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2 commits
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44af20ead5
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| 44af20ead5 | |||
| f4f8a58646 |
3 changed files with 107 additions and 30 deletions
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@ -139,6 +139,12 @@
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must match the class ordering used by the trained recognition network.
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must match the class ordering used by the trained recognition network.
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</summary>
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</summary>
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</member>
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</member>
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<member name="P:AIFotoONLUS.Core.ModelConfiguration.UseGpu">
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<summary>
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When enabled, request OpenCV DNN CUDA backend/target for inference.
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The installed OpenCV runtime must have CUDA support or model loading/forwarding may fail.
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</summary>
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</member>
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<member name="P:AIFotoONLUS.Core.ModelConfiguration.EnableCropSaving">
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<member name="P:AIFotoONLUS.Core.ModelConfiguration.EnableCropSaving">
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<summary>
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<summary>
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When enabled, recognition crops will be saved to disk under
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When enabled, recognition crops will be saved to disk under
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@ -55,6 +55,12 @@ namespace AIFotoONLUS.Core
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/// </summary>
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/// </summary>
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public string[] NumberClasses { get; set; } = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" };
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public string[] NumberClasses { get; set; } = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" };
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/// <summary>
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/// When enabled, request OpenCV DNN CUDA backend/target for inference.
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/// The installed OpenCV runtime must have CUDA support or model loading/forwarding may fail.
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/// </summary>
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public bool UseGpu { get; set; } = false;
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/// <summary>
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/// <summary>
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/// When enabled, recognition crops will be saved to disk under
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/// When enabled, recognition crops will be saved to disk under
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/// "logs/crops" for diagnostic inspection. Disabled by default.
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/// "logs/crops" for diagnostic inspection. Disabled by default.
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@ -95,10 +95,8 @@ namespace AIFotoONLUS.Core
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_detectionNet = CvDnn.ReadNetFromDarknet(_cfg.DetectionCfg, _cfg.DetectionWeights);
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_detectionNet = CvDnn.ReadNetFromDarknet(_cfg.DetectionCfg, _cfg.DetectionWeights);
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_recognitionNet = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
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_recognitionNet = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
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_detectionNet.SetPreferableBackend(Backend.OPENCV);
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ConfigureNetRuntime(_detectionNet, _cfg.UseGpu);
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_detectionNet.SetPreferableTarget(Target.CPU);
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ConfigureNetRuntime(_recognitionNet, _cfg.UseGpu);
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_recognitionNet.SetPreferableBackend(Backend.OPENCV);
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_recognitionNet.SetPreferableTarget(Target.CPU);
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// Let OpenCV use multiple threads internally (use number of logical processors)
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// Let OpenCV use multiple threads internally (use number of logical processors)
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try
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try
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{
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{
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@ -108,6 +106,11 @@ namespace AIFotoONLUS.Core
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{
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{
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// Ignore if not supported by OpenCvSharp build
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// Ignore if not supported by OpenCvSharp build
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}
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}
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if (_cfg.UseGpu)
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{
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ValidateGpuRuntime();
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}
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}
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}
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public void Dispose()
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public void Dispose()
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@ -119,6 +122,38 @@ namespace AIFotoONLUS.Core
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GC.SuppressFinalize(this);
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GC.SuppressFinalize(this);
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}
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}
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public static bool TryValidateGpuRuntime(ModelConfiguration cfg, ILogger? logger, out string? failureMessage)
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{
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if (cfg is null) throw new ArgumentNullException(nameof(cfg));
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var probeConfiguration = new ModelConfiguration
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{
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DetectionCfg = cfg.DetectionCfg,
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DetectionWeights = cfg.DetectionWeights,
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RecognitionCfg = cfg.RecognitionCfg,
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RecognitionWeights = cfg.RecognitionWeights,
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ConfidenceThreshold = cfg.ConfidenceThreshold,
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NmsThreshold = cfg.NmsThreshold,
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DetectionInputSize = cfg.DetectionInputSize,
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RecognitionInputSize = cfg.RecognitionInputSize,
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NumberClasses = cfg.NumberClasses,
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EnableCropSaving = cfg.EnableCropSaving,
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UseGpu = true
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};
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try
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{
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using var engine = new NumberRecognitionEngine(probeConfiguration, logger);
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failureMessage = null;
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return true;
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}
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catch (Exception ex)
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{
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failureMessage = ex.GetBaseException().Message;
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return false;
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}
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}
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private static string SanitizeFileName(string name)
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private static string SanitizeFileName(string name)
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{
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{
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foreach (var c in Path.GetInvalidFileNameChars()) name = name.Replace(c, '_');
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foreach (var c in Path.GetInvalidFileNameChars()) name = name.Replace(c, '_');
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@ -127,6 +162,39 @@ namespace AIFotoONLUS.Core
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private string[] GetOutputLayerNames(Net net) => net.GetUnconnectedOutLayersNames();
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private string[] GetOutputLayerNames(Net net) => net.GetUnconnectedOutLayersNames();
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private static void ConfigureNetRuntime(Net net, bool useGpu)
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{
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if (useGpu)
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{
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net.SetPreferableBackend(Backend.CUDA);
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net.SetPreferableTarget(Target.CUDA);
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return;
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}
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net.SetPreferableBackend(Backend.OPENCV);
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net.SetPreferableTarget(Target.CPU);
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}
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private void ValidateGpuRuntime()
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{
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try
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{
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using var detectionProbe = new Mat(_cfg.DetectionInputSize.Height, _cfg.DetectionInputSize.Width, MatType.CV_8UC3, Scalar.All(0));
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_ = DetectTextRegions(_detectionNet, detectionProbe).Take(1).ToArray();
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using var recognitionProbe = new Mat(_cfg.RecognitionInputSize.Height, _cfg.RecognitionInputSize.Width, MatType.CV_8UC3, Scalar.All(0));
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using var blob = CvDnn.BlobFromImage(recognitionProbe, 0.00392, _cfg.RecognitionInputSize, new Scalar(0, 0, 0), true, false);
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_recognitionNet.SetInput(blob);
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using var output = _recognitionNet.Forward();
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}
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catch (Exception ex)
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{
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throw new InvalidOperationException(
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"OpenCV DNN CUDA runtime validation failed. Disable number AI GPU mode or use an OpenCV runtime built with CUDA DNN support.",
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ex);
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}
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}
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/// <summary>
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/// <summary>
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/// Detect text regions in the supplied image using the detection network.
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/// Detect text regions in the supplied image using the detection network.
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/// </summary>
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/// </summary>
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@ -152,7 +220,7 @@ namespace AIFotoONLUS.Core
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var outNames = GetOutputLayerNames(detectionNet);
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var outNames = GetOutputLayerNames(detectionNet);
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var outsList = new List<Mat>();
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var outsList = new List<Mat>();
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detectionNet.Forward(outsList, outNames);
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detectionNet.Forward(outsList, outNames);
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Mat[] outs = outsList.ToArray();
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Mat[] outs = outsList.ToArray();
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if (outs.Length == 0)
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if (outs.Length == 0)
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{
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{
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@ -162,15 +230,15 @@ namespace AIFotoONLUS.Core
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var fallback = new List<Mat>();
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var fallback = new List<Mat>();
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for (int on = 0; on < outNames.Length; on++)
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for (int on = 0; on < outNames.Length; on++)
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{
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{
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try
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try
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{
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{
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var single = detectionNet.Forward(outNames[on]);
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var single = detectionNet.Forward(outNames[on]);
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fallback.Add(single);
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fallback.Add(single);
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}
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}
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catch (Exception ex)
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catch (Exception ex)
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{
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{
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_logger?.LogError(ex, "Fallback Forward failed for {name}", outNames[on]);
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_logger?.LogError(ex, "Fallback Forward failed for {name}", outNames[on]);
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}
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}
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}
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}
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if (fallback.Count > 0)
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if (fallback.Count > 0)
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{
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{
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@ -221,21 +289,21 @@ namespace AIFotoONLUS.Core
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}
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}
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if (maxScore > _cfg.ConfidenceThreshold)
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if (maxScore > _cfg.ConfidenceThreshold)
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{
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{
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int x = (int)Math.Max(0, Math.Round(cx - w / 2));
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int x = (int)Math.Max(0, Math.Round(cx - w / 2));
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int y = (int)Math.Max(0, Math.Round(cy - h / 2));
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int y = (int)Math.Max(0, Math.Round(cy - h / 2));
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var rect = new Rect(x, y, (int)Math.Round(w), (int)Math.Round(h));
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var rect = new Rect(x, y, (int)Math.Round(w), (int)Math.Round(h));
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boxes.Add(rect);
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boxes.Add(rect);
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confidences.Add(maxScore);
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confidences.Add(maxScore);
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classIds.Add(bestClass);
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classIds.Add(bestClass);
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centerXList.Add(cx);
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centerXList.Add(cx);
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}
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}
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}
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}
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}
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}
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if (boxes.Count == 0) return Enumerable.Empty<DetectedRegion>();
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if (boxes.Count == 0) return Enumerable.Empty<DetectedRegion>();
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CvDnn.NMSBoxes(boxes, confidences, (float)_cfg.ConfidenceThreshold, (float)_cfg.NmsThreshold, out int[] indices);
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CvDnn.NMSBoxes(boxes, confidences, (float)_cfg.ConfidenceThreshold, (float)_cfg.NmsThreshold, out int[] indices);
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@ -486,10 +554,8 @@ namespace AIFotoONLUS.Core
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{
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{
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var det = CvDnn.ReadNetFromDarknet(_cfg.DetectionCfg, _cfg.DetectionWeights);
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var det = CvDnn.ReadNetFromDarknet(_cfg.DetectionCfg, _cfg.DetectionWeights);
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var rec = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
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var rec = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
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det.SetPreferableBackend(Backend.OPENCV);
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ConfigureNetRuntime(det, _cfg.UseGpu);
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det.SetPreferableTarget(Target.CPU);
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ConfigureNetRuntime(rec, _cfg.UseGpu);
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rec.SetPreferableBackend(Backend.OPENCV);
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rec.SetPreferableTarget(Target.CPU);
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netsBag.Add((det, rec));
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netsBag.Add((det, rec));
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return (det, rec);
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return (det, rec);
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});
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});
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try
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try
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{
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{
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using var tempRec = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
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using var tempRec = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
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tempRec.SetPreferableBackend(Backend.OPENCV);
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ConfigureNetRuntime(tempRec, _cfg.UseGpu);
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tempRec.SetPreferableTarget(Target.CPU);
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var alt = RecognizeDigits(crop, tempRec, ctx);
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var alt = RecognizeDigits(crop, tempRec, ctx);
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if (!string.IsNullOrEmpty(alt)) txt = alt;
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if (!string.IsNullOrEmpty(alt)) txt = alt;
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}
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}
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