Can ML.NET Image Classification Transfer Learning be resumed from a saved model .zip file or checkpoint? How?

Question

I am using the NuGet packages Microsoft.ML (1.4.0) and SciSharp.TensorFlow.Redist (1.15.0)

Initial training and saving the model works fine

var options = new Microsoft.ML.Vision.ImageClassificationTrainer.Options()
{
    FeatureColumnName = "Image",
    LabelColumnName = "LabelAsKey",
    Arch = Microsoft.ML.Vision.ImageClassificationTrainer.Architecture.InceptionV3,
    Epoch = 50,
    BatchSize = 10,
    LearningRate = 0.01f,
    MetricsCallback = (metrics) => Console.WriteLine(metrics),
    ValidationSet = testDataView
};

var pipeline = mlContext.MulticlassClassification.Trainers.ImageClassification(options)
        .Append(mlContext.Transforms.Conversion.MapKeyToValue(
            outputColumnName: "PredictedLabel", 
            inputColumnName: "PredictedLabel"));


ITransformer trainedModel = pipeline.Fit(trainDataView);

mlContext.Model.Save(trainedModel, trainDataView.Schema, "C:/Temp/model.zip")

And using the model to make predictions works fine

var loadModel = mlContext.Model.Load("C/Temp/Model.zip", out var modelInputSchema)
var PredictionEngine = mlContext.Model.CreatePredictionEngine<InMemoryImageData, ImagePrediction>(loadModel);

prediction = PredictionEngine.Predict(image);

But if I want to continue training the model.zip file with more images without retraining from the baseline model from scratch, how do I do that?

Is there I way I can call .Fit() again that uses the loaded model?

Answer 1

ML.NET doesn't support resuming training for image classification trainers. Currently, the only trainers that support it are the following: https://learn.microsoft.com/en-us/dotnet/machine-learning/how-to-guides/retrain-model-ml-net