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An example Media Workflow with Dolby.io presented at the 2021 Azure Serverless Conf |
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This sample highlights how to use Azure functions and Dolby.io to create a media processing pipeline that transcribes and enhances input media.
- Install Python 3.8+
- Azure Storage Account
- Azure Speech-to-text service Account
- Dolby.io Account, sign up for free
- ngrok account (only for local testing), sign up for free
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"cog_api_key": Azure Cognitive Services Speech-to-text API Key,
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"dolbyio_api_key": Dolby.io media API Key,
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"azure_api_key" : Azure storage account API key,
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"AZURE_ACC_NAME" : Azure storage account name,
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"AZURE_CONTAINER" : Azure storage container name,
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"AZURE_BLOB_OUTPUT_SUFFIX" : the output suffix added to the enhanced version of the input media,
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"SCORE_THRESHOLD" : the score threshold that decides if the audio quality of the input media is too low,
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"transcription_url" : the Azure cognitive services input URL for transcription, dependent on region.
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"tunneling_url" : The location of your Serverless HTTP trigger, or your HTTP tunnel (if you run locally)
- Follow the guide here to get setup with VS Code, Azure functions, and Python.
- Once set up you can clone the project and open it in VS Code.
- Create a HTTP tunnel with ngrok
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- "ngrok" is a tunneling tool that allows you to port forward to local host.
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- In my case my local function was deployed on 7071, so I initalized ngrok to port forward on LocalHost:7071
- Adjust the "params.json" file with your HTTP ngrok Tunnel and the other appropriate params such as your blob name and API keys, then save the file.
- Now you can press F5 to run the project.
- Once the code is running, navigate to http://localhost:"YOUR_SERVER"/api/MediaProcessingWorkflow?input_file="YOUR_INPUT_FILE" in your browser.
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- This will trigger the function to run locally, if all params are valid you can check your storage account for transcriptions or enhanced media.
- Follow the guide here to get setup with VS Code, Azure functions, and Python.
- Once set up you can clone the project and open it in VS Code.
- Adjust the "params.json" file.
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- In this case the tunneling URL will be https://"YOUR_FUNCTION_APP_NAME".azurewebsites.net/api/"YOUR_FUNCTION_NAME"
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- For example our tunneling URL is https://DolbyioMediaWorkflowTest.azurewebsites.net/api/MediaProcessingWorkflow
- Next deploy function app
- Once successfully deployed to the Azure Server you can test your function by navigating to:
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- https://"YOUR_FUNCTION_APP_NAME".azurewebsites.net/api/"YOUR_FUNCTION_NAME"?input_file="YOUR_INPUT_FILE"