bugfixes

backend/analyze.go

@@ -65,8 +65,8 @@ const (
 	// Sprite-Modus ist aktuell deaktiviert. Analyse läuft über Video-Frames.
 	analyzeMaxSpriteCandidates = 24
 
-	// Video-Modus: schnelle Vorschau. Für bessere Trefferquote später 24.
+	// Video-Modus: extrahiert 1 Frame alle N Sekunden.
-	// neu, falls du später alle N Sekunden willst
+	// 1 = jeder Sekunde, 3 = alle 3 Sekunden, 5 = alle 5 Sekunden.
 	analyzeVideoFrameIntervalSeconds = 3
 
 	// AI-Server nicht mit tausenden Pfaden auf einmal fluten.
@@ -668,12 +668,18 @@ func trainingPredictFramePathsBatchForAnalyze(
 
 	res, err := client.Do(req)
 	if err != nil {
+		if ctxErr := ctx.Err(); ctxErr != nil {
+			return nil, ctxErr
+		}
 		return nil, err
 	}
 	defer res.Body.Close()
 
 	var parsed analyzeBatchPredictResp
 	if err := json.NewDecoder(res.Body).Decode(&parsed); err != nil {
+		if ctxErr := ctx.Err(); ctxErr != nil {
+			return nil, ctxErr
+		}
 		return nil, err
 	}
 
@@ -1785,15 +1791,23 @@ func analyzeVideoFromFramesForGoal(
 		"Analyse 0%",
 	)
 
+	if err := ctx.Err(); err != nil {
+		publishAnalysisError(startedAtMs, file, "Analyse abgebrochen", err)
+		return nil, nil, err
+	}
+
 	durationSec, _ := durationSecondsForAnalyze(ctx, outPath)
+	if err := ctx.Err(); err != nil {
+		publishAnalysisError(startedAtMs, file, "Analyse abgebrochen", err)
+		return nil, nil, err
+	}
+
 	if durationSec <= 0 {
 		err := appErrorf("videolänge konnte nicht bestimmt werden")
 		publishAnalysisError(startedAtMs, file, "Analyse fehlgeschlagen", err)
 		return nil, nil, err
 	}
 
-	// Hilfsfunktion: garantiert, dass keine Prozentpunkte übersprungen werden.
-	// Beispiel: letzter Stand 12, neuer Stand 17 -> sendet 13,14,15,16,17.
 	publishPercentRange := func(lastPercent *int, nextPercent int, current int, total int, extractPhase bool) {
 		if total <= 0 {
 			total = 1
@@ -1814,7 +1828,6 @@ func analyzeVideoFromFramesForGoal(
 			label := fmt.Sprintf("Analyse %d%%", p)
 
 			if extractPhase {
-				// p läuft global 0..50, publishAnalyzeExtractProgress erwartet aber 0..1.
 				ratio := float64(p) / 50.0
 				if ratio < 0 {
 					ratio = 0
@@ -1830,9 +1843,6 @@ func analyzeVideoFromFramesForGoal(
 					label,
 				)
 			} else {
-				// Für die Inferenzphase current/total so wählen, dass der globale
-				// Fortschritt in publishAnalyzeInferenceProgress wieder exakt p ergibt:
-				// current/total = (p - 50) / 50
 				inferenceCurrent := current
 				inferenceTotal := total
 
@@ -1854,6 +1864,16 @@ func analyzeVideoFromFramesForGoal(
 		*lastPercent = nextPercent
 	}
 
+	failCancelled := func() ([]analyzeHit, []analyzeHit, error) {
+		err := ctx.Err()
+		if err == nil {
+			err = context.Canceled
+		}
+
+		publishAnalysisError(startedAtMs, file, "Analyse abgebrochen", err)
+		return nil, nil, err
+	}
+
 	lastExtractPercent := 0
 
 	samples, cleanup, err := extractVideoFramesBatch(
@@ -1887,6 +1907,14 @@ func analyzeVideoFromFramesForGoal(
 		},
 	)
 
+	if cleanup != nil {
+		defer cleanup()
+	}
+
+	if ctx.Err() != nil {
+		return failCancelled()
+	}
+
 	if err != nil {
 		publishAnalysisError(startedAtMs, file, "Frames konnten nicht extrahiert werden", err)
 		return nil, nil, err
@@ -1910,8 +1938,16 @@ func analyzeVideoFromFramesForGoal(
 		)
 	}
 
+	if ctx.Err() != nil {
+		return failCancelled()
+	}
+
 	paths := make([]string, 0, len(samples))
 	for _, sample := range samples {
+		if err := ctx.Err(); err != nil {
+			return failCancelled()
+		}
+
 		paths = append(paths, sample.Path)
 	}
 
@@ -1925,6 +1961,10 @@ func analyzeVideoFromFramesForGoal(
 		"Analyse 50%",
 	)
 
+	if ctx.Err() != nil {
+		return failCancelled()
+	}
+
 	// Schneller AI-Server-Batch-Pfad für nsfw, highlights und all.
 	// Wichtig: ensureAnalyzeAllGoalsForVideoCtx ruft goal="all" auf.
 	// Ohne diesen Block fällt "all" auf die sehr langsame Einzelbild-Analyse zurück.
@@ -1937,6 +1977,10 @@ func analyzeVideoFromFramesForGoal(
 		detectorOnly := false
 
 		for startIdx := 0; startIdx < len(samples); startIdx += analyzeFramePredictBatchSize {
+			if ctx.Err() != nil {
+				return failCancelled()
+			}
+
 			endIdx := startIdx + analyzeFramePredictBatchSize
 			if endIdx > len(samples) {
 				endIdx = len(samples)
@@ -1948,6 +1992,10 @@ func analyzeVideoFromFramesForGoal(
 				detectorOnly,
 			)
 
+			if ctx.Err() != nil {
+				return failCancelled()
+			}
+
 			if batchErr != nil || len(predictions) < endIdx-startIdx {
 				appLogln("⚠️ video batch analyse fehlgeschlagen, fallback auf einzelbild-analyse:", batchErr)
 
@@ -1968,6 +2016,10 @@ func analyzeVideoFromFramesForGoal(
 			}
 
 			for i := 0; i < endIdx-startIdx; i++ {
+				if ctx.Err() != nil {
+					return failCancelled()
+				}
+
 				sample := samples[startIdx+i]
 				pred := predictions[i]
 
@@ -1999,6 +2051,10 @@ func analyzeVideoFromFramesForGoal(
 		}
 
 		if batchOK {
+			if ctx.Err() != nil {
+				return failCancelled()
+			}
+
 			if lastInferencePercent < 100 {
 				publishPercentRange(
 					&lastInferencePercent,
@@ -2012,8 +2068,6 @@ func analyzeVideoFromFramesForGoal(
 			cleanNSFWHits := mergeAnalyzeHits(nsfwHits)
 			cleanHighlightHits := mergeAnalyzeHits(highlightHits)
 
-			cleanup()
-
 			publishAnalysisFinished(startedAtMs, total, file, "Analyse abgeschlossen")
 			return cleanNSFWHits, cleanHighlightHits, nil
 		}
@@ -2022,12 +2076,21 @@ func analyzeVideoFromFramesForGoal(
 	// Fallback: langsame Einzelbild-Analyse.
 	// Dieser Pfad sollte nur laufen, wenn der AI-Server-Batch fehlschlägt.
 	for i, sample := range samples {
+		if ctx.Err() != nil {
+			return failCancelled()
+		}
+
 		t := sample.Time
 
 		switch goal {
 		case "nsfw":
-			res, err := classifyFramePathForAnalyze(ctx, sample.Path)
+			res, frameErr := classifyFramePathForAnalyze(ctx, sample.Path)
-			if err == nil {
+
+			if ctx.Err() != nil {
+				return failCancelled()
+			}
+
+			if frameErr == nil {
 				bestLabel, bestScore := pickBestNSFWResult(res.Results)
 				if bestLabel != "" && bestScore >= nsfwThresholdForLabel(bestLabel) {
 					nsfwHits = append(nsfwHits, analyzeHit{
@@ -2042,10 +2105,20 @@ func analyzeVideoFromFramesForGoal(
 
 		case "highlights":
 			pred := predictFramePathForAnalyze(ctx, sample.Path)
+
+			if ctx.Err() != nil {
+				return failCancelled()
+			}
+
 			highlightHits = appendHighlightHitsFromPrediction(highlightHits, pred, t)
 
 		default:
 			pred := predictFramePathForAnalyze(ctx, sample.Path)
+
+			if ctx.Err() != nil {
+				return failCancelled()
+			}
+
 			nsfwHits = appendNSFWHitFromPrediction(nsfwHits, pred, t)
 			highlightHits = appendHighlightHitsFromPrediction(highlightHits, pred, t)
 		}
@@ -2066,6 +2139,10 @@ func analyzeVideoFromFramesForGoal(
 		)
 	}
 
+	if ctx.Err() != nil {
+		return failCancelled()
+	}
+
 	if lastInferencePercent < 100 {
 		publishPercentRange(
 			&lastInferencePercent,
@@ -2079,8 +2156,6 @@ func analyzeVideoFromFramesForGoal(
 	cleanNSFWHits := mergeAnalyzeHits(nsfwHits)
 	cleanHighlightHits := mergeAnalyzeHits(highlightHits)
 
-	cleanup()
-
 	publishAnalysisFinished(startedAtMs, total, file, "Analyse abgeschlossen")
 
 	return cleanNSFWHits, cleanHighlightHits, nil

backend/tasks_regenerate_assets.go

@@ -492,6 +492,45 @@ func runRegenerateAssetsJob(job *regenerateAssetsJob) {
 	removeRegenerateAssetsJobLater(file, 3*time.Second)
 }
 
+func cancelRegenerateAssetsJob(file string) bool {
+	file = strings.TrimSpace(file)
+	if file == "" {
+		return false
+	}
+
+	regenerateAssetsMu.Lock()
+	job := regenerateAssetsJobs[file]
+	if job == nil {
+		regenerateAssetsMu.Unlock()
+		return false
+	}
+
+	id := job.AssetID
+	cancel := job.Cancel
+
+	if job.State == "queued" || job.State == "running" {
+		job.State = "cancelled"
+		job.Error = "Abgebrochen"
+		job.EndedAt = time.Now()
+	}
+	regenerateAssetsMu.Unlock()
+
+	if cancel != nil {
+		cancel()
+	}
+
+	setRegenerateAssetsTaskError(file, "Abgebrochen")
+
+	publishFinishedPostworkPhase(file, id, "postwork", "meta", "missing", "", "")
+	publishFinishedPostworkPhase(file, id, "postwork", "thumb", "missing", "", "")
+	publishFinishedPostworkPhase(file, id, "postwork", "teaser", "missing", "", "")
+	publishFinishedPostworkPhase(file, id, "postwork", "sprites", "missing", "", "")
+	publishFinishedPostworkPhase(file, id, "enrich", "analyze", "missing", "", "")
+
+	removeRegenerateAssetsJobLater(file, 2*time.Second)
+	return true
+}
+
 func handleRegenerateAssets(w http.ResponseWriter, r *http.Request) {
 	if r.Method != http.MethodPost && r.Method != http.MethodDelete {
 		http.Error(w, "method not allowed", http.StatusMethodNotAllowed)
@@ -520,13 +559,7 @@ func handleRegenerateAssets(w http.ResponseWriter, r *http.Request) {
 			return
 		}
 
-		regenerateAssetsMu.Lock()
+		cancelRegenerateAssetsJob(file)
-		job := regenerateAssetsJobs[file]
-		regenerateAssetsMu.Unlock()
-
-		if job != nil && job.Cancel != nil {
-			job.Cancel()
-		}
 
 		w.Header().Set("Content-Type", "application/json")
 		_ = json.NewEncoder(w).Encode(map[string]any{

frontend/src/components/ui/TrainingTab.tsx

@@ -933,7 +933,7 @@ function sortTrainingLabels(input: Partial<TrainingLabels> | null | undefined):
 function TrainingOverlay(props: { step: string; progress: number }) {
   return (
     <div className="absolute inset-0 z-20 flex items-center justify-center text-center text-white">
-      <div className="absolute -inset-2 bg-black/45 backdrop-blur-[8px] shadow-[inset_0_0_72px_30px_rgba(0,0,0,0.75)]" />
+      <div className="absolute inset-0 rounded-lg bg-black/45 backdrop-blur-[8px] shadow-[inset_0_0_72px_30px_rgba(0,0,0,0.75)]" />
 
       <div className="relative z-10 flex flex-col items-center justify-center">
         <LoadingSpinner
@@ -973,7 +973,7 @@ function LoadingImageOverlay(props: {
 
   return (
     <div className="absolute inset-0 z-20 flex items-center justify-center text-center text-white">
-      <div className="absolute -inset-2 rounded-xl bg-black/45 backdrop-blur-[8px] shadow-[inset_0_0_72px_30px_rgba(0,0,0,0.75)]" />
+      <div className="absolute inset-0 rounded-lg bg-black/45 backdrop-blur-[8px] shadow-[inset_0_0_72px_30px_rgba(0,0,0,0.75)]" />
 
       <div className="relative z-10 flex flex-col items-center justify-center">
         <LoadingSpinner
@@ -2062,6 +2062,8 @@ export default function TrainingTab(props: {
   const wasTrainingRunningRef = useRef(false)
   const shownTrainingCompletionRef = useRef<string | null>(null)
 
+  const [frameImageLoaded, setFrameImageLoaded] = useState(false)
+
   const imageBoxRef = useRef<HTMLDivElement | null>(null)
 
   const detectorBoxesScrollRef = useRef<HTMLDivElement | null>(null)
@@ -2231,6 +2233,15 @@ export default function TrainingTab(props: {
     return `${sample.frameUrl}&t=${encodeURIComponent(sample.sampleId)}&r=${imageReloadKey}`
   }, [sample, imageReloadKey])
 
+  useEffect(() => {
+    if (!imageSrc) {
+      setFrameImageLoaded(false)
+      return
+    }
+
+    setFrameImageLoaded(false)
+  }, [imageSrc])
+
   const canStartTraining = Boolean(trainingStatus?.canTrain)
   const feedbackCount = trainingStatus?.feedbackCount ?? 0
   const requiredCount = trainingStatus?.requiredCount ?? 5
@@ -3150,7 +3161,9 @@ export default function TrainingTab(props: {
     })
   }, [])
 
-  const showImageBoxes = !loading && !trainingRunning
+  const frameBusy = loading || (!!imageSrc && !frameImageLoaded)
+
+  const showImageBoxes = !frameBusy && !trainingRunning
 
   const shownTrainingDurationMs = useMemo(() => {
     const job = trainingStatus?.training
@@ -3428,7 +3441,7 @@ export default function TrainingTab(props: {
     return (
       <div
         className={[
-          'overflow-hidden rounded-xl border border-gray-200 bg-white shadow-sm dark:border-white/10 dark:bg-gray-900/70',
+          'relative z-0 overflow-hidden rounded-xl border border-gray-200 bg-white shadow-sm dark:border-white/10 dark:bg-gray-900/70',
           compact ? 'p-2' : 'p-3',
         ].join(' ')}
       >
@@ -3580,14 +3593,17 @@ export default function TrainingTab(props: {
 
   const detectorBoxesPanel = (opts?: {
     compact?: boolean
+    stretch?: boolean
     maxHeightClassName?: string
   }) => {
     const compact = Boolean(opts?.compact)
+    const stretch = Boolean(opts?.stretch)
 
     return (
       <div
         className={[
-          'rounded-lg bg-gray-50 ring-1 ring-black/5 dark:bg-white/5 dark:ring-white/10',
+          'relative z-0 flex min-h-0 flex-col overflow-hidden rounded-lg bg-gray-50 ring-1 ring-black/5 dark:bg-white/5 dark:ring-white/10',
+          stretch ? 'h-full max-h-full flex-1' : 'max-h-full',
           compact ? 'p-1.5' : 'p-2',
         ].join(' ')}
       >
@@ -3612,11 +3628,11 @@ export default function TrainingTab(props: {
         <div
           ref={detectorBoxesScrollRef}
           className={[
-            'mt-2 min-h-6 overflow-y-auto pr-1 overscroll-contain scroll-smooth',
+            'mt-2 min-h-0 flex-1 overflow-y-auto pr-1 overscroll-contain scroll-smooth',
             compact
               ? 'max-h-40 space-y-1'
               : [
-                  'max-h-32 space-y-1',
+                  'space-y-1',
                   opts?.maxHeightClassName || 'lg:max-h-[32dvh]',
                 ].join(' '),
           ].join(' ')}
@@ -3657,7 +3673,7 @@ export default function TrainingTab(props: {
                       <span className="flex min-w-0 items-center gap-1.5">
                         <Icon
                           className={[
-                            'shrink-0',
+                            'relative z-0 shrink-0',
                             compact ? 'h-3 w-3' : 'h-3.5 w-3.5',
                             isActive
                               ? 'text-blue-600 dark:text-blue-300'
@@ -3695,7 +3711,7 @@ export default function TrainingTab(props: {
                       type="button"
                       disabled={uiLocked}
                       className={[
-                        'group/delete shrink-0 inline-flex items-center justify-center rounded-md transition',
+                        'group/delete relative z-0 shrink-0 inline-flex items-center justify-center rounded-md transition',
                         compact ? 'h-6 w-6' : 'h-7 w-7',
                         'text-red-600 hover:bg-red-50 hover:text-red-700',
                         'focus:outline-none focus:ring-2 focus:ring-red-500/30',
@@ -3711,7 +3727,7 @@ export default function TrainingTab(props: {
                     >
                       <TrashIcon
                         className={[
-                          'transition group-hover/delete:scale-110',
+                          'relative z-0 transition group-hover/delete:scale-110',
                           compact ? 'h-3.5 w-3.5' : 'h-4 w-4',
                         ].join(' ')}
                         aria-hidden="true"
@@ -3738,7 +3754,7 @@ export default function TrainingTab(props: {
           <Button
             size="md"
             variant="secondary"
-            className={compact ? 'mt-1.5 w-full text-xs' : 'mt-2 w-full'}
+            className={compact ? 'mt-1.5 w-full text-xs' : 'mt-2 w-full shrink-0'}
             disabled={uiLocked}
             onClick={clearBoxes}
           >
@@ -3802,9 +3818,12 @@ export default function TrainingTab(props: {
             Bestätige oder korrigiere die Analyse. Jede Antwort wird als Trainingsdatenpunkt gespeichert.
           </div>
 
-          <div className="mt-3 flex min-h-0 flex-1 flex-col gap-3">
+          <div className="mt-3 flex min-h-0 flex-1 flex-col gap-3 overflow-hidden">
-            <div className="min-h-0">
+            <div className="min-h-0 flex-1 overflow-hidden">
-              {detectorBoxesPanel({ maxHeightClassName: 'lg:max-h-[28dvh]' })}
+              {detectorBoxesPanel({
+                stretch: true,
+                maxHeightClassName: 'lg:max-h-none',
+              })}
             </div>
 
             <div className="shrink-0">
@@ -3815,7 +3834,7 @@ export default function TrainingTab(props: {
 
         {/* Mitte */}
         <section className="min-w-0 rounded-xl border border-gray-200 bg-white p-2 shadow-sm dark:border-white/10 dark:bg-gray-900/60 sm:p-3 lg:self-start">
-          <div className="relative flex min-h-[180px] flex-1 items-center justify-center overflow-visible rounded-xl bg-black p-2 sm:p-3 lg:min-h-[300px]">
+          <div className="relative flex min-h-[180px] flex-1 items-center justify-center overflow-visible rounded-lg bg-black p-2 sm:p-3 lg:min-h-[300px]">
             {imageSrc ? (
               <div className="relative flex h-full w-full items-center justify-center">
                 <div
@@ -3836,10 +3855,12 @@ export default function TrainingTab(props: {
                     src={imageSrc}
                     alt="Training Frame"
                     draggable={false}
+                    onLoad={() => setFrameImageLoaded(true)}
+                    onError={() => setFrameImageLoaded(true)}
                     onContextMenu={(e) => e.preventDefault()}
                     onDragStart={(e) => e.preventDefault()}
                     className={[
-                      'block max-h-[52dvh] max-w-full object-contain sm:max-h-[60dvh] lg:max-h-[72dvh]',
+                      'block rounded-lg max-h-[52dvh] max-w-full object-contain sm:max-h-[60dvh] lg:max-h-[72dvh]',
                       'select-none',
                       imageTouchClass,
                       '[-webkit-user-drag:none] [-webkit-touch-callout:none]',
@@ -4228,10 +4249,10 @@ export default function TrainingTab(props: {
                     step={shownTrainingStep}
                     progress={shownTrainingProgress}
                   />
-                ) : loading ? (
+                ) : frameBusy ? (
                   <LoadingImageOverlay
-                    text={analysisStep}
+                    text={analysisStep || 'Frame wird geladen…'}
-                    progress={analysisProgress}
+                    progress={loading ? analysisProgress : 100}
                   />
                 ) : null}
               </div>
@@ -4250,13 +4271,14 @@ export default function TrainingTab(props: {
             )}
           </div>
 
-          <div className="sticky bottom-0 z-40 mt-2 grid grid-cols-2 gap-2 sm:static">
+          <div className="sticky bottom-0 z-40 mt-3 grid grid-cols-2 gap-2 sm:static sm:mt-4">
             <Button
               size="md"
               variant={hasManualCorrection ? 'primary' : 'soft'}
               color={hasManualCorrection ? undefined : 'emerald'}
               disabled={
                 uiLocked ||
+                frameBusy ||
                 !sample ||
                 (!hasManualCorrection && !sample.prediction.modelAvailable)
               }
@@ -4288,7 +4310,7 @@ export default function TrainingTab(props: {
             <Button
               size="md"
               variant="secondary"
-              disabled={uiLocked || !sample}
+              disabled={uiLocked || frameBusy || !sample}
               onClick={() => void loadNext({ forceNew: true })}
               className="w-full justify-center px-2 text-xs sm:text-sm"
               title="Dieses Bild nicht bewerten und ein anderes laden."