private static TFSession LoadTFSession(IHostEnvironment env, string exportDirSavedModel)
{
Contracts.Check(env != null, nameof(env));
env.CheckValue(exportDirSavedModel, nameof(exportDirSavedModel));
var sessionOptions = new TFSessionOptions();
var tags = new string[] { "serve" };
var graph = new TFGraph();
var metaGraphDef = new TFBuffer();
return(TFSession.FromSavedModel(sessionOptions, null, exportDirSavedModel, tags, graph, metaGraphDef));
}
public static void Main(string [] args)
{
TFSessionOptions options = new TFSessionOptions();
unsafe
{
//byte[] PUConfig = new byte[] { 0x32, 0x05, 0x20, 0x01, 0x2a, 0x01, 0x30, 0x38, 0x01 }; //gpu
byte[] PUConfig = new byte[] { 0x0a, 0x07, 0x0a, 0x03, 0x67, 0x70, 0x75, 0x10, 0x00 }; //cpu
fixed(void *ptr = &PUConfig[0])
{
options.SetConfig(new IntPtr(ptr), PUConfig.Length);
}
}
TFSession session;
var graph = new TFGraph();
using (TFSession sess = new TFSession(graph, options))
using (var metaGraphUnused = new TFBuffer())
{
session = sess.FromSavedModel(options, null, "tzb", new[] { "serve" }, graph, metaGraphUnused);
IEnumerable <TensorFlow.DeviceAttributes> iem = session.ListDevices();
foreach (object obj in iem)
{
Console.WriteLine(((DeviceAttributes)obj).Name);
}
var labels = File.ReadAllLines("tzb/label.txt");
//打印节点名称
/*IEnumerable<TensorFlow.TFOperation> iem = graph.GetEnumerator();
* foreach (object obj in iem)
* {
* Console.WriteLine(((TFOperation)obj).Name);
* }*/
//while(true)
float[] eimg = new float[224 * 224];
for (int i = 0; i < 224 * 224; i++)
{
eimg[i] = 0;
}
TFTensor ten = TFTensor.FromBuffer(tfs, eimg, 0, 224 * 224 * 1);
for (int j = 0; j < 3; j++)
{
var runner = session.GetRunner();
runner.AddInput(graph["images"][0], ten).Fetch(graph["classes"].Name);
var output = runner.Run();
}
ten.Dispose();
string[] files = Directory.GetFiles("tzb/images/defect", "*.*");
//while(true)
foreach (string file in files)
{
DateTime bft = DateTime.Now;
//var tensor = Image2Tensor(file);
//break;
var tensor = ImageUtil.CreateTensorFromImageFile(file);
//TFTensor tensor = TFTensor.FromBuffer(tfs, eimg, 0, 224 * 224);
var runner = session.GetRunner();
runner.AddInput(graph["images"][0], tensor).Fetch(graph["classes"].Name);
var output = runner.Run();
DateTime aft = DateTime.Now;
TimeSpan ts = aft.Subtract(bft);
System.Threading.Thread.Sleep(50);
var result = output[0];
int class_ = ((int[])result.GetValue(jagged: true))[0];
Console.WriteLine(file + " best_match: " + class_ + " " + labels[class_] + " time: " + ts.TotalMilliseconds);
}
}
}