bugfixes

backend/training.go

@@ -1842,6 +1842,9 @@ func trainingCreateNextSample() (*TrainingSample, error) {
 
 func trainingCreateUncertainNextSampleWithProgress(startedAtMs int64) (*TrainingSample, error) {
 	const attempts = 8
+	const stepsPerAttempt = 4
+
+	totalSteps := attempts*stepsPerAttempt + 1
 
 	root, err := trainingRootDir()
 	if err != nil {
@@ -1853,22 +1856,47 @@ func trainingCreateUncertainNextSampleWithProgress(startedAtMs int64) (*Training
 	errs := []string{}
 
 	for i := 0; i < attempts; i++ {
-		publishAnalysisStep(
+		attempt := i + 1
+		stepStart := i*stepsPerAttempt + 1
+
+		prefix := fmt.Sprintf("Kandidat %d/%d: ", attempt, attempts)
+
+		sample, err := trainingCreateNextSampleWithProgressRange(
 			startedAtMs,
-			i+1,
+			stepStart,
-			attempts+1,
+			totalSteps,
-			"",
+			prefix,
-			fmt.Sprintf("Unsicherer Kandidat %d/%d wird analysiert…", i+1, attempts),
 		)
 
-		sample, err := trainingCreateNextSample()
 		if err != nil {
 			errs = append(errs, err.Error())
+
+			publishAnalysisStep(
+				startedAtMs,
+				stepStart+stepsPerAttempt-1,
+				totalSteps,
+				"",
+				fmt.Sprintf("Kandidat %d/%d fehlgeschlagen…", attempt, attempts),
+			)
+
 			continue
 		}
 
 		score := trainingPredictionUncertaintyScore(sample.Prediction)
 
+		publishAnalysisStep(
+			startedAtMs,
+			stepStart+stepsPerAttempt-1,
+			totalSteps,
+			sample.SourceFile,
+			fmt.Sprintf(
+				"Kandidat %d/%d bewertet · Unsicherheit %.0f%%",
+				attempt,
+				attempts,
+				score*100,
+			),
+		)
+
 		if score > bestScore {
 			if best != nil {
 				trainingDeleteSampleFiles(root, best.SampleID)
@@ -1891,8 +1919,8 @@ func trainingCreateUncertainNextSampleWithProgress(startedAtMs int64) (*Training
 
 	publishAnalysisStep(
 		startedAtMs,
-		attempts+1,
+		totalSteps,
-		attempts+1,
+		totalSteps,
 		best.SourceFile,
 		fmt.Sprintf("Unsicherer Kandidat gewählt · Score %.0f%%", bestScore*100),
 	)
@@ -1988,7 +2016,31 @@ func trainingPredictionUncertaintyScore(pred TrainingPrediction) float64 {
 }
 
 func trainingCreateNextSampleWithProgress(startedAtMs int64) (*TrainingSample, error) {
-	publishAnalysisStep(startedAtMs, 1, 4, "", "Video wird ausgewählt…")
+	return trainingCreateNextSampleWithProgressRange(
+		startedAtMs,
+		1,
+		4,
+		"",
+	)
+}
+
+func trainingCreateNextSampleWithProgressRange(
+	startedAtMs int64,
+	stepStart int,
+	stepTotal int,
+	prefix string,
+) (*TrainingSample, error) {
+	publishStep := func(localStep int, sourceFile string, message string) {
+		publishAnalysisStep(
+			startedAtMs,
+			stepStart+localStep-1,
+			stepTotal,
+			sourceFile,
+			prefix+message,
+		)
+	}
+
+	publishStep(1, "", "Video wird ausgewählt…")
 
 	settings := getSettings()
 
@@ -2002,7 +2054,9 @@ func trainingCreateNextSampleWithProgress(startedAtMs int64) (*TrainingSample, e
 		return nil, err
 	}
 
-	publishAnalysisStep(startedAtMs, 2, 4, filepath.Base(videoPath), "Bild wird extrahiert…")
+	sourceFile := filepath.Base(videoPath)
+
+	publishStep(2, sourceFile, "Bild wird extrahiert…")
 
 	duration := trainingProbeDurationSeconds(videoPath)
 	second := trainingRandomSecond(duration)
@@ -2019,6 +2073,7 @@ func trainingCreateNextSampleWithProgress(startedAtMs int64) (*TrainingSample, e
 	if err := os.MkdirAll(filepath.Join(root, "frames"), 0755); err != nil {
 		return nil, err
 	}
+
 	if err := os.MkdirAll(filepath.Join(root, "samples"), 0755); err != nil {
 		return nil, err
 	}
@@ -2027,6 +2082,8 @@ func trainingCreateNextSampleWithProgress(startedAtMs int64) (*TrainingSample, e
 	framePath := filepath.Join(root, "frames", id+".jpg")
 
 	if err := trainingExtractFrame(videoPath, framePath, second); err != nil {
+		publishStep(2, sourceFile, "Bild wird erneut bei Sekunde 0 extrahiert…")
+
 		second = 0
 		id = trainingMakeSampleID(videoPath, second)
 		framePath = filepath.Join(root, "frames", id+".jpg")
@@ -2036,7 +2093,7 @@ func trainingCreateNextSampleWithProgress(startedAtMs int64) (*TrainingSample, e
 		}
 	}
 
-	publishAnalysisStep(startedAtMs, 3, 4, filepath.Base(videoPath), "Bild wird analysiert…")
+	publishStep(3, sourceFile, "Bild wird analysiert…")
 
 	prediction := trainingPredictFrame(framePath)
 
@@ -2048,7 +2105,7 @@ func trainingCreateNextSampleWithProgress(startedAtMs int64) (*TrainingSample, e
 	sample := &TrainingSample{
 		SampleID:        id,
 		FrameURL:        "/api/training/frame?id=" + id,
-		SourceFile:      filepath.Base(videoPath),
+		SourceFile:      sourceFile,
 		SourcePath:      videoPath,
 		SourceSizeBytes: sourceSizeBytes,
 		Second:          second,
@@ -2056,7 +2113,7 @@ func trainingCreateNextSampleWithProgress(startedAtMs int64) (*TrainingSample, e
 		Prediction:      prediction,
 	}
 
-	publishAnalysisStep(startedAtMs, 4, 4, filepath.Base(videoPath), "Analyse-Ergebnis wird gespeichert…")
+	publishStep(4, sourceFile, "Analyse-Ergebnis wird gespeichert…")
 
 	if err := trainingWriteSample(root, sample); err != nil {
 		return nil, err

frontend/src/App.tsx

@@ -2741,7 +2741,6 @@ export default function App() {
     if (!authed) return
 
     let es: EventSource | null = null
-    let autostartEs: EventSource | null = null
     let fallbackTimer: number | null = null
 
     const stopFallbackPoll = () => {
@@ -2844,6 +2843,12 @@ export default function App() {
 
         if (msg?.type !== 'analysis_progress') return
 
+        window.dispatchEvent(
+          new CustomEvent('app:sse:analysis', {
+            detail: msg,
+          })
+        )
+
         const file = baseName(String(msg?.file ?? '').trim())
         if (!file) return
 
@@ -2929,6 +2934,12 @@ export default function App() {
         if (data?.type !== 'training_status') return
 
         setTrainingTabRunning(Boolean(data?.training?.running))
+
+        window.dispatchEvent(
+          new CustomEvent('app:sse:training', {
+            detail: data,
+          })
+        )
       } catch {
         // ignore
       }
@@ -2944,20 +2955,6 @@ export default function App() {
     eventSourceRef.current = es
     modelEventNamesRef.current = new Set()
 
-    autostartEs = new EventSource('/api/autostart/state/stream')
-
-    autostartEs.addEventListener('autostart', (ev) => {
-      try {
-        applyAutostartState(JSON.parse(String((ev as MessageEvent).data ?? 'null')))
-      } catch {
-        // ignore
-      }
-    })
-
-    autostartEs.onerror = () => {
-      // Falls der separate Stream ausfällt, wenigstens beim Fokus/Visibility wieder korrekt ziehen.
-    }
-
     es.onopen = () => {
       stopFallbackPoll()
       void loadTaskStateOnce()
@@ -3010,10 +3007,6 @@ export default function App() {
         es.close()
       }
 
-      if (autostartEs) {
-        autostartEs.close()
-      }
-
       eventSourceRef.current = null
       modelEventNamesRef.current = new Set()
     }

frontend/src/components/ui/TrainingTab.tsx

@@ -2326,10 +2326,10 @@ export default function TrainingTab(props: {
 
       const url = `/api/training/next${params.toString() ? `?${params.toString()}` : ''}`
 
-      setAnalysisProgress(25)
+      setAnalysisProgress(uncertainMode ? 5 : 25)
       setAnalysisStep(
         uncertainMode
-          ? 'Mehrere Kandidaten werden bewertet…'
+          ? 'Mehrere Kandidaten werden vorbereitet…'
           : 'Bild wird vorbereitet…'
       )
 
@@ -2441,11 +2441,9 @@ export default function TrainingTab(props: {
   }, [])
 
   useEffect(() => {
-    const es = new EventSource('/api/events/stream')
+    const onTraining = (event: Event) => {
-
-    const onTraining = (ev: MessageEvent) => {
       try {
-        const data = JSON.parse(String(ev.data ?? 'null'))
+        const data = (event as CustomEvent<any>).detail
 
         if (data?.type !== 'training_status') return
 
@@ -2457,18 +2455,69 @@ export default function TrainingTab(props: {
       }
     }
 
-    es.addEventListener('training', onTraining as EventListener)
+    window.addEventListener('app:sse:training', onTraining as EventListener)
-
-    es.onerror = () => {
-      // Optional: Polling-Fallback bleibt separat bestehen.
-    }
 
     return () => {
-      es.removeEventListener('training', onTraining as EventListener)
+      window.removeEventListener('app:sse:training', onTraining as EventListener)
-      es.close()
     }
   }, [applyTrainingStatus])
 
+  useEffect(() => {
+    const onAnalysis = (event: Event) => {
+      try {
+        const data = (event as CustomEvent<any>).detail
+
+        const message = String(
+          data?.message ||
+          data?.step ||
+          data?.title ||
+          ''
+        ).trim()
+
+        const current = Number(data?.current ?? data?.stepIndex ?? data?.index)
+        const total = Number(data?.total ?? data?.steps ?? data?.stepTotal)
+
+        const rawProgress = Number(
+          data?.progress ??
+          data?.percent ??
+          data?.analysis?.progress
+        )
+
+        let nextProgress: number | null = null
+
+        if (
+          Number.isFinite(current) &&
+          Number.isFinite(total) &&
+          total > 0
+        ) {
+          nextProgress = (current / total) * 100
+        } else if (Number.isFinite(rawProgress)) {
+          nextProgress = rawProgress <= 1
+            ? rawProgress * 100
+            : rawProgress
+        }
+
+        if (message) {
+          setAnalysisStep(message)
+        }
+
+        if (nextProgress !== null) {
+          setAnalysisProgress((prev) =>
+            Math.max(prev, clampPercent(nextProgress))
+          )
+        }
+      } catch {
+        // ignore
+      }
+    }
+
+    window.addEventListener('app:sse:analysis', onAnalysis as EventListener)
+
+    return () => {
+      window.removeEventListener('app:sse:analysis', onAnalysis as EventListener)
+    }
+  }, [])
+
   useEffect(() => {
     const draggingBox = Boolean(drawingBox || boxInteraction)