5Str, r.headMd5, r.tailMd5, r.size)
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o.markSeen(r.md5Str)
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o.add(f, classify.ImageDir(f.Ext, r.res.Width, r.res.Height, r.darkScore, r.lightScore))
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success++
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}
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o.record(f, "image", res, md5Str, headMd5, tailMd5, size)
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darkScore, lightScore := 0.0, 0.0
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if !strings.EqualFold(f.Ext, ".gif") {
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dark, light, berr := probe.AnalyzeBrightness(f.Path)
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if berr != nil {
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fmt.Printf("=== 明暗分析失败(按中性mid归类): %s \n", f.Path)
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} else {
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darkScore, lightScore = dark, light
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}
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}
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o.add(f, classify.ImageDir(f.Ext, res.Width, res.Height, darkScore, lightScore))
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success++
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}
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fmt.Printf("=== 图片处理完毕，成功: %d, 读取异常: %d, 忽略: %d, 重复: %d \n\n", success, fail, ignore, dup)
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}
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// ProcessMedia 处理媒体候选：去重 → ffprobe 判定视频/音频/不支持
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// mediaProbeResult 媒体探测结果（并行阶段产出，串行阶段归类）
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type mediaProbeResult struct {
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res *probe.ProbeResult
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err error
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md5 string
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head string
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tail string
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size int64
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}
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// probeMedia 并行探测一个媒体文件（ffprobe + MD5）。不访问共享可变状态。
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func (o *Organizer) probeMedia(f scanner.File) mediaProbeResult {
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res, err := probe.ProbeMediaFile(o.ffprobePath, f.Path)
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if err != nil {
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return mediaProbeResult{err: err}
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}
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if !res.HasVideo && !res.HasAudio {
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return mediaProbeResult{res: res}
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}
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md5, head, tail, size := o.calcFileInfo(f)
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return mediaProbeResult{res: res, md5: md5, head: head, tail: tail, size: size}
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}
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// ProcessMedia 处理媒体候选：并行 ffprobe 判定 → 串行去重归类
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func (o *Organizer) ProcessMedia(media []scanner.File) {
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video, audio, fail, ignore, dup := 0, 0, 0, 0, 0
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for _, f := range media {
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res, err := probe.ProbeMediaFile(o.ffprobePath, f.Path)
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if err != nil {
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total := len(media)
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results := runParallel(media, o.probeMedia, func(done int) {
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o.report(done, total)
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})
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for i, r := range results {
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f := media[i]
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if r.err != nil {
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// 仅 MIME 明确为视频/音频的文件才移入异常/忽略目录；
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// octet-stream/空 MIME 且 ffprobe 无法确认的原地忽略，不移动
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if strings.HasPrefix(f.Mime, "video/") {
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@@ -195,27 +378,29 @@ func (o *Organizer) ProcessMedia(media []scanner.File) {
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continue
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}
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switch {
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case res.HasVideo:
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md5Str, headMd5, tailMd5, size := o.calcFileInfo(f)
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if o.isDuplicate(md5Str) {
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case r.res.HasVideo:
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if o.isDuplicate(r.md5) {
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o.recordDuplicate(f, "video", r.res, r.md5, r.head, r.tail, r.size)
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dup++
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o.add(f, dirDuplicate)
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fmt.Printf("=== 重复媒体: %s \n", f.Path)
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continue
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}
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video++
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o.record(f, "video", res, md5Str, headMd5, tailMd5, size)
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o.add(f, classify.VideoDir(f.Ext, res.Width, res.Height))
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case res.HasAudio:
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md5Str, headMd5, tailMd5, size := o.calcFileInfo(f)
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if o.isDuplicate(md5Str) {
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o.record(f, "video", r.res, r.md5, r.head, r.tail, r.size)
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o.markSeen(r.md5)
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o.add(f, classify.VideoDir(f.Ext, r.res.Width, r.res.Height))
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case r.res.HasAudio:
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if o.isDuplicate(r.md5) {
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o.recordDuplicate(f, "audio", r.res, r.md5, r.head, r.tail, r.size)
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dup++
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o.add(f, dirDuplicate)
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fmt.Printf("=== 重复媒体: %s \n", f.Path)
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continue
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}
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audio++
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o.record(f, "audio", res, md5Str, headMd5, tailMd5, size)
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o.record(f, "audio", r.res, r.md5, r.head, r.tail, r.size)
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o.markSeen(r.md5)
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o.add(f, dirAudio)
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default:
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// ffprobe 无音视频流：MIME 明确为媒体的归入忽略目录，其余原地不动
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@@ -231,12 +416,23 @@ func (o *Organizer) ProcessMedia(media []scanner.File) {
|
||||
fmt.Printf("=== 媒体处理完毕，视频: %d, 音频: %d, 读取异常: %d, 忽略: %d, 重复: %d \n\n", video, audio, fail, ignore, dup)
|
||||
}
|
||||
|
||||
// Flush 将所有收集到的文件移动到对应目录，并回填归类去向
|
||||
// Flush 先将缓冲的媒体记录批量入库，再将收集到的文件移动到对应目录并回填归类去向。
|
||||
// 移动期间按累计完成数上报进度。
|
||||
func (o *Organizer) Flush() {
|
||||
o.flushRecords()
|
||||
total := 0
|
||||
for _, dir := range o.order {
|
||||
moved := o.mover.MoveToDir(o.buckets[dir], dir)
|
||||
total += len(o.buckets[dir])
|
||||
}
|
||||
movedAll := 0
|
||||
for _, dir := range o.order {
|
||||
onProgress := func(done int) {
|
||||
o.report(movedAll+done, total)
|
||||
}
|
||||
moved := o.mover.MoveToDir(o.buckets[dir], dir, onProgress)
|
||||
movedAll += len(o.buckets[dir])
|
||||
for src, dest := range moved {
|
||||
if err := o.store.UpdateMediaDest(src, dest); err != nil {
|
||||
if err := o.store.UpdateMediaDest(src, dir, dest); err != nil {
|
||||
fmt.Printf("=== 更新媒体去向失败: %s, 错误: %v\n", src, err)
|
||||
}
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user