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LabelImage.cs 4.4 kB

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  1. using ICSharpCode.SharpZipLib.GZip;
  2. using ICSharpCode.SharpZipLib.Tar;
  3. using NumSharp.Core;
  4. using System;
  5. using System.Collections.Generic;
  6. using System.IO;
  7. using System.Linq;
  8. using System.Net;
  9. using System.Text;
  10. using System.Threading;
  11. using System.Threading.Tasks;
  12. using Tensorflow;
  13. namespace TensorFlowNET.Examples
  14. {
  15. /// <summary>
  16. /// Port from tensorflow\examples\label_image\label_image.py
  17. /// </summary>
  18. public class LabelImage : Python, IExample
  19. {
  20. string dir = "label_image_data";
  21. string pbFile = "inception_v3_2016_08_28_frozen.pb";
  22. string labelFile = "imagenet_slim_labels.txt";
  23. string picFile = "grace_hopper.jpg";
  24. int input_height = 299;
  25. int input_width = 299;
  26. int input_mean = 0;
  27. int input_std = 255;
  28. string input_name = "import/input";
  29. string output_name = "import/InceptionV3/Predictions/Reshape_1";
  30. public void Run()
  31. {
  32. PrepareData();
  33. var labels = LoadLabels(Path.Join(dir, labelFile));
  34. var nd = ReadTensorFromImageFile(Path.Join(dir, picFile),
  35. input_height: input_height,
  36. input_width: input_width,
  37. input_mean: input_mean,
  38. input_std: input_std);
  39. var graph = LoadGraph(Path.Join(dir, pbFile));
  40. var input_operation = graph.get_operation_by_name(input_name);
  41. var output_operation = graph.get_operation_by_name(output_name);
  42. var results = with<Session, NDArray>(tf.Session(graph),
  43. sess => sess.run(output_operation.outputs[0],
  44. new FeedItem(input_operation.outputs[0], nd)));
  45. results = np.squeeze(results);
  46. var argsort = results.argsort<float>();
  47. var top_k = argsort.Data<float>()
  48. .Skip(results.size - 5)
  49. .Reverse()
  50. .ToArray();
  51. foreach (float idx in top_k)
  52. Console.WriteLine($"{picFile}: {idx} {labels[(int)idx]}, {results[(int)idx]}");
  53. }
  54. private string[] LoadLabels(string file)
  55. {
  56. return File.ReadAllLines(file);
  57. }
  58. private Graph LoadGraph(string modelFile)
  59. {
  60. var graph = tf.Graph().as_default();
  61. var graph_def = GraphDef.Parser.ParseFrom(File.ReadAllBytes(modelFile));
  62. tf.import_graph_def(graph_def);
  63. return graph;
  64. }
  65. private NDArray ReadTensorFromImageFile(string file_name,
  66. int input_height = 299,
  67. int input_width = 299,
  68. int input_mean = 0,
  69. int input_std = 255)
  70. {
  71. return with<Graph, NDArray>(tf.Graph().as_default(), graph =>
  72. {
  73. var file_reader = tf.read_file(file_name, "file_reader");
  74. var image_reader = tf.image.decode_jpeg(file_reader, channels: 3, name: "jpeg_reader");
  75. var caster = tf.cast(image_reader, tf.float32);
  76. var dims_expander = tf.expand_dims(caster, 0);
  77. var resize = tf.constant(new int[] { input_height, input_width });
  78. var bilinear = tf.image.resize_bilinear(dims_expander, resize);
  79. var sub = tf.subtract(bilinear, new float[] { input_mean });
  80. var normalized = tf.divide(sub, new float[] { input_std });
  81. return with<Session, NDArray>(tf.Session(graph), sess => sess.run(normalized));
  82. });
  83. }
  84. private void PrepareData()
  85. {
  86. Directory.CreateDirectory(dir);
  87. // get model file
  88. string url = "https://storage.googleapis.com/download.tensorflow.org/models/inception_v3_2016_08_28_frozen.pb.tar.gz";
  89. string zipFile = Path.Join(dir, $"{pbFile}.tar.gz");
  90. Utility.Web.Download(url, zipFile);
  91. if (!File.Exists(Path.Join(dir, pbFile)))
  92. Utility.Compress.ExtractTGZ(zipFile, dir);
  93. // download sample picture
  94. string pic = "grace_hopper.jpg";
  95. Utility.Web.Download($"https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/examples/label_image/data/{pic}", Path.Join(dir, pic));
  96. }
  97. }
  98. }

tensorflow框架的.NET版本,提供了丰富的特性和API,可以借此很方便地在.NET平台下搭建深度学习训练与推理流程。