opencvsharp4 调用Tensorflow pb文件预测
时间: 2024-02-28 14:53:11 浏览: 27
可以使用OpenCvSharp4和TensorFlowSharp来调用TensorFlow的pb文件进行预测。
首先,需要安装OpenCvSharp4和TensorFlowSharp的NuGet包。然后,可以使用以下代码来加载pb文件并进行预测:
```
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using System.Threading.Tasks;
using OpenCvSharp;
using TensorFlow;
namespace TensorFlowSharpTest
{
class Program
{
static void Main(string[] args)
{
// Load the TensorFlow model from the pb file
var graph = new TFGraph();
var model = File.ReadAllBytes("model.pb");
graph.Import(model, "");
// Create a TensorFlow session
var session = new TFSession(graph);
// Load the input image
var inputImage = new Mat("input.jpg");
// Resize the image to the expected size of the model
var inputTensor = ResizeImage(inputImage);
// Run the prediction
var runner = session.GetRunner();
runner.AddInput(graph["input"][0], inputTensor);
runner.Fetch(graph["output"][0]);
var output = runner.Run()[0];
// Get the predicted class
var outputData = (float[,])output.GetValue(jagged: false);
var predictedClass = GetPredictedClass(outputData);
Console.WriteLine($"Predicted class: {predictedClass}");
}
static TFTensor ResizeImage(Mat image)
{
// Resize the image to the expected size of the model
var resizedImage = new Mat();
Cv2.Resize(image, resizedImage, new Size(224, 224));
// Convert the image to a TensorFlow tensor
var tensor = TFTensor.FromBuffer(
new TFShape(1, resizedImage.Height, resizedImage.Width, 3),
resizedImage.Data
);
return tensor;
}
static int GetPredictedClass(float[,] outputData)
{
// Find the index of the maximum value in the output array
var maxIndex = 0;
var maxValue = float.MinValue;
for (int i = 0; i < outputData.GetLength(1); i++)
{
var value = outputData[0, i];
if (value > maxValue)
{
maxIndex = i;
maxValue = value;
}
}
return maxIndex;
}
}
}
```
注意,这里假设模型的输入是名为“input”的张量,输出是名为“output”的张量。如果模型的输入和输出名称不同,请相应地更改代码。
希望这可以帮助你。
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