http-trigger-onnx-model

http-trigger-onnx-model (Python)

Sample	Description	Trigger	In Bindings	Out Bindings
http-trigger-onnx-model	This function demonstrates running an inference using an ONNX model. It is triggered by an HTTP request. See Try it out for usage.	HTTP	NONE	HTTP

The style transfer model used in this function is called Rain Princess. It is downloaded from the ONNX Model Zoo.

Artistic style transfer models mix the content of an image with the style of another image. Examples of the styles can be seen here.

Open Neural Network Exchange (ONNX) is an open standard format for representing machine learning models. ONNX is supported by a community of partners who have implemented it in many frameworks and tools.

The ONNX Model Zoo is a collection of pre-trained, state-of-the-art models in the ONNX format contributed by community members like you. See https://github.com/onnx/models for more.

You should be able to use other ONNX models in your function by rewriting the preprocess/postprocess code and wiring the expected inputs and outputs.

Sample run

This example is probably not going to age well. However the pun stands on its own. Shown here: httpie, imgcat.

Dependencies

Pillow==7.0.0
onnxruntime==1.1.0
numpy==1.18.1

Make sure you have these in your requirements.txt at the root of your function app.

Configuration

As specified in functions.json, this function is triggered by an HTTP request. It expects a POST request with raw image bytes (JPEG/PNG/whatever the Pillow library can open). Output is an HTTP response with the resulting style transferred image (JPEG encoded).

{
  "scriptFile": "__init__.py",
  "bindings": [
    {
      "authLevel": "function",
      "type": "httpTrigger",
      "direction": "in",
      "name": "req",
      "methods": [
        "post"
      ]
    },
    {
      "type": "http",
      "direction": "out",
      "name": "$return"
    }
  ]
}

How to develop and publish the functions

Local development

func host start

Try it out

# Make a POST request
$ curl -s --data-binary @babyyoda.jpg http://localhost:7071/api/http-trigger-onnx-model -o out.jpg

# Open the resulting image (on a Mac)
# Use feh or xdg-open on Linux
$ open out.jpg

Publish the function to the cloud

Publish the function to the cloud

FUNCTION_APP_NAME="MyFunctionApp"
func azure functionapp publish $FUNCTION_APP_NAME --build-native-deps --no-bundler

Add Functions App Settings

FUNCTION_STORAGE_CONNECTION="*************"
az webapp config appsettings set \
  -n $FUNCTION_APP_NAME \
  -g $RESOURCE_GROUP \
  --settings \
    MyStorageConnectionString=$FUNCTION_STORAGE_CONNECTION