No Library cv2 on AzureML - azure

Question

I am trying to learn AzureML sdk and train my model on cloud.
I successfully train demo project located here.
Now, that I want to train my own model, I get error :
UserError","message":"No module named 'cv2'","target":null,"details":[],"innerErro...
This means, that cv2 is not installed on AzureML and I use it in my train script,...
How to pip install library on AzureML or, how to "copy" virtual environment to my workspace

Answer 1

The answer is to add opencv-python-headless as a pip installation
like this:
TensorFlow(source_directory=script_folder,
script_params=script_params,
compute_target=compute_target,
entry_script=train_script_name,
pip_packages=['opencv-python-headless', 'scikit-image', 'mathematics', 'keras', 'scikit-learn'],
use_gpu=True)

Answer 2

I assume you mean that you are training on Azure ML managed compute?! If so, you need to specify all your required packages in a Conda dependencies file. See here for guidance: https://learn.microsoft.com/sl-si/azure/machine-learning/service/how-to-set-up-training-targets#system-managed-environment
Use a system-managed environment when you want Conda to manage the
Python environment and the script dependencies for you. A
system-managed environment is assumed by default and the most common
choice. It is useful on remote compute targets, especially when you
cannot configure that target.
All you need to do is specify each package dependency using the
CondaDependency class Then Conda creates a file named
conda_dependencies.yml in the aml_config directory in your workspace
with your list of package dependencies and sets up your Python
environment when you submit your training experiment.
Alternativly, if you are using estimators and require only a few packages, you can also specify them directly:
estimator = SKLearn(source_directory=project_folder,
script_params=script_params,
compute_target=compute_target,
entry_script='train_iris.py'
pip_packages=['joblib']
)
https://learn.microsoft.com/en-Us/azure/machine-learning/service/how-to-train-scikit-learn#create-a-scikit-learn-estimator