var graph = new TFGraph();//重點是下面的這句，把訓練好的pb文件給讀出來字節，然后導入var model = File.ReadAllBytes(model_file);graph.Import(model);Console.WriteLine("請輸入一個圖片的地址");var src = Console.ReadLine();var tensor = ImageUtil.CreateTensorFromImageFile(src);using (var sess = new TFSession(graph)){var runner = sess.GetRunner();runner.AddInput(graph["Cast_1"][0], tensor);var r = runner.Run(graph.softmax(graph["softmax_linear/softmax_linear"][0]));var v = (float[,])r.GetValue();Console.WriteLine(v[0,0]);Console.WriteLine(v[0, 1]);}

public static class ImageUtil{public static TFTensor CreateTensorFromImageFile(byte[] contents, TFDataType destinationDataType = TFDataType.Float){var tensor = TFTensor.CreateString(contents);TFOutput input, output;// Construct a graph to normalize the imageusing (var graph = ConstructGraphToNormalizeImage(out input, out output, destinationDataType)){// Execute that graph to normalize this one imageusing (var session = new TFSession(graph)){var normalized = session.Run(inputs: new[] { input },inputValues: new[] { tensor },outputs: new[] { output });return normalized[0];}}}// Convert the image in filename to a Tensor suitable as input to the Inception model.public static TFTensor CreateTensorFromImageFile(string file, TFDataType destinationDataType = TFDataType.Float){var contents = File.ReadAllBytes(file);// DecodeJpeg uses a scalar String-valued tensor as input.var tensor = TFTensor.CreateString(contents);TFOutput input, output;// Construct a graph to normalize the imageusing (var graph = ConstructGraphToNormalizeImage(out input, out output, destinationDataType)){// Execute that graph to normalize this one imageusing (var session = new TFSession(graph)){var normalized = session.Run(inputs: new[] { input },inputValues: new[] { tensor },outputs: new[] { output });return normalized[0];}}}// The inception model takes as input the image described by a Tensor in a very// specific normalized format (a particular image size, shape of the input tensor,// normalized pixel values etc.).//// This function constructs a graph of TensorFlow operations which takes as// input a JPEG-encoded string and returns a tensor suitable as input to the// inception model.private static TFGraph ConstructGraphToNormalizeImage(out TFOutput input, out TFOutput output, TFDataType destinationDataType = TFDataType.Float){// Some constants specific to the pre-trained model at:// https://storage.googleapis.com/download.tensorflow.org/models/inception5h.zip//// - The model was trained after with images scaled to 224x224 pixels.// - The colors, represented as R, G, B in 1-byte each were converted to// float using (value - Mean)/Scale.const int W = 128;const int H = 128;const float Mean = 0;const float Scale = 1f;var graph = new TFGraph();input = graph.Placeholder(TFDataType.String);output = graph.Cast(graph.Div(x: graph.Sub(x: graph.ResizeBilinear(images: graph.ExpandDims(input: graph.Cast(graph.DecodeJpeg(contents: input, channels: 3), DstT: TFDataType.Float),dim: graph.Const(0, "make_batch")),size: graph.Const(new int[] { W, H }, "size")),y: graph.Const(Mean, "mean")),y: graph.Const(Scale, "scale")), destinationDataType);return graph;}}