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:
- Build the NIMA TFS Docker image
docker build -t tfs_nima contrib/tf_serving - Run a NIMA TFS container with
docker run -d --name tfs_nima -p 8500:8500 tfs_nima - 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
- 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