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- using ICSharpCode.SharpZipLib.GZip;
- using ICSharpCode.SharpZipLib.Tar;
- using NumSharp.Core;
- using System;
- using System.Collections.Generic;
- using System.IO;
- using System.Linq;
- using System.Net;
- using System.Text;
- using System.Threading;
- using System.Threading.Tasks;
- using Tensorflow;
-
- namespace TensorFlowNET.Examples
- {
- /// <summary>
- /// Port from tensorflow\examples\label_image\label_image.py
- /// </summary>
- public class LabelImage : Python, IExample
- {
- string dir = "label_image_data";
- string pbFile = "inception_v3_2016_08_28_frozen.pb";
- string labelFile = "imagenet_slim_labels.txt";
- string picFile = "grace_hopper.jpg";
- int input_height = 299;
- int input_width = 299;
- int input_mean = 0;
- int input_std = 255;
- string input_name = "import/input";
- string output_name = "import/InceptionV3/Predictions/Reshape_1";
-
- public void Run()
- {
- PrepareData();
-
- var labels = LoadLabels(Path.Join(dir, labelFile));
-
- var nd = ReadTensorFromImageFile(Path.Join(dir, picFile),
- input_height: input_height,
- input_width: input_width,
- input_mean: input_mean,
- input_std: input_std);
-
- var graph = LoadGraph(Path.Join(dir, pbFile));
- var input_operation = graph.get_operation_by_name(input_name);
- var output_operation = graph.get_operation_by_name(output_name);
-
- var results = with<Session, NDArray>(tf.Session(graph),
- sess => sess.run(output_operation.outputs[0],
- new FeedItem(input_operation.outputs[0], nd)));
-
- results = np.squeeze(results);
-
- var argsort = results.argsort<float>();
- var top_k = argsort.Data<float>()
- .Skip(results.size - 5)
- .Reverse()
- .ToArray();
-
- foreach (float idx in top_k)
- Console.WriteLine($"{picFile}: {idx} {labels[(int)idx]}, {results[(int)idx]}");
- }
-
- private string[] LoadLabels(string file)
- {
- return File.ReadAllLines(file);
- }
-
- private Graph LoadGraph(string modelFile)
- {
- var graph = tf.Graph().as_default();
- var graph_def = GraphDef.Parser.ParseFrom(File.ReadAllBytes(modelFile));
- tf.import_graph_def(graph_def);
- return graph;
- }
-
- private NDArray ReadTensorFromImageFile(string file_name,
- int input_height = 299,
- int input_width = 299,
- int input_mean = 0,
- int input_std = 255)
- {
- return with<Graph, NDArray>(tf.Graph().as_default(), graph =>
- {
- var file_reader = tf.read_file(file_name, "file_reader");
- var image_reader = tf.image.decode_jpeg(file_reader, channels: 3, name: "jpeg_reader");
- var caster = tf.cast(image_reader, tf.float32);
- var dims_expander = tf.expand_dims(caster, 0);
- var resize = tf.constant(new int[] { input_height, input_width });
- var bilinear = tf.image.resize_bilinear(dims_expander, resize);
- var sub = tf.subtract(bilinear, new float[] { input_mean });
- var normalized = tf.divide(sub, new float[] { input_std });
-
- return with<Session, NDArray>(tf.Session(graph), sess => sess.run(normalized));
- });
- }
-
- private void PrepareData()
- {
-
- Directory.CreateDirectory(dir);
-
- // get model file
- string url = "https://storage.googleapis.com/download.tensorflow.org/models/inception_v3_2016_08_28_frozen.pb.tar.gz";
-
- string zipFile = Path.Join(dir, $"{pbFile}.tar.gz");
- Utility.Web.Download(url, zipFile);
-
- if (!File.Exists(Path.Join(dir, pbFile)))
- Utility.Compress.ExtractTGZ(zipFile, dir);
-
- // download sample picture
- string pic = "grace_hopper.jpg";
- Utility.Web.Download($"https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/examples/label_image/data/{pic}", Path.Join(dir, pic));
- }
- }
- }
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