Add GPU validation and configuration support in NumberRecognitionEngine

- Changed the repository URL in the AIFotoONLUS.Core project file to point to the new Forgejo instance.
- Removed the inclusion of the XML documentation file in the NuGet package.
- Added a new CSV file containing test data for image processing, including filenames and associated text values.

.forgejo/workflows/publish-aifotoonlus-core.yml

@@ -0,0 +1,124 @@
+name: Build And Publish AIFotoONLUS.Core
+
+on:
+  push:
+    branches:
+      - master
+      - develop
+    tags:
+      - '*'
+  workflow_dispatch:
+
+env:
+  DOTNET_VERSION: 10.0.x
+  PROJECT_PATH: src/AIFotoONLUS.Core/AIFotoONLUS.Core.csproj
+  PACKAGE_OUTPUT_DIR: artifacts/nuget
+  PACKAGE_ARTIFACT_NAME: aifotoonlus-core-nuget
+  NUGET_SOURCE_NAME: forgejo-aifotoonlus
+  NUGET_SOURCE_URL: ${{ vars.AIFOTOONLUS_NUGET_SOURCE_URL || format('{0}/api/packages/{1}/nuget/index.json', github.server_url, vars.AIFOTOONLUS_PACKAGE_OWNER || github.repository_owner) }}
+
+jobs:
+  build:
+    runs-on: docker
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - name: Setup .NET
+        uses: actions/setup-dotnet@v4
+        with:
+          dotnet-version: ${{ env.DOTNET_VERSION }}
+
+      - name: Restore
+        run: dotnet restore "${{ env.PROJECT_PATH }}"
+
+      - name: Build
+        run: dotnet build "${{ env.PROJECT_PATH }}" --configuration Release --no-restore /p:GeneratePackageOnBuild=false
+
+      - name: Pack
+        shell: bash
+        run: |
+          set -eu
+          mkdir -p "${{ env.PACKAGE_OUTPUT_DIR }}"
+
+          if [[ "${GITHUB_REF}" == refs/tags/* ]]; then
+            package_version="${GITHUB_REF_NAME#v}"
+            echo "Packing tag version ${package_version}"
+            dotnet pack "${{ env.PROJECT_PATH }}" \
+              --configuration Release \
+              --output "${{ env.PACKAGE_OUTPUT_DIR }}" \
+              --no-build \
+              /p:PackageVersion="${package_version}"
+          else
+            echo "Packing with project version or MinVer-derived version"
+            dotnet pack "${{ env.PROJECT_PATH }}" \
+              --configuration Release \
+              --output "${{ env.PACKAGE_OUTPUT_DIR }}" \
+              --no-build
+          fi
+
+      - name: Upload package artifact
+        uses: actions/upload-artifact@v3
+        with:
+          name: ${{ env.PACKAGE_ARTIFACT_NAME }}
+          path: ${{ env.PACKAGE_OUTPUT_DIR }}/*.nupkg
+          if-no-files-found: error
+
+  publish:
+    if: startsWith(github.ref, 'refs/tags/') || github.event_name == 'workflow_dispatch'
+    needs: build
+    runs-on: docker
+    env:
+      FORGEJO_PACKAGE_USERNAME: ${{ secrets.FORGEJO_PACKAGE_USERNAME }}
+      FORGEJO_PACKAGE_TOKEN: ${{ secrets.FORGEJO_PACKAGE_TOKEN }}
+
+    steps:
+      - name: Setup .NET
+        uses: actions/setup-dotnet@v4
+        with:
+          dotnet-version: ${{ env.DOTNET_VERSION }}
+
+      - name: Download package artifact
+        uses: actions/download-artifact@v3
+        with:
+          name: ${{ env.PACKAGE_ARTIFACT_NAME }}
+          path: ${{ env.PACKAGE_OUTPUT_DIR }}
+
+      - name: Validate publish secrets
+        shell: bash
+        run: |
+          set -eu
+          if [ -z "${FORGEJO_PACKAGE_USERNAME}" ]; then
+            echo "secrets.FORGEJO_PACKAGE_USERNAME is required"
+            exit 1
+          fi
+          if [ -z "${FORGEJO_PACKAGE_TOKEN}" ]; then
+            echo "secrets.FORGEJO_PACKAGE_TOKEN is required"
+            exit 1
+          fi
+
+      - name: Configure Forgejo NuGet source
+        run: |
+          dotnet nuget add source "${{ env.NUGET_SOURCE_URL }}" \
+            --name "${{ env.NUGET_SOURCE_NAME }}" \
+            --username "${FORGEJO_PACKAGE_USERNAME}" \
+            --password "${FORGEJO_PACKAGE_TOKEN}" \
+            --store-password-in-clear-text
+
+      - name: Publish package to Forgejo NuGet
+        shell: bash
+        run: |
+          set -eu
+          shopt -s nullglob
+          packages=("${{ env.PACKAGE_OUTPUT_DIR }}"/*.nupkg)
+          if [ "${#packages[@]}" -eq 0 ]; then
+            echo "No NuGet packages found in ${{ env.PACKAGE_OUTPUT_DIR }}"
+            exit 1
+          fi
+
+          dotnet nuget push "${{ env.PACKAGE_OUTPUT_DIR }}"/*.nupkg \
+            --source "${{ env.NUGET_SOURCE_NAME }}" \
+            --skip-duplicate

gitversion.json

@@ -0,0 +1,27 @@
+{
+  "AssemblySemFileVer": "0.1.0.0",
+  "AssemblySemVer": "0.1.0.0",
+  "BranchName": "master",
+  "BuildMetaData": null,
+  "CommitDate": "2026-02-15",
+  "CommitsSinceVersionSource": 11,
+  "EscapedBranchName": "master",
+  "FullBuildMetaData": "Branch.master.Sha.a90da31e531332a4cf0bafe604f89d0e14f3395a",
+  "FullSemVer": "0.1.0-{BranchName}.11",
+  "InformationalVersion": "0.1.0-{BranchName}.11+Branch.master.Sha.a90da31e531332a4cf0bafe604f89d0e14f3395a",
+  "Major": 0,
+  "MajorMinorPatch": "0.1.0",
+  "Minor": 1,
+  "Patch": 0,
+  "PreReleaseLabel": "{BranchName}",
+  "PreReleaseLabelWithDash": "-{BranchName}",
+  "PreReleaseNumber": 11,
+  "PreReleaseTag": "{BranchName}.11",
+  "PreReleaseTagWithDash": "-{BranchName}.11",
+  "SemVer": "0.1.0-{BranchName}.11",
+  "Sha": "a90da31e531332a4cf0bafe604f89d0e14f3395a",
+  "ShortSha": "a90da31",
+  "UncommittedChanges": 7,
+  "VersionSourceSha": "",
+  "WeightedPreReleaseNumber": 11
+}

src/AIFotoONLUS.Core/AIFotoONLUS.Core.csproj

@@ -8,22 +8,13 @@
     <!-- Ensure the documentation file path is predictable so it can be packed -->
     <DocumentationFile>$(OutputPath)$(AssemblyName).xml</DocumentationFile>
   </PropertyGroup>
-  <!-- Include the generated XML documentation in the produced NuGet package
-       next to the assembly under the lib/<tfm>/ folder. This guarantees the
-       consumers installing the package will receive IntelliSense XML docs. -->
-  <ItemGroup>
-    <None Include="$(OutputPath)$(AssemblyName).xml">
-      <Pack>true</Pack>
-      <PackagePath>lib\$(TargetFramework)\</PackagePath>
-    </None>
-  </ItemGroup>
   <PropertyGroup>
     <!-- NuGet package metadata -->
     <PackageId>AIFotoONLUS.Core</PackageId>
     <Authors>Maddo</Authors>
     <Company>Maddo</Company>
     <Description>Core library for AIFotoONLUS image processing and recognition.</Description>
-    <RepositoryUrl>https://gitlab.com/MaddoScientisto/aifotoonlus</RepositoryUrl>
+    <RepositoryUrl>https://forgejo.maddoscientisto.net/maddo/AIFotoONLUS</RepositoryUrl>
         <!-- Versioning: use MinVer to infer semantic versions from Git tags. When no tag is present,
           projects will fall back to the default below. -->
         <Version>0.1.0</Version>

src/AIFotoONLUS.Core/AIFotoONLUS.Core.xml

@@ -139,6 +139,12 @@
             must match the class ordering used by the trained recognition network.
             </summary>
         </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">
             <summary>
             When enabled, recognition crops will be saved to disk under

src/AIFotoONLUS.Core/ModelConfiguration.cs

@@ -55,6 +55,12 @@ namespace AIFotoONLUS.Core
         /// </summary>
         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>
         /// When enabled, recognition crops will be saved to disk under
         /// "logs/crops" for diagnostic inspection. Disabled by default.

src/AIFotoONLUS.Core/NumberRecognitionEngine.cs

@@ -95,10 +95,8 @@ namespace AIFotoONLUS.Core
             _detectionNet = CvDnn.ReadNetFromDarknet(_cfg.DetectionCfg, _cfg.DetectionWeights);
             _recognitionNet = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
 
-            _detectionNet.SetPreferableBackend(Backend.OPENCV);
-            _detectionNet.SetPreferableTarget(Target.CPU);
-            _recognitionNet.SetPreferableBackend(Backend.OPENCV);
-            _recognitionNet.SetPreferableTarget(Target.CPU);
+            ConfigureNetRuntime(_detectionNet, _cfg.UseGpu);
+            ConfigureNetRuntime(_recognitionNet, _cfg.UseGpu);
             // Let OpenCV use multiple threads internally (use number of logical processors)
             try
             {
@@ -108,6 +106,11 @@ namespace AIFotoONLUS.Core
             {
                 // Ignore if not supported by OpenCvSharp build
             }
+
+            if (_cfg.UseGpu)
+            {
+                ValidateGpuRuntime();
+            }
         }
 
         public void Dispose()
@@ -119,6 +122,38 @@ namespace AIFotoONLUS.Core
             GC.SuppressFinalize(this);
         }
 
+        public static bool TryValidateGpuRuntime(ModelConfiguration cfg, ILogger? logger, out string? failureMessage)
+        {
+            if (cfg is null) throw new ArgumentNullException(nameof(cfg));
+
+            var probeConfiguration = new ModelConfiguration
+            {
+                DetectionCfg = cfg.DetectionCfg,
+                DetectionWeights = cfg.DetectionWeights,
+                RecognitionCfg = cfg.RecognitionCfg,
+                RecognitionWeights = cfg.RecognitionWeights,
+                ConfidenceThreshold = cfg.ConfidenceThreshold,
+                NmsThreshold = cfg.NmsThreshold,
+                DetectionInputSize = cfg.DetectionInputSize,
+                RecognitionInputSize = cfg.RecognitionInputSize,
+                NumberClasses = cfg.NumberClasses,
+                EnableCropSaving = cfg.EnableCropSaving,
+                UseGpu = true
+            };
+
+            try
+            {
+                using var engine = new NumberRecognitionEngine(probeConfiguration, logger);
+                failureMessage = null;
+                return true;
+            }
+            catch (Exception ex)
+            {
+                failureMessage = ex.GetBaseException().Message;
+                return false;
+            }
+        }
+
         private static string SanitizeFileName(string name)
         {
             foreach (var c in Path.GetInvalidFileNameChars()) name = name.Replace(c, '_');
@@ -127,6 +162,39 @@ namespace AIFotoONLUS.Core
 
         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);
+        }
+
+        private void ValidateGpuRuntime()
+        {
+            try
+            {
+                using var detectionProbe = new Mat(_cfg.DetectionInputSize.Height, _cfg.DetectionInputSize.Width, MatType.CV_8UC3, Scalar.All(0));
+                _ = DetectTextRegions(_detectionNet, detectionProbe).Take(1).ToArray();
+
+                using var recognitionProbe = new Mat(_cfg.RecognitionInputSize.Height, _cfg.RecognitionInputSize.Width, MatType.CV_8UC3, Scalar.All(0));
+                using var blob = CvDnn.BlobFromImage(recognitionProbe, 0.00392, _cfg.RecognitionInputSize, new Scalar(0, 0, 0), true, false);
+                _recognitionNet.SetInput(blob);
+                using var output = _recognitionNet.Forward();
+            }
+            catch (Exception ex)
+            {
+                throw new InvalidOperationException(
+                    "OpenCV DNN CUDA runtime validation failed. Disable number AI GPU mode or use an OpenCV runtime built with CUDA DNN support.",
+                    ex);
+            }
+        }
+
         /// <summary>
         /// Detect text regions in the supplied image using the detection network.
         /// </summary>
@@ -152,7 +220,7 @@ namespace AIFotoONLUS.Core
             var outNames = GetOutputLayerNames(detectionNet);
             var outsList = new List<Mat>();
             detectionNet.Forward(outsList, outNames);
-            
+
             Mat[] outs = outsList.ToArray();
             if (outs.Length == 0)
             {
@@ -162,15 +230,15 @@ namespace AIFotoONLUS.Core
                     var fallback = new List<Mat>();
                     for (int on = 0; on < outNames.Length; on++)
                     {
-                            try
-                            {
-                                var single = detectionNet.Forward(outNames[on]);
-                                fallback.Add(single);
-                            }
-                            catch (Exception ex)
-                            {
-                                _logger?.LogError(ex, "Fallback Forward failed for {name}", outNames[on]);
-                            }
+                        try
+                        {
+                            var single = detectionNet.Forward(outNames[on]);
+                            fallback.Add(single);
+                        }
+                        catch (Exception ex)
+                        {
+                            _logger?.LogError(ex, "Fallback Forward failed for {name}", outNames[on]);
+                        }
                     }
                     if (fallback.Count > 0)
                     {
@@ -221,21 +289,21 @@ namespace AIFotoONLUS.Core
                     }
 
                     if (maxScore > _cfg.ConfidenceThreshold)
-                        {
-                            int x = (int)Math.Max(0, Math.Round(cx - w / 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));
-                            boxes.Add(rect);
-                            confidences.Add(maxScore);
-                            classIds.Add(bestClass);
-                            centerXList.Add(cx);
-                        }
+                    {
+                        int x = (int)Math.Max(0, Math.Round(cx - w / 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));
+                        boxes.Add(rect);
+                        confidences.Add(maxScore);
+                        classIds.Add(bestClass);
+                        centerXList.Add(cx);
+                    }
                 }
             }
 
             if (boxes.Count == 0) return Enumerable.Empty<DetectedRegion>();
 
-            
+
 
             CvDnn.NMSBoxes(boxes, confidences, (float)_cfg.ConfidenceThreshold, (float)_cfg.NmsThreshold, out int[] indices);
 
@@ -486,10 +554,8 @@ namespace AIFotoONLUS.Core
             {
                 var det = CvDnn.ReadNetFromDarknet(_cfg.DetectionCfg, _cfg.DetectionWeights);
                 var rec = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
-                det.SetPreferableBackend(Backend.OPENCV);
-                det.SetPreferableTarget(Target.CPU);
-                rec.SetPreferableBackend(Backend.OPENCV);
-                rec.SetPreferableTarget(Target.CPU);
+                ConfigureNetRuntime(det, _cfg.UseGpu);
+                ConfigureNetRuntime(rec, _cfg.UseGpu);
                 netsBag.Add((det, rec));
                 return (det, rec);
             });
@@ -525,8 +591,7 @@ namespace AIFotoONLUS.Core
                                     try
                                     {
                                         using var tempRec = CvDnn.ReadNetFromDarknet(_cfg.RecognitionCfg, _cfg.RecognitionWeights);
-                                        tempRec.SetPreferableBackend(Backend.OPENCV);
-                                        tempRec.SetPreferableTarget(Target.CPU);
+                                        ConfigureNetRuntime(tempRec, _cfg.UseGpu);
                                         var alt = RecognizeDigits(crop, tempRec, ctx);
                                         if (!string.IsNullOrEmpty(alt)) txt = alt;
                                     }