@@ -17,15 +17,15 @@ Terms of use
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Please note that all models provided by InnerEye-DeepLearning are intended for
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research purposes only. You are responsible for the performance, the necessary testing,
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- and if needed any regulatory clearance for any of the models produced by this toolbox.
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+ and if needed any regulatory clearance for any of the models produced by this toolbox.
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Usage
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-----
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The following instructions assume you have completed the preceding setup
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steps in the `InnerEye
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README <https://github.com/microsoft/InnerEye-DeepLearning/> `__, in
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- particular, `Setting up Azure Machine Learning <setting_up_aml.md >`__.
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+ particular, `Setting up Azure Machine Learning <../md/setting_up_aml.html >`__.
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Create an AzureML Dataset
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~~~~~~~~~~~~~~~~~~~~~~~~~
@@ -34,7 +34,7 @@ To evaluate pre-trained models on your own data, you will first need to register
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an `Azure ML
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Dataset <https://docs.microsoft.com/en-us/azure/machine-learning/v1/how-to-create-register-datasets> `__.
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You can follow the instructions in the for `creating
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- datasets <creating_dataset.md > `__ in order to do this.
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+ datasets <../md/creating_dataset.html > `__ in order to do this.
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Downloading the models
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~~~~~~~~~~~~~~~~~~~~~~
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Model <https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.model.model?view=azure-ml-py#remarks> `__.
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To register the pre-trained model in your AML Workspace, unpack the
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source code downloaded in the previous step and follow InnerEye's
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- `instructions to upload models to Azure ML <move_model.md >`__.
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+ `instructions to upload models to Azure ML <../md/move_model.html >`__.
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Run the following from a folder that contains both the ``ENVIRONMENT/ ``
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and ``MODEL/ `` folders (these exist inside the downloaded model files):
@@ -74,7 +74,7 @@ Evaluating the model
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You can evaluate the model either in Azure ML or locally using the
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downloaded checkpoint files. These 2 scenarios are described in more
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detail, along with instructions in `testing an existing
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- model <building_models.md #testing-an-existing-model> `__.
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+ model <../md/building_models.html #testing-an-existing-model> `__.
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For example, to evaluate the model on your Dataset in Azure ML, run the
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following from within the directory ``*/MODEL/final_ensemble_model/ ``
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