bugfixes
This commit is contained in:
Linrador
parent
96b81fc89d
commit
cf5888d9e5
@ -65,8 +65,8 @@ const (
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// Sprite-Modus ist aktuell deaktiviert. Analyse läuft über Video-Frames.
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analyzeMaxSpriteCandidates = 24
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// Video-Modus: schnelle Vorschau. Für bessere Trefferquote später 24.
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// neu, falls du später alle N Sekunden willst
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// Video-Modus: extrahiert 1 Frame alle N Sekunden.
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// 1 = jeder Sekunde, 3 = alle 3 Sekunden, 5 = alle 5 Sekunden.
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analyzeVideoFrameIntervalSeconds = 3
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// AI-Server nicht mit tausenden Pfaden auf einmal fluten.
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@ -668,12 +668,18 @@ func trainingPredictFramePathsBatchForAnalyze(
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res, err := client.Do(req)
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if err != nil {
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if ctxErr := ctx.Err(); ctxErr != nil {
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return nil, ctxErr
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}
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return nil, err
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}
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defer res.Body.Close()
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var parsed analyzeBatchPredictResp
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if err := json.NewDecoder(res.Body).Decode(&parsed); err != nil {
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if ctxErr := ctx.Err(); ctxErr != nil {
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return nil, ctxErr
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}
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return nil, err
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}
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@ -1785,15 +1791,23 @@ func analyzeVideoFromFramesForGoal(
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"Analyse 0%",
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)
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if err := ctx.Err(); err != nil {
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publishAnalysisError(startedAtMs, file, "Analyse abgebrochen", err)
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return nil, nil, err
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}
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durationSec, _ := durationSecondsForAnalyze(ctx, outPath)
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if err := ctx.Err(); err != nil {
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publishAnalysisError(startedAtMs, file, "Analyse abgebrochen", err)
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return nil, nil, err
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}
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if durationSec <= 0 {
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err := appErrorf("videolänge konnte nicht bestimmt werden")
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publishAnalysisError(startedAtMs, file, "Analyse fehlgeschlagen", err)
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return nil, nil, err
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}
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// Hilfsfunktion: garantiert, dass keine Prozentpunkte übersprungen werden.
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// Beispiel: letzter Stand 12, neuer Stand 17 -> sendet 13,14,15,16,17.
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publishPercentRange := func(lastPercent *int, nextPercent int, current int, total int, extractPhase bool) {
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if total <= 0 {
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total = 1
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@ -1814,7 +1828,6 @@ func analyzeVideoFromFramesForGoal(
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label := fmt.Sprintf("Analyse %d%%", p)
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if extractPhase {
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// p läuft global 0..50, publishAnalyzeExtractProgress erwartet aber 0..1.
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ratio := float64(p) / 50.0
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if ratio < 0 {
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ratio = 0
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@ -1830,9 +1843,6 @@ func analyzeVideoFromFramesForGoal(
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label,
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)
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} else {
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// Für die Inferenzphase current/total so wählen, dass der globale
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// Fortschritt in publishAnalyzeInferenceProgress wieder exakt p ergibt:
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// current/total = (p - 50) / 50
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inferenceCurrent := current
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inferenceTotal := total
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@ -1854,6 +1864,16 @@ func analyzeVideoFromFramesForGoal(
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*lastPercent = nextPercent
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}
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failCancelled := func() ([]analyzeHit, []analyzeHit, error) {
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err := ctx.Err()
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if err == nil {
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err = context.Canceled
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}
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publishAnalysisError(startedAtMs, file, "Analyse abgebrochen", err)
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return nil, nil, err
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}
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lastExtractPercent := 0
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samples, cleanup, err := extractVideoFramesBatch(
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@ -1887,6 +1907,14 @@ func analyzeVideoFromFramesForGoal(
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},
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)
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if cleanup != nil {
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defer cleanup()
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}
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if ctx.Err() != nil {
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return failCancelled()
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}
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if err != nil {
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publishAnalysisError(startedAtMs, file, "Frames konnten nicht extrahiert werden", err)
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return nil, nil, err
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@ -1910,8 +1938,16 @@ func analyzeVideoFromFramesForGoal(
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)
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}
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if ctx.Err() != nil {
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return failCancelled()
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}
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paths := make([]string, 0, len(samples))
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for _, sample := range samples {
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if err := ctx.Err(); err != nil {
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return failCancelled()
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}
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paths = append(paths, sample.Path)
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}
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@ -1925,6 +1961,10 @@ func analyzeVideoFromFramesForGoal(
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"Analyse 50%",
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)
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if ctx.Err() != nil {
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return failCancelled()
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}
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// Schneller AI-Server-Batch-Pfad für nsfw, highlights und all.
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// Wichtig: ensureAnalyzeAllGoalsForVideoCtx ruft goal="all" auf.
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// Ohne diesen Block fällt "all" auf die sehr langsame Einzelbild-Analyse zurück.
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@ -1937,6 +1977,10 @@ func analyzeVideoFromFramesForGoal(
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detectorOnly := false
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for startIdx := 0; startIdx < len(samples); startIdx += analyzeFramePredictBatchSize {
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if ctx.Err() != nil {
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return failCancelled()
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}
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endIdx := startIdx + analyzeFramePredictBatchSize
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if endIdx > len(samples) {
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endIdx = len(samples)
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@ -1948,6 +1992,10 @@ func analyzeVideoFromFramesForGoal(
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detectorOnly,
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)
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if ctx.Err() != nil {
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return failCancelled()
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}
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if batchErr != nil || len(predictions) < endIdx-startIdx {
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appLogln("⚠️ video batch analyse fehlgeschlagen, fallback auf einzelbild-analyse:", batchErr)
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@ -1968,6 +2016,10 @@ func analyzeVideoFromFramesForGoal(
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}
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for i := 0; i < endIdx-startIdx; i++ {
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if ctx.Err() != nil {
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return failCancelled()
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}
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sample := samples[startIdx+i]
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pred := predictions[i]
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@ -1999,6 +2051,10 @@ func analyzeVideoFromFramesForGoal(
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}
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if batchOK {
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if ctx.Err() != nil {
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return failCancelled()
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}
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if lastInferencePercent < 100 {
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publishPercentRange(
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&lastInferencePercent,
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@ -2012,8 +2068,6 @@ func analyzeVideoFromFramesForGoal(
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cleanNSFWHits := mergeAnalyzeHits(nsfwHits)
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cleanHighlightHits := mergeAnalyzeHits(highlightHits)
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cleanup()
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publishAnalysisFinished(startedAtMs, total, file, "Analyse abgeschlossen")
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return cleanNSFWHits, cleanHighlightHits, nil
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}
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@ -2022,12 +2076,21 @@ func analyzeVideoFromFramesForGoal(
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// Fallback: langsame Einzelbild-Analyse.
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// Dieser Pfad sollte nur laufen, wenn der AI-Server-Batch fehlschlägt.
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for i, sample := range samples {
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if ctx.Err() != nil {
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return failCancelled()
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}
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t := sample.Time
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switch goal {
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case "nsfw":
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res, err := classifyFramePathForAnalyze(ctx, sample.Path)
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if err == nil {
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res, frameErr := classifyFramePathForAnalyze(ctx, sample.Path)
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if ctx.Err() != nil {
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return failCancelled()
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}
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if frameErr == nil {
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bestLabel, bestScore := pickBestNSFWResult(res.Results)
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if bestLabel != "" && bestScore >= nsfwThresholdForLabel(bestLabel) {
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nsfwHits = append(nsfwHits, analyzeHit{
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@ -2042,10 +2105,20 @@ func analyzeVideoFromFramesForGoal(
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case "highlights":
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pred := predictFramePathForAnalyze(ctx, sample.Path)
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if ctx.Err() != nil {
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return failCancelled()
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}
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highlightHits = appendHighlightHitsFromPrediction(highlightHits, pred, t)
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default:
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pred := predictFramePathForAnalyze(ctx, sample.Path)
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if ctx.Err() != nil {
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return failCancelled()
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}
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nsfwHits = appendNSFWHitFromPrediction(nsfwHits, pred, t)
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highlightHits = appendHighlightHitsFromPrediction(highlightHits, pred, t)
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}
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@ -2066,6 +2139,10 @@ func analyzeVideoFromFramesForGoal(
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)
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}
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if ctx.Err() != nil {
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return failCancelled()
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}
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if lastInferencePercent < 100 {
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publishPercentRange(
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&lastInferencePercent,
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@ -2079,8 +2156,6 @@ func analyzeVideoFromFramesForGoal(
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cleanNSFWHits := mergeAnalyzeHits(nsfwHits)
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cleanHighlightHits := mergeAnalyzeHits(highlightHits)
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cleanup()
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publishAnalysisFinished(startedAtMs, total, file, "Analyse abgeschlossen")
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return cleanNSFWHits, cleanHighlightHits, nil
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@ -492,6 +492,45 @@ func runRegenerateAssetsJob(job *regenerateAssetsJob) {
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removeRegenerateAssetsJobLater(file, 3*time.Second)
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}
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func cancelRegenerateAssetsJob(file string) bool {
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file = strings.TrimSpace(file)
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if file == "" {
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return false
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}
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regenerateAssetsMu.Lock()
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job := regenerateAssetsJobs[file]
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if job == nil {
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regenerateAssetsMu.Unlock()
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return false
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}
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id := job.AssetID
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cancel := job.Cancel
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if job.State == "queued" || job.State == "running" {
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job.State = "cancelled"
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job.Error = "Abgebrochen"
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job.EndedAt = time.Now()
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}
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regenerateAssetsMu.Unlock()
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if cancel != nil {
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cancel()
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}
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setRegenerateAssetsTaskError(file, "Abgebrochen")
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publishFinishedPostworkPhase(file, id, "postwork", "meta", "missing", "", "")
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publishFinishedPostworkPhase(file, id, "postwork", "thumb", "missing", "", "")
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publishFinishedPostworkPhase(file, id, "postwork", "teaser", "missing", "", "")
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publishFinishedPostworkPhase(file, id, "postwork", "sprites", "missing", "", "")
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publishFinishedPostworkPhase(file, id, "enrich", "analyze", "missing", "", "")
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removeRegenerateAssetsJobLater(file, 2*time.Second)
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return true
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}
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func handleRegenerateAssets(w http.ResponseWriter, r *http.Request) {
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if r.Method != http.MethodPost && r.Method != http.MethodDelete {
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http.Error(w, "method not allowed", http.StatusMethodNotAllowed)
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@ -520,13 +559,7 @@ func handleRegenerateAssets(w http.ResponseWriter, r *http.Request) {
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return
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}
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regenerateAssetsMu.Lock()
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job := regenerateAssetsJobs[file]
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regenerateAssetsMu.Unlock()
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if job != nil && job.Cancel != nil {
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job.Cancel()
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}
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cancelRegenerateAssetsJob(file)
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w.Header().Set("Content-Type", "application/json")
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_ = json.NewEncoder(w).Encode(map[string]any{
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@ -933,7 +933,7 @@ function sortTrainingLabels(input: Partial<TrainingLabels> | null | undefined):
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function TrainingOverlay(props: { step: string; progress: number }) {
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return (
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<div className="absolute inset-0 z-20 flex items-center justify-center text-center text-white">
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<div className="absolute -inset-2 bg-black/45 backdrop-blur-[8px] shadow-[inset_0_0_72px_30px_rgba(0,0,0,0.75)]" />
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<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)]" />
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<div className="relative z-10 flex flex-col items-center justify-center">
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<LoadingSpinner
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@ -973,7 +973,7 @@ function LoadingImageOverlay(props: {
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return (
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<div className="absolute inset-0 z-20 flex items-center justify-center text-center text-white">
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<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)]" />
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<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)]" />
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<div className="relative z-10 flex flex-col items-center justify-center">
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<LoadingSpinner
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@ -2062,6 +2062,8 @@ export default function TrainingTab(props: {
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const wasTrainingRunningRef = useRef(false)
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const shownTrainingCompletionRef = useRef<string | null>(null)
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const [frameImageLoaded, setFrameImageLoaded] = useState(false)
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const imageBoxRef = useRef<HTMLDivElement | null>(null)
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const detectorBoxesScrollRef = useRef<HTMLDivElement | null>(null)
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@ -2231,6 +2233,15 @@ export default function TrainingTab(props: {
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return `${sample.frameUrl}&t=${encodeURIComponent(sample.sampleId)}&r=${imageReloadKey}`
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}, [sample, imageReloadKey])
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useEffect(() => {
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if (!imageSrc) {
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setFrameImageLoaded(false)
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return
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}
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setFrameImageLoaded(false)
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}, [imageSrc])
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const canStartTraining = Boolean(trainingStatus?.canTrain)
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const feedbackCount = trainingStatus?.feedbackCount ?? 0
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const requiredCount = trainingStatus?.requiredCount ?? 5
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@ -3150,7 +3161,9 @@ export default function TrainingTab(props: {
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})
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}, [])
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const showImageBoxes = !loading && !trainingRunning
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const frameBusy = loading || (!!imageSrc && !frameImageLoaded)
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const showImageBoxes = !frameBusy && !trainingRunning
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const shownTrainingDurationMs = useMemo(() => {
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const job = trainingStatus?.training
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@ -3428,7 +3441,7 @@ export default function TrainingTab(props: {
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return (
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<div
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className={[
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'overflow-hidden rounded-xl border border-gray-200 bg-white shadow-sm dark:border-white/10 dark:bg-gray-900/70',
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'relative z-0 overflow-hidden rounded-xl border border-gray-200 bg-white shadow-sm dark:border-white/10 dark:bg-gray-900/70',
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compact ? 'p-2' : 'p-3',
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].join(' ')}
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>
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@ -3580,14 +3593,17 @@ export default function TrainingTab(props: {
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const detectorBoxesPanel = (opts?: {
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compact?: boolean
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stretch?: boolean
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maxHeightClassName?: string
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}) => {
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const compact = Boolean(opts?.compact)
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const stretch = Boolean(opts?.stretch)
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return (
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<div
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className={[
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'rounded-lg bg-gray-50 ring-1 ring-black/5 dark:bg-white/5 dark:ring-white/10',
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'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',
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stretch ? 'h-full max-h-full flex-1' : 'max-h-full',
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compact ? 'p-1.5' : 'p-2',
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].join(' ')}
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>
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@ -3612,11 +3628,11 @@ export default function TrainingTab(props: {
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<div
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ref={detectorBoxesScrollRef}
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className={[
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'mt-2 min-h-6 overflow-y-auto pr-1 overscroll-contain scroll-smooth',
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'mt-2 min-h-0 flex-1 overflow-y-auto pr-1 overscroll-contain scroll-smooth',
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compact
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? 'max-h-40 space-y-1'
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: [
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'max-h-32 space-y-1',
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'space-y-1',
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opts?.maxHeightClassName || 'lg:max-h-[32dvh]',
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].join(' '),
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].join(' ')}
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@ -3657,7 +3673,7 @@ export default function TrainingTab(props: {
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<span className="flex min-w-0 items-center gap-1.5">
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<Icon
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className={[
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'shrink-0',
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'relative z-0 shrink-0',
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compact ? 'h-3 w-3' : 'h-3.5 w-3.5',
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isActive
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? 'text-blue-600 dark:text-blue-300'
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@ -3695,7 +3711,7 @@ export default function TrainingTab(props: {
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type="button"
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disabled={uiLocked}
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className={[
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'group/delete shrink-0 inline-flex items-center justify-center rounded-md transition',
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'group/delete relative z-0 shrink-0 inline-flex items-center justify-center rounded-md transition',
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compact ? 'h-6 w-6' : 'h-7 w-7',
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'text-red-600 hover:bg-red-50 hover:text-red-700',
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'focus:outline-none focus:ring-2 focus:ring-red-500/30',
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@ -3711,7 +3727,7 @@ export default function TrainingTab(props: {
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>
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<TrashIcon
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className={[
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'transition group-hover/delete:scale-110',
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'relative z-0 transition group-hover/delete:scale-110',
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compact ? 'h-3.5 w-3.5' : 'h-4 w-4',
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].join(' ')}
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aria-hidden="true"
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@ -3738,7 +3754,7 @@ export default function TrainingTab(props: {
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<Button
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size="md"
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variant="secondary"
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className={compact ? 'mt-1.5 w-full text-xs' : 'mt-2 w-full'}
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className={compact ? 'mt-1.5 w-full text-xs' : 'mt-2 w-full shrink-0'}
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disabled={uiLocked}
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onClick={clearBoxes}
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>
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@ -3802,9 +3818,12 @@ export default function TrainingTab(props: {
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Bestätige oder korrigiere die Analyse. Jede Antwort wird als Trainingsdatenpunkt gespeichert.
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</div>
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<div className="mt-3 flex min-h-0 flex-1 flex-col gap-3">
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<div className="min-h-0">
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{detectorBoxesPanel({ maxHeightClassName: 'lg:max-h-[28dvh]' })}
|
||||
<div className="mt-3 flex min-h-0 flex-1 flex-col gap-3 overflow-hidden">
|
||||
<div className="min-h-0 flex-1 overflow-hidden">
|
||||
{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}
|
||||
progress={analysisProgress}
|
||||
text={analysisStep || 'Frame wird geladen…'}
|
||||
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."
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user