364 lines
17 KiB
C#
364 lines
17 KiB
C#
using ShellProgressBar;
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using System.Text.Json;
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using View_by_Distance.Distance.Models.Stateless;
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using View_by_Distance.FaceRecognitionDotNet;
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using View_by_Distance.Shared.Models;
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namespace View_by_Distance.Distance.Models;
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public partial class E_Distance
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{
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private readonly List<string> _Moved;
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private readonly List<double?> _Debug;
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private readonly List<string> _Renamed;
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private readonly Serilog.ILogger? _Log;
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private readonly int _FaceConfidencePercent;
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private readonly bool _DistanceRenameToMatch;
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private readonly double[] _RangeFaceConfidence;
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private readonly bool _DistanceMoveUnableToMatch;
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private readonly List<string> _AllMappedFaceFiles;
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private readonly double[] _RangeDistanceTolerance;
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private readonly List<string> _AllMappedFaceFileNames;
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private readonly List<string> _DuplicateMappedFaceFiles;
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public E_Distance(bool distanceMoveUnableToMatch, bool distanceRenameToMatch, int faceConfidencePercent, double[] rangeDistanceTolerance, double[] rangeFaceConfidence)
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{
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_Debug = new();
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_Moved = new();
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_Renamed = new();
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_AllMappedFaceFiles = new();
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_AllMappedFaceFileNames = new();
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_DuplicateMappedFaceFiles = new();
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_RangeFaceConfidence = rangeFaceConfidence;
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_Log = Serilog.Log.ForContext<E_Distance>();
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_DistanceRenameToMatch = distanceRenameToMatch;
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_FaceConfidencePercent = faceConfidencePercent;
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_RangeDistanceTolerance = rangeDistanceTolerance;
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_DistanceMoveUnableToMatch = distanceMoveUnableToMatch;
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}
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private static void MoveUnableToMatch(string file)
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{
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string checkFile = string.Concat(file, ".unk");
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if (File.Exists(file) && !File.Exists(checkFile))
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File.Move(file, checkFile);
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}
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private FaceDistanceContainer[] GetFaceDistanceContainers(MappingFromItem mappingFromItem, List<Face> intersectFaces)
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{
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FaceDistanceContainer[] results;
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int confidencePercent;
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int normalizedRectangle;
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FaceDistance faceDistance;
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FaceDistanceContainer faceDistanceContainer;
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List<FaceDistanceContainer> collection = new();
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foreach (Face face in intersectFaces)
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{
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if (face.FaceEncoding is null || face.Location is null || face.OutputResolution is null)
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throw new NotSupportedException();
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confidencePercent = Shared.Models.Stateless.Methods.ILocation.GetConfidencePercent(_FaceConfidencePercent, _RangeFaceConfidence, face.Location.Confidence);
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normalizedRectangle = Shared.Models.Stateless.Methods.ILocation.GetNormalizedRectangle(face.Location, Shared.Models.Stateless.ILocation.Digits, face.OutputResolution);
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if (face.FaceDistance?.Encoding is not null && face.FaceDistance.Encoding is FaceRecognitionDotNet.FaceEncoding faceEncoding)
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faceDistance = new(confidencePercent, faceEncoding, mappingFromItem.Id, mappingFromItem.IsWrongYear, mappingFromItem.MinimumDateTime, normalizedRectangle);
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else
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{
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faceEncoding = FaceRecognition.LoadFaceEncoding(face.FaceEncoding.RawEncoding);
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faceDistance = new(confidencePercent, faceEncoding, mappingFromItem.Id, mappingFromItem.IsWrongYear, mappingFromItem.MinimumDateTime, normalizedRectangle);
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lock (intersectFaces)
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face.SetFaceDistance(faceDistance);
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}
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faceDistanceContainer = new(face, faceDistance);
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collection.Add(faceDistanceContainer);
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}
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results = collection.ToArray();
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return results;
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}
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private static List<FaceDistance> GetFaceDistanceEncodings(FaceDistanceContainer[] faceDistanceContainers)
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{
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List<FaceDistance> faceDistanceEncodings = new();
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foreach (FaceDistanceContainer faceDistanceContainer in faceDistanceContainers)
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{
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if (faceDistanceContainer.FaceDistance.Encoding is null)
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continue;
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faceDistanceEncodings.Add(faceDistanceContainer.FaceDistance);
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}
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return faceDistanceEncodings;
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}
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private List<(Face Face, double? Length)> GetValues(MappingFromItem mappingFromItem, List<Face> intersectFaces, Shared.Models.FaceEncoding modelsFaceEncoding)
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{
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List<(Face Face, double? Length)> results = new();
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Face face;
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FaceDistance faceDistanceLength;
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FaceRecognitionDotNet.FaceEncoding faceRecognitionDotNetFaceEncoding = FaceRecognition.LoadFaceEncoding(modelsFaceEncoding.RawEncoding);
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FaceDistance faceDistanceEncoding = new(faceRecognitionDotNetFaceEncoding);
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FaceDistanceContainer[] faceDistanceContainers = GetFaceDistanceContainers(mappingFromItem, intersectFaces);
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int faceDistanceContainersLength = faceDistanceContainers.Length;
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if (faceDistanceContainersLength != intersectFaces.Count)
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throw new NotSupportedException();
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List<FaceDistance> faceDistanceEncodings = GetFaceDistanceEncodings(faceDistanceContainers);
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if (faceDistanceEncodings.Count != intersectFaces.Count)
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throw new NotSupportedException();
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List<FaceDistance> faceDistanceLengths = FaceRecognition.FaceDistances(faceDistanceEncodings, faceDistanceEncoding);
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if (faceDistanceLengths.Count != faceDistanceContainersLength)
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throw new NotSupportedException();
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for (int i = 0; i < intersectFaces.Count; i++)
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{
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face = intersectFaces[i];
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faceDistanceLength = faceDistanceLengths[i];
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if (faceDistanceLength.Length is null)
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throw new NotSupportedException();
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results.Add(new(face, faceDistanceLength.Length.Value));
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}
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return results;
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}
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private (Face, double?)[] GetClosestFaceByDistanceIgnoringTolerance(MappingFromItem mappingFromItem, List<Face> intersectFaces, Shared.Models.FaceEncoding modelsFaceEncoding)
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{
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(Face, double?)[] results;
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List<(Face Face, double? Length)> collection = GetValues(mappingFromItem, intersectFaces, modelsFaceEncoding);
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results = (from l in collection orderby l.Length select l).Take(1).ToArray();
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if (results.Any())
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{
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(Face _, double? length) = results.First();
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_Debug.Add(length);
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}
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return results;
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}
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private static List<(Face, double?)> GetMatchingFacesByFaceEncoding(Face[] filteredFaces, string? json)
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{
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List<(Face, double?)> results = new();
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string check;
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foreach (Face face in filteredFaces)
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{
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if (json is null || face.FaceEncoding is null)
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continue;
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if (!json.Contains(face.FaceEncoding.RawEncoding[0].ToString()))
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continue;
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check = JsonSerializer.Serialize(face.FaceEncoding);
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if (check != json)
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continue;
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results.Add(new(face, 0));
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}
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return results;
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}
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private static FileInfo? CheckFileThenGetFileInfo(string facesFileNameExtension, MappingFromItem mappingFromItem, string file, List<(Face, double?)> checkFaces)
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{
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FileInfo? result = null;
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string checkFile;
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string? mappedFaceDirectory;
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string deterministicHashCodeKey;
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foreach ((Face face, _) in checkFaces)
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{
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if (checkFaces.Count != 1)
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break;
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if (face.FaceEncoding is null || face.Location is null || face.OutputResolution is null)
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throw new NotSupportedException();
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mappedFaceDirectory = Path.GetDirectoryName(file);
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if (mappedFaceDirectory is null)
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throw new NotSupportedException();
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deterministicHashCodeKey = Shared.Models.Stateless.Methods.IMapping.GetDeterministicHashCodeKey(mappingFromItem.Id, face.Location, Shared.Models.Stateless.ILocation.Digits, face.OutputResolution);
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checkFile = Path.Combine(mappedFaceDirectory, $"{deterministicHashCodeKey}{mappingFromItem.ImageFileHolder.ExtensionLowered}{facesFileNameExtension}");
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if (checkFile == file)
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continue;
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result = new FileInfo(checkFile);
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}
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return result;
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}
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private void AppendMatchingDuplicates(string file, string[] matches)
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{
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string checkFile;
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FileInfo fileInfo = new(file);
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List<(long Length, string FullName)> collection = new();
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if (fileInfo.Exists)
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collection.Add(new(fileInfo.Length, fileInfo.FullName));
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lock (_DuplicateMappedFaceFiles)
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_DuplicateMappedFaceFiles.Add(file);
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foreach (string match in matches)
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{
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fileInfo = new(match);
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if (!fileInfo.Exists)
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continue;
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collection.Add(new(fileInfo.Length, fileInfo.FullName));
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break;
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}
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collection = collection.OrderBy(l => l.Length).ToList();
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for (int i = 0; i < collection.Count - 1; i++)
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{
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checkFile = string.Concat(collection[i].FullName, ".dup");
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if (File.Exists(checkFile))
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continue;
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File.Move(collection[i].FullName, checkFile);
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}
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}
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public void LookForMatchFacesAndPossiblyRename(string facesFileNameExtension, string eDistanceContentDirectory, MappingFromItem mappingFromItem, List<Face> faces, List<LocationContainer<MetadataExtractor.Directory>> collection)
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{
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string? json;
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string fileName;
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string[] matches;
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FileInfo? fileInfo;
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List<Face> intersectFaces;
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List<(Face, double?)> checkFaces = new();
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Shared.Models.FaceEncoding? modelsFaceEncoding;
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Face[] filteredFaces = (from l in faces where l.FaceEncoding is not null && l.Location is not null && l.OutputResolution is not null select l).ToArray();
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if (filteredFaces.Length != faces.Count)
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checkFaces.Clear();
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foreach (LocationContainer<MetadataExtractor.Directory>? locationContainer in collection)
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{
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if (_Renamed.Contains(locationContainer.File))
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continue;
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fileName = Path.GetFileName(locationContainer.File);
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if (locationContainer.FromDistanceContent && _DuplicateMappedFaceFiles.Contains(fileName))
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continue;
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checkFaces.Clear();
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if (!locationContainer.Directories.Any())
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{
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if (locationContainer.FromDistanceContent)
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throw new NullReferenceException(nameof(locationContainer.Directories));
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continue;
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}
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json = Metadata.Models.Stateless.IMetadata.GetFaceEncoding(locationContainer.Directories);
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if (json is null)
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{
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if (_DistanceMoveUnableToMatch)
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MoveUnableToMatch(locationContainer.File);
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continue;
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}
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if (filteredFaces.Any())
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checkFaces.AddRange(GetMatchingFacesByFaceEncoding(filteredFaces, json));
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if (checkFaces.Count == 1)
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_Debug.Add(0);
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if (checkFaces.Count != 1 && !string.IsNullOrEmpty(json))
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{
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checkFaces.Clear();
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modelsFaceEncoding = JsonSerializer.Deserialize<Shared.Models.FaceEncoding>(json);
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if (modelsFaceEncoding is null)
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throw new NotSupportedException();
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if (filteredFaces.Any())
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{
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intersectFaces = Shared.Models.Stateless.Methods.ILocation.FilterByIntersect(filteredFaces, locationContainer.NormalizedRectangle);
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if (intersectFaces.Any())
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checkFaces.AddRange(GetClosestFaceByDistanceIgnoringTolerance(mappingFromItem, intersectFaces, modelsFaceEncoding));
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}
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}
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if (!checkFaces.Any())
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{
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if (_DistanceMoveUnableToMatch)
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MoveUnableToMatch(locationContainer.File);
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continue;
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}
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if (checkFaces.Count != 1)
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{
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if (_DistanceMoveUnableToMatch)
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MoveUnableToMatch(locationContainer.File);
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continue;
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}
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fileInfo = CheckFileThenGetFileInfo(facesFileNameExtension, mappingFromItem, locationContainer.File, checkFaces);
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if (fileInfo is not null)
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{
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if (_DistanceRenameToMatch && fileInfo is not null)
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{
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if (fileInfo.Exists)
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File.Delete(locationContainer.File);
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else
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File.Move(locationContainer.File, fileInfo.FullName);
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_Renamed.Add(locationContainer.File);
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}
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continue;
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}
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if (_AllMappedFaceFileNames.Contains(fileName))
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{
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lock (_AllMappedFaceFiles)
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matches = (from l in _AllMappedFaceFiles where l != locationContainer.File && Path.GetFileName(l) == fileName select l).ToArray();
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if (locationContainer.FromDistanceContent && matches.Any())
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AppendMatchingDuplicates(locationContainer.File, matches);
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}
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if (!locationContainer.FromDistanceContent)
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continue;
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lock (_AllMappedFaceFiles)
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_AllMappedFaceFiles.Add(locationContainer.File);
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lock (_AllMappedFaceFileNames)
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_AllMappedFaceFileNames.Add(fileName);
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}
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}
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public void Clear()
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{
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if (_Log is null)
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throw new NullReferenceException(nameof(_Log));
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double?[] debug = (from l in _Debug where l is null or not 0 select l).ToArray();
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if (debug.Any())
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{
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string debugMessage = $"{_Debug.Count - debug.Length} - {debug.Min()} - {_Debug.Max()}";
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_Log.Info(debugMessage);
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}
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if (_Moved.Any() || _Renamed.Any() || _DuplicateMappedFaceFiles.Any())
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throw new NotImplementedException("Restart!");
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_Debug.Clear();
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_Moved.Clear();
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_Renamed.Clear();
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_AllMappedFaceFiles.Clear();
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_AllMappedFaceFileNames.Clear();
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_DuplicateMappedFaceFiles.Clear();
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}
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public List<FaceDistanceContainer> GetMissingFaceDistanceContainer(int maxDegreeOfParallelism, long ticks, string dFacesCollectionDirectory, Dictionary<int, Dictionary<int, PersonContainer[]>> missingIdThenNormalizedRectangleToPersonContainers)
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{
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List<FaceDistanceContainer> results = new();
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string[] files;
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List<Face>? faces;
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int confidencePercent;
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int normalizedRectangle;
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bool? isWrongYear = null;
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FaceDistance faceDistance;
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List<(int id, string json)> collection = new();
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FaceDistanceContainer faceDistanceContainer;
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foreach (KeyValuePair<int, Dictionary<int, PersonContainer[]>> keyValuePair in missingIdThenNormalizedRectangleToPersonContainers)
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{
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files = Directory.GetFiles(dFacesCollectionDirectory, $"{keyValuePair.Key}*.json", SearchOption.TopDirectoryOnly);
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if (files.Length != 1)
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continue;
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collection.Add(new(keyValuePair.Key, Shared.Models.Stateless.Methods.IFace.GetJson(files[0])));
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}
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int totalSeconds = (int)Math.Floor(new TimeSpan(DateTime.Now.Ticks - ticks).TotalSeconds);
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ParallelOptions parallelOptions = new() { MaxDegreeOfParallelism = maxDegreeOfParallelism };
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string message = $") {collection.Count:000} Setting missing distance containers - {totalSeconds} total second(s)";
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ProgressBarOptions options = new() { ProgressCharacter = '─', ProgressBarOnBottom = true, DisableBottomPercentage = true };
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using ProgressBar progressBar = new(collection.Count, message, options);
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_ = Parallel.For(0, collection.Count, parallelOptions, (i, state) =>
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{
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progressBar.Tick();
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int id = collection[i].id;
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string json = collection[i].json;
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faces = JsonSerializer.Deserialize<List<Face>>(json);
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if (faces is null)
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throw new NullReferenceException(nameof(faces));
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foreach (Face face in faces)
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{
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if (face.FaceEncoding is null || face.Location is null || face.OutputResolution is null)
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continue;
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confidencePercent = Shared.Models.Stateless.Methods.ILocation.GetConfidencePercent(_FaceConfidencePercent, _RangeFaceConfidence, face.Location.Confidence);
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normalizedRectangle = Shared.Models.Stateless.Methods.ILocation.GetNormalizedRectangle(face.Location, Shared.Models.Stateless.ILocation.Digits, face.OutputResolution);
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if (face.FaceDistance?.Encoding is not null && face.FaceDistance.Encoding is FaceRecognitionDotNet.FaceEncoding faceEncoding)
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faceDistance = new(confidencePercent, faceEncoding, id, isWrongYear, face.DateTime, normalizedRectangle);
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else
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{
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faceEncoding = FaceRecognition.LoadFaceEncoding(face.FaceEncoding.RawEncoding);
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faceDistance = new(confidencePercent, faceEncoding, id, isWrongYear, face.DateTime, normalizedRectangle);
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face.SetFaceDistance(faceDistance);
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}
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faceDistanceContainer = new(face, faceDistance);
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lock (results)
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results.Add(faceDistanceContainer);
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}
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});
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return results;
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}
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} |