feat: Enhance AI extraction summaries and worker allocation for GPU support
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3 changed files with 90 additions and 51 deletions
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@ -450,12 +450,14 @@ namespace ImageCatalog_2
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private string BuildNumberAiIdleSummary()
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{
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var workerCount = ResolveNumberAiWorkerCount(UseNumberAiGpu, NumberAiWorkloadLevel);
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return $"In attesa. Carico {NumberAiWorkloadLevel}/5, {workerCount} worker, 0.00 img/s.";
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var unit = UseNumberAiGpu ? "batch" : "worker";
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return $"In attesa. Carico {NumberAiWorkloadLevel}/5, {workerCount} {unit}, 0.00 img/s.";
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}
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private static string BuildNumberAiProgressSummary(AiExtractionProgressUpdate progress)
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{
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return $"{progress.ProcessedFiles}/{progress.TotalFiles} immagini, media {progress.AverageImagesPerSecond:F2} img/s, carico {progress.WorkloadLevel}/5, {progress.WorkerCount} worker.";
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var unit = progress.UseGpu ? "batch" : "worker";
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return $"{progress.ProcessedFiles}/{progress.TotalFiles} immagini, media {progress.AverageImagesPerSecond:F2} img/s, carico {progress.WorkloadLevel}/5, {progress.WorkerCount} {unit}.";
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}
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private static string BuildNumberAiCompletionSummary(AiExtractionRunSummary summary)
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@ -465,7 +467,8 @@ namespace ImageCatalog_2
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return "Nessuna immagine trovata per OCR.";
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}
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return $"Completato: {summary.ProcessedFiles}/{summary.TotalFiles} immagini, media finale {summary.AverageImagesPerSecond:F2} img/s, errori {summary.FailedFiles}, carico {summary.WorkloadLevel}/5, {summary.WorkerCount} worker.";
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var unit = summary.UseGpu ? "batch" : "worker";
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return $"Completato: {summary.ProcessedFiles}/{summary.TotalFiles} immagini, media finale {summary.AverageImagesPerSecond:F2} img/s, errori {summary.FailedFiles}, carico {summary.WorkloadLevel}/5, {summary.WorkerCount} {unit}.";
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}
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private List<string> LoadAvailableFonts()
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@ -2228,11 +2231,11 @@ namespace ImageCatalog_2
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var requestedWorkers = useGpu
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? normalized switch
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{
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1 => 2,
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2 => 4,
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3 => 8,
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4 => 12,
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_ => 16
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1 => 4,
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2 => 8,
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3 => 16,
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4 => 24,
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_ => 32
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}
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: normalized switch
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{
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@ -2243,7 +2246,7 @@ namespace ImageCatalog_2
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_ => 5
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};
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return Math.Min(requestedWorkers, maxWorkers);
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return useGpu ? requestedWorkers : Math.Min(requestedWorkers, maxWorkers);
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}
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private static int NormalizeFaceMinSize(int value)
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@ -45,8 +45,8 @@ public class AiExtractionService : IAiExtractionService
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var total = imageFiles.Count;
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if (total == 0)
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{
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var emptySummary = new AiExtractionRunSummary(0, 0, 0, 0, workloadLevel, workerCount);
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await onProgress(new AiExtractionProgressUpdate(0, 0, 100, 0, workloadLevel, workerCount)).ConfigureAwait(false);
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var emptySummary = new AiExtractionRunSummary(0, 0, 0, 0, workloadLevel, workerCount, request.UseGpu);
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await onProgress(new AiExtractionProgressUpdate(0, 0, 100, 0, workloadLevel, workerCount, request.UseGpu)).ConfigureAwait(false);
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return emptySummary;
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}
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@ -79,7 +79,7 @@ public class AiExtractionService : IAiExtractionService
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var currentProcessed = Interlocked.Increment(ref processed);
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var averageImagesPerSecond = CalculateAverageImagesPerSecond(currentProcessed, stopwatch.Elapsed);
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var percent = currentProcessed * 100.0 / total;
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await onProgress(new AiExtractionProgressUpdate(total, currentProcessed, percent, averageImagesPerSecond, workloadLevel, workerCount)).ConfigureAwait(false);
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await onProgress(new AiExtractionProgressUpdate(total, currentProcessed, percent, averageImagesPerSecond, workloadLevel, workerCount, request.UseGpu)).ConfigureAwait(false);
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var shouldLog = false;
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lock (logLock)
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@ -94,54 +94,74 @@ public class AiExtractionService : IAiExtractionService
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if (shouldLog)
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{
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_logger.LogInformation(
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"Number AI progress: {Processed}/{Total} ({Percent:F1}%), {ImagesPerSecond:F2} img/s avg, workload {WorkloadLevel} ({WorkerCount} workers)",
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"Number AI progress: {Processed}/{Total} ({Percent:F1}%), {ImagesPerSecond:F2} img/s avg, workload {WorkloadLevel} ({WorkerCount} {ExecutionUnit})",
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currentProcessed,
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total,
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percent,
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averageImagesPerSecond,
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workloadLevel,
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workerCount);
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workerCount,
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request.UseGpu ? "batch" : "workers");
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}
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}
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}, token);
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var workerTasks = Enumerable.Range(0, workerCount)
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.Select(_ => Task.Run(async () =>
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{
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using var engine = new NumberRecognitionEngine(modelConfiguration, _logger);
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await foreach (var file in fileChannel.Reader.ReadAllAsync(token).ConfigureAwait(false))
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{
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var extracted = string.Empty;
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try
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{
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extracted = engine.ProcessImage(file).Text;
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}
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catch (Exception ex)
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{
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lock (failureLock)
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{
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failed++;
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firstFailure ??= ex;
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}
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_logger.LogWarning(ex, "Error processing AI OCR for {File}", file);
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}
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await resultChannel.Writer.WriteAsync(new AiResultItem { Path = file, Text = extracted }, token).ConfigureAwait(false);
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}
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}, token))
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.ToArray();
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try
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{
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foreach (var file in imageFiles)
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if (request.UseGpu)
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{
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await fileChannel.Writer.WriteAsync(file, token).ConfigureAwait(false);
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}
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using var engine = new NumberRecognitionEngine(modelConfiguration, _logger);
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var resultProgress = new SynchronousProgress<ImageResult>(result =>
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{
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resultChannel.Writer.TryWrite(new AiResultItem { Path = result.FilePath, Text = result.Text });
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});
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fileChannel.Writer.TryComplete();
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await Task.WhenAll(workerTasks).ConfigureAwait(false);
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await engine.ProcessFilesAsync(
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imageFiles,
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skipTextNegative: false,
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maxDegreeOfParallelism: workerCount,
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progress: null,
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resultProgress: resultProgress,
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cancellationToken: token).ConfigureAwait(false);
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}
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else
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{
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var workerTasks = Enumerable.Range(0, workerCount)
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.Select(_ => Task.Run(async () =>
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{
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using var engine = new NumberRecognitionEngine(modelConfiguration, _logger);
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await foreach (var file in fileChannel.Reader.ReadAllAsync(token).ConfigureAwait(false))
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{
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var extracted = string.Empty;
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try
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{
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extracted = engine.ProcessImage(file).Text;
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}
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catch (Exception ex)
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{
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lock (failureLock)
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{
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failed++;
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firstFailure ??= ex;
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}
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_logger.LogWarning(ex, "Error processing AI OCR for {File}", file);
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}
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await resultChannel.Writer.WriteAsync(new AiResultItem { Path = file, Text = extracted }, token).ConfigureAwait(false);
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}
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}, token))
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.ToArray();
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foreach (var file in imageFiles)
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{
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await fileChannel.Writer.WriteAsync(file, token).ConfigureAwait(false);
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}
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fileChannel.Writer.TryComplete();
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await Task.WhenAll(workerTasks).ConfigureAwait(false);
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}
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}
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finally
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{
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@ -161,16 +181,18 @@ public class AiExtractionService : IAiExtractionService
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failed,
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CalculateAverageImagesPerSecond(processed, stopwatch.Elapsed),
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workloadLevel,
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workerCount);
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workerCount,
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request.UseGpu);
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_logger.LogInformation(
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"Number AI completed: {Processed}/{Total} processed, {Failed} failures, {ImagesPerSecond:F2} img/s avg, workload {WorkloadLevel} ({WorkerCount} workers)",
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"Number AI completed: {Processed}/{Total} processed, {Failed} failures, {ImagesPerSecond:F2} img/s avg, workload {WorkloadLevel} ({WorkerCount} {ExecutionUnit})",
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summary.ProcessedFiles,
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summary.TotalFiles,
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summary.FailedFiles,
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summary.AverageImagesPerSecond,
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summary.WorkloadLevel,
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summary.WorkerCount);
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summary.WorkerCount,
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request.UseGpu ? "batch" : "workers");
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if (!string.IsNullOrWhiteSpace(request.CsvOutputPath))
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{
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@ -217,11 +239,11 @@ public class AiExtractionService : IAiExtractionService
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var requestedWorkers = useGpu
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? normalized switch
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{
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1 => 2,
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2 => 4,
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3 => 8,
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4 => 12,
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_ => 16
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1 => 4,
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2 => 8,
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3 => 16,
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4 => 24,
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_ => 32
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}
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: normalized switch
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{
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@ -232,7 +254,19 @@ public class AiExtractionService : IAiExtractionService
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_ => 5
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};
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return Math.Min(requestedWorkers, maxWorkers);
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return useGpu ? requestedWorkers : Math.Min(requestedWorkers, maxWorkers);
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}
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private sealed class SynchronousProgress<T> : IProgress<T>
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{
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private readonly Action<T> _handler;
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public SynchronousProgress(Action<T> handler)
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{
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_handler = handler;
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}
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public void Report(T value) => _handler(value);
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}
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private static ModelConfiguration BuildModelConfiguration(string modelsFolderPath, bool useGpu)
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@ -22,7 +22,8 @@ public sealed record AiExtractionProgressUpdate(
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double PercentComplete,
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double AverageImagesPerSecond,
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int WorkloadLevel,
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int WorkerCount);
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int WorkerCount,
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bool UseGpu);
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public sealed record AiExtractionRunSummary(
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int TotalFiles,
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@ -30,7 +31,8 @@ public sealed record AiExtractionRunSummary(
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int FailedFiles,
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double AverageImagesPerSecond,
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int WorkloadLevel,
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int WorkerCount);
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int WorkerCount,
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bool UseGpu);
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public interface IAiExtractionService
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{
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