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How to build:
==============================================

docker build -t <your image name> .

How to run locally:
==============================================
docker run -p 127.0.0.1:80:80 -d <your image name>

Then use your favorite tool to connect to the end points.

POST http://127.0.0.1/image with multipart/form-data using the imageData key
e.g
	curl -X POST http://127.0.0.1/image -F imageData=@some_file_name.jpg

POST http://127.0.0.1/image with application/octet-stream
e.g.
	curl -X POST http://127.0.0.1/image -H "Content-Type: application/octet-stream" --data-binary @some_file_name.jpg

POST http://127.0.0.1/url with a json body of { "url": "<test url here>" }
e.g.
    curl -X POST http://127.0.0.1/url -d '{ "url": "<test url here>" }'

For information on how to use these files to create and deploy through AzureML check out the readme.txt in the azureml directory.

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Car detection Computer Vision server for Iot

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