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+## Serving NIMA with TensorFlow Serving
+TensorFlow versions of both the technical and aesthetic MobileNet models are provided,
+along with the script to generate them from the original Keras files, under the `contrib/tf_serving` directory.
+
+There is also an already configured TFS `Dockerfile` that you can use.
+
+To get predictions from the aesthetic or technical model:
+1. Build the NIMA TFS Docker image `docker build -t tfs_nima contrib/tf_serving`
+2. Run a NIMA TFS container with `docker run -d --name tfs_nima -p 8500:8500 tfs_nima`
+3. Install python dependencies to run TF serving sample client
+```
+virtualenv -p python3 contrib/tf_serving/venv_tfs_nima
+source contrib/tf_serving/venv_tfs_nima/bin/activate
+pip install -r contrib/tf_serving/requirements.txt
+```
+4. Get predictions from aesthetic or technical model by running the sample client
+```
+python -m contrib.tf_serving.tfs_sample_client --image-path src/tests/test_images/42039.jpg --model-name mobilenet_aesthetic
+python -m contrib.tf_serving.tfs_sample_client --image-path src/tests/test_images/42039.jpg --model-name mobilenet_technical
+```