/// <summary>
/// Dispose our model <see cref="m_model"/> and interpreter <see cref="m_interpreter"/>.
/// </summary>
public void DisposeObjects()
{
if (m_model != null)
{
m_model.Dispose();
m_model = null;
}
if (m_interpreter != null)
{
m_interpreter.Dispose();
m_interpreter = null;
}
}
/// <summary>
/// Constructor with arguments defining the values of <see cref="m_frozenModelPath"/>, <see cref="m_model"/>,
/// <see cref="m_interpreter"/>. It also defines <see cref="m_outputTensors"/> as the <see cref="m_interpreter.Outputs">
/// and <see cref="m_inputTensor"/> as <see cref="m_inputTensor.Inputs[0]"/>, assuming the input tensor will be a
/// 3 channels BGR image.
/// </summary>
/// <param name="frozenModelPath">Path to a PoseNet model saved with tensorflow lite (.tflite file).</param>
/// <param name="numberOfThreads">Number of threads the neural network will be able to use (default: 2, from base class)</param>
public PoseNetEstimator(String frozenModelPath,
int numberOfThreads = 4)
{
// Check file
if (!File.Exists(frozenModelPath))
{
Console.WriteLine("ERROR:");
Console.WriteLine("FrozenModelPath specified in DeepNetworkLite " +
"construtor with argument does not exist.");
Console.WriteLine("Network not loaded.");
return;
}
if (Path.GetExtension(frozenModelPath) != m_expectedModelExtension)
{
Console.WriteLine("ERROR:");
Console.WriteLine("Extension of specified frozen model path in DeepNetworkLite " +
"constructor with argument does not" +
"match " + m_expectedModelExtension);
Console.WriteLine("Network not loaded.");
return;
}
if (m_frozenModelPath == "")
{
m_frozenModelPath = frozenModelPath;
}
try
{
if (m_frozenModelPath != "")
{
m_model = new Emgu.TF.Lite.FlatBufferModel(filename: m_frozenModelPath);
m_interpreter = new Emgu.TF.Lite.Interpreter(flatBufferModel: m_model);
m_interpreter.AllocateTensors();
m_interpreter.SetNumThreads(numThreads: numberOfThreads);
}
}
catch
{
DisposeObjects();
Console.WriteLine("ERROR:");
Console.WriteLine("Unable to load frozen model in DeepNetworkLite constructor with arguments " +
"despite files was found with correct extension. " +
"Please, make sure you saved your model using tensorflow lite pipelines." +
"Current path found is : " + m_frozenModelPath);
return;
}
if (m_inputTensor == null)
{
int[] input = m_interpreter.InputIndices;
m_inputTensor = m_interpreter.GetTensor(input[0]);
}
if (m_outputTensors == null)
{
m_outputTensors = m_interpreter.Outputs;
}
// Populate our array of keypoints
for (int i = 0; i < m_keypoints.Length; i++)
{
m_keypoints[i] = new Keypoint();
}
return;
}