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tensorflow/core
tensorflow_serving/apis
.dockerignore
Dockerfile
Dockerfile.alpine
Dockerfile.model
README.md
app.go
inception_client.go
kontena.yml

README.md

Tensorflow models in containers

This repo has an example how to utilize TensorFlow models with containers.

The model

The example inception model for image classification can be built as container image using Dockerfile.model file. It will download the model and put it to be served by tensorrflow-service component.

API

The model servicing API is somewhat complex to use, so there's a simplified Go API implemented on top of it. Build it using Dockerfile.

Deploying

There's a ready stack file to deploy everything on Kontena, so get you Kontena up-and-running. See https://kontena.io/docs/quick-start.html to get up-and-running in no time.

After you have Kontena platform running, you can install the stack with kontena stack install jussi/tensorflow-example

To test it out, you can use e.g. curl:

$ curl -s -XPOST -F "file=@/Users/jussi/Downloads/cropped_panda.jpg" image-classifier.kontena.works/classify | jq .
[
  {
    "Class": "giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca",
    "Score": 9.546637
  },
  {
    "Class": "indri, indris, Indri indri, Indri brevicaudatus",
    "Score": 6.6261067
  },
  {
    "Class": "gibbon, Hylobates lar",
    "Score": 4.3301826
  },
  {
    "Class": "lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens",
    "Score": 4.0944114
  },
  {
    "Class": "titi, titi monkey",
    "Score": 2.8160584
  }
]