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contrib/segmentation/mlops
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+ $schema : https://azuremlschemas.azureedge.net/latest/compute.schema.json
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+ name : gpu-cluster
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+ type : amlcompute
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+ size : Standard_NC24s_v3
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+ min_instances : 0
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+ max_instances : 2
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+ name : conda-env
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+ channels :
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+ - conda-forge
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+ dependencies :
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+ - python=3.8
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+ - pip
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+ - pip :
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+ - albumentations
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+ - azure-storage-blob
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+ - azureml-sdk
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+ - click
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+ - ipyplot
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+ - jupyter
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+ - jupytext
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+ - matplotlib
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+ - numpy>=1.20
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+ - pandas
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+ - pycocotools
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+ - python-dotenv
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+ - scikit-learn
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+ - seaborn
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+ - segmentation-models-pytorch
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+ - torch
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+ - torchmetrics
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+ - torchvision
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+ $schema : https://azuremlschemas.azureedge.net/latest/dataset.schema.json
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+ name : drone-dataset
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+ version : 1
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+ datastore : azureml:workspaceblobstore
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+ local_path : <path-to-local-dataset>
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+ $schema : https://azuremlschemas.azureedge.net/latest/environment.schema.json
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+ name : semantic-segmentation
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+ version : 1
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+ docker :
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+ image : mcr.microsoft.com/azureml/openmpi3.1.2-ubuntu18.04
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+ conda_file : file:conda_envs/conda_env.yml
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