代码初始化
This commit is contained in:
657
service/scene/scene_service.go
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657
service/scene/scene_service.go
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@@ -0,0 +1,657 @@
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package scene
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import (
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"bufio"
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"context"
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"fmt"
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"math"
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"os"
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"os/exec"
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"path/filepath"
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"regexp"
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"strconv"
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"strings"
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"sync"
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"github.com/gogf/gf/v2/frame/g"
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)
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// SceneAnalyzerService 场景分析服务
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type SceneAnalyzerService struct{}
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// SceneAnalyzer 场景分析服务单例
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var SceneAnalyzer = new(SceneAnalyzerService)
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// KeyframeInfo 关键帧信息
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type KeyframeInfo struct {
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Path string `json:"path"` // 关键帧图片路径
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TimeStr string `json:"timeStr"` // 时间点
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Width int `json:"width"` // 图片宽度
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Height int `json:"height"` // 图片高度
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}
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// SceneInfo 单个场景信息
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type SceneInfo struct {
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SceneIndex int `json:"sceneIndex"` // 场景序号
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StartTime float64 `json:"startTime"` // 开始时间（秒，精确到3位小数）
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EndTime float64 `json:"endTime"` // 结束时间（秒）
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Duration float64 `json:"duration"` // 时长（秒）
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StartTimeStr string `json:"startTimeStr"` // HH:MM:SS.mmm
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EndTimeStr string `json:"endTimeStr"`
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DurationStr string `json:"durationStr"`
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ShotType string `json:"shotType"` // 镜头类型
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MotionLevel string `json:"motionLevel"` // 运动程度
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Composition string `json:"composition"` // 构图类型
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NarrativePos string `json:"narrativePos"` // 叙事位置
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Keyframe *KeyframeInfo `json:"keyframe,omitempty"` // 关键帧（如有提取）
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Description string `json:"description"` // 场景描述（供 AI 使用）
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}
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// VideoSceneAnalysis 单视频场景分析结果
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type VideoSceneAnalysis struct {
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FileName string `json:"fileName"`
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FilePath string `json:"filePath"`
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Duration float64 `json:"duration"`
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DurationStr string `json:"durationStr"`
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FrameRate float64 `json:"frameRate"`
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Width int `json:"width"`
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Height int `json:"height"`
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AspectRatio string `json:"aspectRatio"` // 画面比例
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Orientation string `json:"orientation"` // 横屏/竖屏
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TotalScenes int `json:"totalScenes"`
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Scenes []SceneInfo `json:"scenes"`
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DetectParams DetectParams `json:"detectParams"`
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Summary SceneSummary `json:"summary"` // 场景总览
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}
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// SceneSummary 场景总览
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type SceneSummary struct {
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AvgShotDuration float64 `json:"avgShotDuration"` // 平均镜头时长
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MinShotDuration float64 `json:"minShotDuration"`
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MaxShotDuration float64 `json:"maxShotDuration"`
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ShotTypeDist map[string]int `json:"shotTypeDist"` // 镜头类型分布
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MotionDist map[string]int `json:"motionDist"` // 运动程度分布
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CompositionDist map[string]int `json:"compositionDist"` // 构图分布
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Pacing string `json:"pacing"` // 剪辑节奏
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KeyframesDir string `json:"keyframesDir,omitempty"` // 关键帧目录
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}
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// DetectParams 检测参数
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type DetectParams struct {
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Threshold float64 `json:"threshold"`
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Method string `json:"method"`
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ExtractKeyframes bool `json:"extractKeyframes"`
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}
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// SceneAnalyzeReq 场景分析请求
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type SceneAnalyzeReq struct {
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VideoPaths []string // 视频文件路径列表
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Threshold float64 // 场景检测阈值 0.1-0.5，默认 0.3
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ExtractKeyframes bool // 是否提取关键帧图片
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}
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// SceneAnalyzeRes 场景分析响应
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type SceneAnalyzeRes struct {
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Analyses []VideoSceneAnalysis `json:"analyses"`
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}
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var (
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ptsTimeRegex = regexp.MustCompile(`pts_time:([\d.]+)`)
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)
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// Analyze 分析多个视频的场景
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func (s *SceneAnalyzerService) Analyze(ctx context.Context, req *SceneAnalyzeReq) (res *SceneAnalyzeRes, err error) {
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threshold := req.Threshold
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if threshold <= 0 || threshold > 1 {
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threshold = 0.3
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}
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var (
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mu sync.Mutex
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analyses []VideoSceneAnalysis
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wg sync.WaitGroup
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errCh = make(chan error, len(req.VideoPaths))
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)
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for _, videoPath := range req.VideoPaths {
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wg.Add(1)
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go func(vp string) {
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defer wg.Done()
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analysis, aErr := s.analyzeSingle(ctx, vp, threshold, req.ExtractKeyframes)
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if aErr != nil {
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errCh <- fmt.Errorf("分析失败 [%s]: %v", filepath.Base(vp), aErr)
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return
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}
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mu.Lock()
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analyses = append(analyses, *analysis)
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mu.Unlock()
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}(videoPath)
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}
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wg.Wait()
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close(errCh)
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var errs []string
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for e := range errCh {
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errs = append(errs, e.Error())
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}
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if len(errs) > 0 {
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g.Log().Errorf(ctx, "部分视频分析失败: %s", strings.Join(errs, "; "))
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}
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if len(analyses) == 0 {
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return nil, fmt.Errorf("所有视频分析均失败: %s", strings.Join(errs, "; "))
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}
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res = &SceneAnalyzeRes{Analyses: analyses}
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return
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}
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// analyzeSingle 分析单个视频
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func (s *SceneAnalyzerService) analyzeSingle(ctx context.Context, videoPath string, threshold float64, extractKeyframes bool) (*VideoSceneAnalysis, error) {
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ffmpegPath, err := s.getFFmpegPath()
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if err != nil {
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return nil, err
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}
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// 1. 视频元数据
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duration, frameRate, width, height, err := s.getVideoMeta(ctx, ffmpegPath, videoPath)
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if err != nil {
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return nil, fmt.Errorf("获取视频元数据失败: %v", err)
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}
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// 2. 场景检测
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sceneChanges, err := s.detectScenes(ctx, ffmpegPath, videoPath, threshold)
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if err != nil {
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return nil, fmt.Errorf("场景检测失败: %v", err)
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}
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// 3. 构建场景列表 + 分析
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rawScenes := s.buildScenes(sceneChanges, duration)
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totalDuration := duration
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// 4. 提取关键帧（如果需要）
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keyframesDir := ""
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if extractKeyframes {
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keyframesDir = filepath.Join(filepath.Dir(videoPath), "keyframes_"+filepath.Base(videoPath))
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os.MkdirAll(keyframesDir, 0755)
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}
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// 构建带分析信息的场景
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aspectRatio := fmt.Sprintf("%d:%d", width/gcd(width, height), height/gcd(width, height))
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orientation := "横屏"
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if height > width {
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orientation = "竖屏"
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}
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fileName := filepath.Base(videoPath)
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if idx := strings.Index(fileName, "_"); idx > 0 {
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fileName = fileName[idx+1:]
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}
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// 生成场景分析
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totalScenes := len(rawScenes)
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scenes := make([]SceneInfo, totalScenes)
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shotDist := make(map[string]int)
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motionDist := make(map[string]int)
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compDist := make(map[string]int)
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var durTotal float64
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for i, rs := range rawScenes {
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scene := SceneInfo{
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SceneIndex: rs.SceneIndex,
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StartTime: round3(rs.StartTime),
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EndTime: round3(rs.EndTime),
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Duration: round3(rs.Duration),
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StartTimeStr: rs.StartTimeStr,
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EndTimeStr: rs.EndTimeStr,
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DurationStr: rs.DurationStr,
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}
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// 镜头类型
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scene.ShotType = classifyShotType(rs.Duration)
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shotDist[scene.ShotType]++
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// 运动程度
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scene.MotionLevel = classifyMotionLevel(rs.Duration, totalDuration)
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motionDist[scene.MotionLevel]++
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// 构图
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scene.Composition = classifyComposition(rs.Duration, width, height)
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compDist[scene.Composition]++
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// 叙事位置
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ratio := rs.StartTime / totalDuration
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switch {
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case ratio < 0.15:
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scene.NarrativePos = "开头引入"
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case ratio < 0.35:
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scene.NarrativePos = "前段发展"
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case ratio < 0.65:
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scene.NarrativePos = "中段高潮"
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case ratio < 0.85:
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scene.NarrativePos = "后段收束"
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default:
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scene.NarrativePos = "结尾总结"
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}
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// 关键帧
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if extractKeyframes && keyframesDir != "" {
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midTime := (rs.StartTime + rs.EndTime) / 2
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kfPath := filepath.Join(keyframesDir, fmt.Sprintf("scene_%03d.jpg", rs.SceneIndex))
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if kfErr := s.extractKeyframe(ctx, ffmpegPath, videoPath, midTime, kfPath); kfErr == nil {
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scene.Keyframe = &KeyframeInfo{
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Path: kfPath,
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TimeStr: formatTime(midTime),
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Width: width,
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Height: height,
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}
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}
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}
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// AI 描述
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scene.Description = buildSceneDescription(scene)
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durTotal += rs.Duration
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scenes[i] = scene
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}
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analysis := &VideoSceneAnalysis{
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FileName: fileName,
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FilePath: videoPath,
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Duration: round3(totalDuration),
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DurationStr: formatTime(totalDuration),
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FrameRate: round3(frameRate),
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Width: width,
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Height: height,
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AspectRatio: aspectRatio,
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Orientation: orientation,
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TotalScenes: totalScenes,
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Scenes: scenes,
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DetectParams: DetectParams{
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Threshold: threshold,
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Method: "ffmpeg scene filter",
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ExtractKeyframes: extractKeyframes,
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},
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Summary: s.buildSummary(scenes, shotDist, motionDist, compDist, keyframesDir),
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}
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return analysis, nil
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}
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// buildSummary 构建场景总览
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func (s *SceneAnalyzerService) buildSummary(scenes []SceneInfo, shotDist, motionDist, compDist map[string]int, kfDir string) SceneSummary {
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if len(scenes) == 0 {
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return SceneSummary{}
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}
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var minD, maxD, sumD float64
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minD = math.MaxFloat64
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for _, sc := range scenes {
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sumD += sc.Duration
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if sc.Duration < minD {
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minD = sc.Duration
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}
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if sc.Duration > maxD {
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maxD = sc.Duration
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}
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}
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avgD := sumD / float64(len(scenes))
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pacing := "平稳"
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if avgD < 2 {
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pacing = "快节奏（快速剪辑）"
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} else if avgD < 4 {
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pacing = "适中节奏"
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} else if avgD < 8 {
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pacing = "舒缓节奏"
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} else {
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pacing = "慢节奏（长镜头为主）"
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}
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sm := SceneSummary{
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AvgShotDuration: round3(avgD),
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MinShotDuration: round3(minD),
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MaxShotDuration: round3(maxD),
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ShotTypeDist: shotDist,
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MotionDist: motionDist,
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CompositionDist: compDist,
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Pacing: pacing,
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}
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if kfDir != "" {
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sm.KeyframesDir = kfDir
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}
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return sm
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}
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// getVideoMeta 获取视频元数据
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func (s *SceneAnalyzerService) getVideoMeta(ctx context.Context, ffmpegPath, videoPath string) (duration, frameRate float64, width, height int, err error) {
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ffprobePath := filepath.Join(filepath.Dir(ffmpegPath), "ffprobe")
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if _, statErr := os.Stat(ffprobePath); os.IsNotExist(statErr) {
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ffprobePath = "ffprobe"
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}
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cmd := exec.CommandContext(ctx, ffprobePath,
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"-v", "quiet",
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"-print_format", "json",
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"-show_format",
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"-show_streams",
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videoPath,
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)
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output, execErr := cmd.Output()
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if execErr != nil {
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err = fmt.Errorf("ffprobe 执行失败: %v", execErr)
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return
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}
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text := string(output)
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duration = parseJSONFloat(text, `"duration":`)
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frameRate = parseFrameRate(text)
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width = parseJSONInt(text, `"width":`)
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height = parseJSONInt(text, `"height":`)
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return
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}
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// detectScenes 通过 ffmpeg scene filter 检测场景变化
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func (s *SceneAnalyzerService) detectScenes(ctx context.Context, ffmpegPath, videoPath string, threshold float64) ([]float64, error) {
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thresholdStr := strconv.FormatFloat(threshold, 'f', 1, 64)
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args := []string{
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"-i", videoPath,
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"-filter:v", fmt.Sprintf("select='gt(scene,%s)',showinfo", thresholdStr),
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"-f", "null",
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"-",
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}
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cmd := exec.CommandContext(ctx, ffmpegPath, args...)
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output, _ := cmd.CombinedOutput()
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var timestamps []float64
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scanner := bufio.NewScanner(strings.NewReader(string(output)))
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for scanner.Scan() {
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line := scanner.Text()
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matches := ptsTimeRegex.FindStringSubmatch(line)
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if len(matches) >= 2 {
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ts, parseErr := strconv.ParseFloat(matches[1], 64)
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if parseErr == nil && ts > 0 {
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timestamps = append(timestamps, ts)
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}
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}
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}
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return timestamps, nil
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}
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// extractKeyframe 提取指定时间点的关键帧
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func (s *SceneAnalyzerService) extractKeyframe(ctx context.Context, ffmpegPath, videoPath string, timeSec float64, outputPath string) error {
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timeStr := strconv.FormatFloat(timeSec, 'f', 3, 64)
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args := []string{
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"-ss", timeStr,
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"-i", videoPath,
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"-vframes", "1",
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"-q:v", "3",
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"-y",
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outputPath,
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}
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cmd := exec.CommandContext(ctx, ffmpegPath, args...)
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return cmd.Run()
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}
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// buildScenes 根据场景变化时间戳构建场景列表
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func (s *SceneAnalyzerService) buildScenes(sceneChanges []float64, totalDuration float64) []SceneInfo {
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var scenes []SceneInfo
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if len(sceneChanges) == 0 {
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scenes = append(scenes, SceneInfo{
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SceneIndex: 1,
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StartTime: 0,
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EndTime: totalDuration,
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Duration: totalDuration,
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StartTimeStr: formatTime(0),
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EndTimeStr: formatTime(totalDuration),
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DurationStr: formatTime(totalDuration),
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})
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return scenes
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}
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startTime := 0.0
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for i, ts := range sceneChanges {
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if ts <= startTime || ts > totalDuration {
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continue
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}
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scenes = append(scenes, SceneInfo{
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SceneIndex: i + 1,
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StartTime: startTime,
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EndTime: ts,
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Duration: ts - startTime,
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StartTimeStr: formatTime(startTime),
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EndTimeStr: formatTime(ts),
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DurationStr: formatTime(ts - startTime),
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})
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startTime = ts
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}
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if startTime < totalDuration {
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scenes = append(scenes, SceneInfo{
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SceneIndex: len(scenes) + 1,
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StartTime: startTime,
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EndTime: totalDuration,
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Duration: totalDuration - startTime,
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StartTimeStr: formatTime(startTime),
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EndTimeStr: formatTime(totalDuration),
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DurationStr: formatTime(totalDuration - startTime),
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})
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}
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return scenes
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}
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// ---------- 镜头分类逻辑 ----------
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// classifyShotType 根据时长判断镜头类型
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func classifyShotType(duration float64) string {
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switch {
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case duration < 0.8:
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return "极速闪切"
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case duration < 1.5:
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return "快速切换"
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case duration < 2.5:
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return "短镜头"
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case duration < 4:
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return "标准镜头"
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case duration < 8:
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return "中长镜头"
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case duration < 15:
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return "长镜头"
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default:
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return "超长镜头"
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}
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}
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// classifyMotionLevel 基于时长和相对比例推断运动程度
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func classifyMotionLevel(duration, totalDuration float64) string {
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switch {
|
||||
case duration < 1.0:
|
||||
return "高动态（快速切换）"
|
||||
case duration < 2.0:
|
||||
return "中高动态"
|
||||
case duration < 4.0:
|
||||
return "中等动态"
|
||||
case duration < 8.0:
|
||||
return "低动态（平稳）"
|
||||
default:
|
||||
return "静态/固定机位"
|
||||
}
|
||||
}
|
||||
|
||||
// classifyComposition 基于时长和画面比例推断构图类型
|
||||
func classifyComposition(duration float64, width, height int) string {
|
||||
isVertical := height > width
|
||||
|
||||
switch {
|
||||
case duration < 1.2:
|
||||
if isVertical {
|
||||
return "竖屏特写/细节"
|
||||
}
|
||||
return "特写/细节"
|
||||
case duration < 2.5:
|
||||
if isVertical {
|
||||
return "竖屏近景"
|
||||
}
|
||||
return "近景/中近景"
|
||||
case duration < 5:
|
||||
if isVertical {
|
||||
return "竖屏中景"
|
||||
}
|
||||
return "中景/半身"
|
||||
case duration < 10:
|
||||
if isVertical {
|
||||
return "竖屏全景"
|
||||
}
|
||||
return "全景/环境"
|
||||
default:
|
||||
if isVertical {
|
||||
return "竖屏远景/固定机位"
|
||||
}
|
||||
return "远景/广角"
|
||||
}
|
||||
}
|
||||
|
||||
// buildSceneDescription 生成可读的场景描述（供 AI 使用）
|
||||
func buildSceneDescription(scene SceneInfo) string {
|
||||
return fmt.Sprintf(
|
||||
"场景%d：%s～%s，时长%s，%s，%s，%s，%s",
|
||||
scene.SceneIndex,
|
||||
scene.StartTimeStr, scene.EndTimeStr,
|
||||
scene.DurationStr,
|
||||
scene.ShotType,
|
||||
scene.Composition,
|
||||
scene.MotionLevel,
|
||||
scene.NarrativePos,
|
||||
)
|
||||
}
|
||||
|
||||
// ---------- 工具函数 ----------
|
||||
|
||||
func round3(v float64) float64 {
|
||||
return math.Round(v*1000) / 1000
|
||||
}
|
||||
|
||||
func gcd(a, b int) int {
|
||||
for b != 0 {
|
||||
a, b = b, a%b
|
||||
}
|
||||
return a
|
||||
}
|
||||
|
||||
func getFFmpegPath() (string, error) {
|
||||
ffmpegPath := g.Cfg().MustGet(context.Background(), "ffmpeg.path", "").String()
|
||||
if ffmpegPath != "" {
|
||||
if _, err := os.Stat(ffmpegPath); err == nil {
|
||||
return ffmpegPath, nil
|
||||
}
|
||||
}
|
||||
path, err := exec.LookPath("ffmpeg")
|
||||
if err != nil {
|
||||
return "", fmt.Errorf("未找到 ffmpeg")
|
||||
}
|
||||
return path, nil
|
||||
}
|
||||
|
||||
func formatTime(seconds float64) string {
|
||||
h := int(seconds) / 3600
|
||||
m := (int(seconds) % 3600) / 60
|
||||
s := int(seconds) % 60
|
||||
ms := int(math.Round((seconds - float64(int(seconds))) * 1000))
|
||||
return fmt.Sprintf("%02d:%02d:%02d.%03d", h, m, s, ms)
|
||||
}
|
||||
|
||||
func parseJSONFloat(text, key string) float64 {
|
||||
idx := strings.Index(text, key)
|
||||
if idx < 0 {
|
||||
return 0
|
||||
}
|
||||
start := idx + len(key)
|
||||
for start < len(text) && (text[start] == ' ' || text[start] == '"') {
|
||||
start++
|
||||
}
|
||||
end := start
|
||||
for end < len(text) && (isDigit(text[end]) || text[end] == '.') {
|
||||
end++
|
||||
}
|
||||
if start < end {
|
||||
val, _ := strconv.ParseFloat(text[start:end], 64)
|
||||
return val
|
||||
}
|
||||
return 0
|
||||
}
|
||||
|
||||
func parseJSONInt(text, key string) int {
|
||||
idx := strings.Index(text, key)
|
||||
if idx < 0 {
|
||||
return 0
|
||||
}
|
||||
start := idx + len(key)
|
||||
for start < len(text) && (text[start] == ' ' || text[start] == '"') {
|
||||
start++
|
||||
}
|
||||
end := start
|
||||
for end < len(text) && isDigit(text[end]) {
|
||||
end++
|
||||
}
|
||||
if start < end {
|
||||
val, _ := strconv.Atoi(text[start:end])
|
||||
return val
|
||||
}
|
||||
return 0
|
||||
}
|
||||
|
||||
func parseFrameRate(text string) float64 {
|
||||
for _, key := range []string{`"r_frame_rate":`, `"avg_frame_rate":`} {
|
||||
idx := strings.Index(text, key)
|
||||
if idx < 0 {
|
||||
continue
|
||||
}
|
||||
start := idx + len(key)
|
||||
for start < len(text) && (text[start] == ' ' || text[start] == '"') {
|
||||
start++
|
||||
}
|
||||
end := start
|
||||
for end < len(text) && text[end] != '"' && text[end] != ',' && text[end] != '}' && text[end] != ' ' {
|
||||
end++
|
||||
}
|
||||
valStr := text[start:end]
|
||||
if strings.Contains(valStr, "/") {
|
||||
parts := strings.Split(valStr, "/")
|
||||
if len(parts) == 2 {
|
||||
num, _ := strconv.ParseFloat(parts[0], 64)
|
||||
den, _ := strconv.ParseFloat(parts[1], 64)
|
||||
if den > 0 {
|
||||
return num / den
|
||||
}
|
||||
}
|
||||
}
|
||||
val, _ := strconv.ParseFloat(valStr, 64)
|
||||
if val > 0 {
|
||||
return val
|
||||
}
|
||||
}
|
||||
return 0
|
||||
}
|
||||
|
||||
func isDigit(b byte) bool {
|
||||
return b >= '0' && b <= '9'
|
||||
}
|
||||
|
||||
// Cleanup 清理视频和关键帧文件
|
||||
func Cleanup(paths []string) {
|
||||
for _, p := range paths {
|
||||
os.RemoveAll(p)
|
||||
}
|
||||
}
|
||||
|
||||
// getFFmpegPath on SceneAnalyzerService
|
||||
func (s *SceneAnalyzerService) getFFmpegPath() (string, error) {
|
||||
return getFFmpegPath()
|
||||
}
|
||||
Reference in New Issue
Block a user