GeezerVison is showing github.com — TensorFlow.NET/test/TensorFlowNET.Examples/ImageRecognition.cs at master · dsyme/TensorFlow.NET

Expand file tree

ImageRecognition.cs

Copy path

More file actions

Latest commit

History

98 lines (83 loc) · 3.67 KB

ImageRecognition.cs

Copy path

File metadata and controls

98 lines (83 loc) · 3.67 KB

Raw

Copy raw file

Download raw file

Open symbols panel

Edit and raw actions

using NumSharp.Core;

using System;

using System.Collections.Generic;

using System.IO;

using System.IO.Compression;

using System.Linq;

using System.Net;

using System.Text;

using Tensorflow;

namespace TensorFlowNET.Examples

{

public class ImageRecognition : Python, IExample

{

string dir = "ImageRecognition";

string pbFile = "tensorflow_inception_graph.pb";

string labelFile = "imagenet_comp_graph_label_strings.txt";

string picFile = "grace_hopper.jpg";

public void Run()

{

PrepareData();

var labels = File.ReadAllLines(Path.Join(dir, labelFile));

var files = Directory.GetFiles(Path.Join(dir, "img"));

foreach (var file in files)

{

var tensor = ReadTensorFromImageFile(file);

var graph = new Graph().as_default();

//import GraphDef from pb file

graph.Import(Path.Join(dir, pbFile));

var input_name = "input";

var output_name = "output";

var input_operation = graph.OperationByName(input_name);

var output_operation = graph.OperationByName(output_name);

var idx = 0;

float propability = 0;

with(tf.Session(graph), sess =>

{

var results = sess.run(output_operation.outputs[0], new FeedItem(input_operation.outputs[0], tensor));

var probabilities = results.Data<float>();

for (int i = 0; i < probabilities.Length; i++)

{

if (probabilities[i] > propability)

{

idx = i;

propability = probabilities[i];

}

});

Console.WriteLine($"{picFile}: {labels[idx]} {propability}");

}

private NDArray ReadTensorFromImageFile(string file_name,

int input_height = 224,

int input_width = 224,

int input_mean = 117,

int input_std = 1)

{

return with(tf.Graph().as_default(), graph =>

{

var file_reader = tf.read_file(file_name, "file_reader");

var decodeJpeg = tf.image.decode_jpeg(file_reader, channels: 3, name: "DecodeJpeg");

var cast = tf.cast(decodeJpeg, tf.float32);

var dims_expander = tf.expand_dims(cast, 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(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/inception5h.zip";

Utility.Web.Download(url, dir, "inception5h.zip");

Utility.Compress.UnZip(Path.Join(dir, "inception5h.zip"), dir);

// download sample picture

Directory.CreateDirectory(Path.Join(dir, "img"));

url = $"https://raw.githubusercontent.com/tensorflow/tensorflow/master/tensorflow/examples/label_image/data/grace_hopper.jpg";

Utility.Web.Download(url, Path.Join(dir, "img"), "grace_hopper.jpg");

}