Add UseGpu property to ModelConfiguration and update network runtime configuration

This commit is contained in:
MaddoScientisto 2026-05-09 17:29:56 +02:00
commit f4f8a58646
3 changed files with 50 additions and 30 deletions

View file

@ -139,6 +139,12 @@
must match the class ordering used by the trained recognition network. must match the class ordering used by the trained recognition network.
</summary> </summary>
</member> </member>
<member name="P:AIFotoONLUS.Core.ModelConfiguration.UseGpu">
<summary>
When enabled, request OpenCV DNN CUDA backend/target for inference.
The installed OpenCV runtime must have CUDA support or model loading/forwarding may fail.
</summary>
</member>
<member name="P:AIFotoONLUS.Core.ModelConfiguration.EnableCropSaving"> <member name="P:AIFotoONLUS.Core.ModelConfiguration.EnableCropSaving">
<summary> <summary>
When enabled, recognition crops will be saved to disk under When enabled, recognition crops will be saved to disk under

View file

@ -55,6 +55,12 @@ namespace AIFotoONLUS.Core
/// </summary> /// </summary>
public string[] NumberClasses { get; set; } = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" }; public string[] NumberClasses { get; set; } = new[] { "0", "1", "2", "3", "4", "5", "6", "7", "8", "9" };
/// <summary>
/// When enabled, request OpenCV DNN CUDA backend/target for inference.
/// The installed OpenCV runtime must have CUDA support or model loading/forwarding may fail.
/// </summary>
public bool UseGpu { get; set; } = false;
/// <summary> /// <summary>
/// When enabled, recognition crops will be saved to disk under /// When enabled, recognition crops will be saved to disk under
/// "logs/crops" for diagnostic inspection. Disabled by default. /// "logs/crops" for diagnostic inspection. Disabled by default.

View file

@ -95,10 +95,8 @@ namespace AIFotoONLUS.Core
_detectionNet = CvDnn.ReadNetFromDarknet(_cfg.DetectionCfg, _cfg.DetectionWeights); _detectionNet = CvDnn.ReadNetFromDarknet(_cfg.DetectionCfg, _cfg.DetectionWeights);
_recognitionNet = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights); _recognitionNet = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
_detectionNet.SetPreferableBackend(Backend.OPENCV); ConfigureNetRuntime(_detectionNet, _cfg.UseGpu);
_detectionNet.SetPreferableTarget(Target.CPU); ConfigureNetRuntime(_recognitionNet, _cfg.UseGpu);
_recognitionNet.SetPreferableBackend(Backend.OPENCV);
_recognitionNet.SetPreferableTarget(Target.CPU);
// Let OpenCV use multiple threads internally (use number of logical processors) // Let OpenCV use multiple threads internally (use number of logical processors)
try try
{ {
@ -127,6 +125,19 @@ namespace AIFotoONLUS.Core
private string[] GetOutputLayerNames(Net net) => net.GetUnconnectedOutLayersNames(); private string[] GetOutputLayerNames(Net net) => net.GetUnconnectedOutLayersNames();
private static void ConfigureNetRuntime(Net net, bool useGpu)
{
if (useGpu)
{
net.SetPreferableBackend(Backend.CUDA);
net.SetPreferableTarget(Target.CUDA);
return;
}
net.SetPreferableBackend(Backend.OPENCV);
net.SetPreferableTarget(Target.CPU);
}
/// <summary> /// <summary>
/// Detect text regions in the supplied image using the detection network. /// Detect text regions in the supplied image using the detection network.
/// </summary> /// </summary>
@ -162,15 +173,15 @@ namespace AIFotoONLUS.Core
var fallback = new List<Mat>(); var fallback = new List<Mat>();
for (int on = 0; on < outNames.Length; on++) for (int on = 0; on < outNames.Length; on++)
{ {
try try
{ {
var single = detectionNet.Forward(outNames[on]); var single = detectionNet.Forward(outNames[on]);
fallback.Add(single); fallback.Add(single);
} }
catch (Exception ex) catch (Exception ex)
{ {
_logger?.LogError(ex, "Fallback Forward failed for {name}", outNames[on]); _logger?.LogError(ex, "Fallback Forward failed for {name}", outNames[on]);
} }
} }
if (fallback.Count > 0) if (fallback.Count > 0)
{ {
@ -221,15 +232,15 @@ namespace AIFotoONLUS.Core
} }
if (maxScore > _cfg.ConfidenceThreshold) if (maxScore > _cfg.ConfidenceThreshold)
{ {
int x = (int)Math.Max(0, Math.Round(cx - w / 2)); int x = (int)Math.Max(0, Math.Round(cx - w / 2));
int y = (int)Math.Max(0, Math.Round(cy - h / 2)); int y = (int)Math.Max(0, Math.Round(cy - h / 2));
var rect = new Rect(x, y, (int)Math.Round(w), (int)Math.Round(h)); var rect = new Rect(x, y, (int)Math.Round(w), (int)Math.Round(h));
boxes.Add(rect); boxes.Add(rect);
confidences.Add(maxScore); confidences.Add(maxScore);
classIds.Add(bestClass); classIds.Add(bestClass);
centerXList.Add(cx); centerXList.Add(cx);
} }
} }
} }
@ -486,10 +497,8 @@ namespace AIFotoONLUS.Core
{ {
var det = CvDnn.ReadNetFromDarknet(_cfg.DetectionCfg, _cfg.DetectionWeights); var det = CvDnn.ReadNetFromDarknet(_cfg.DetectionCfg, _cfg.DetectionWeights);
var rec = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights); var rec = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
det.SetPreferableBackend(Backend.OPENCV); ConfigureNetRuntime(det, _cfg.UseGpu);
det.SetPreferableTarget(Target.CPU); ConfigureNetRuntime(rec, _cfg.UseGpu);
rec.SetPreferableBackend(Backend.OPENCV);
rec.SetPreferableTarget(Target.CPU);
netsBag.Add((det, rec)); netsBag.Add((det, rec));
return (det, rec); return (det, rec);
}); });
@ -525,8 +534,7 @@ namespace AIFotoONLUS.Core
try try
{ {
using var tempRec = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights); using var tempRec = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
tempRec.SetPreferableBackend(Backend.OPENCV); ConfigureNetRuntime(tempRec, _cfg.UseGpu);
tempRec.SetPreferableTarget(Target.CPU);
var alt = RecognizeDigits(crop, tempRec, ctx); var alt = RecognizeDigits(crop, tempRec, ctx);
if (!string.IsNullOrEmpty(alt)) txt = alt; if (!string.IsNullOrEmpty(alt)) txt = alt;
} }