Awesome

GNES Flow Demo: Flower Image Retrieval

Since v0.0.46 GNES Flow has become the main interface of GNES. GNES Flow provides a pythonic and intuitive way to implement a pipeline, enabling users to run or debug GNES on a local machine. By default, GNES Flow orchestrates all microservices using multi-thread or multi-process backend, it can be also exported to a Docker Swarm/Kubernetes YAML config, allowing one to deliver GNES to the cloud.

In this demo, we will learn to build a toy image search engine using GNES Flow API. The task is to retrieve similar flowers given query flowers.

Files

For first-time users, simply open flower.ipynb and follow the steps there.

• flower.ipynb: a self-contained Jupyter notebook with a step-by-step explanation
• index.py: the indexing part of flower.ipynb, for indexing all images.
• query.py: the querying part of flower.ipynb, for querying sampled images and plotting top-10 results

Requirements

gnes>=0.0.46
image
tensorflow==1.12

You can install them via pip install .. However, you may want to do that in a virtual env though as it will replace your local Tensorflow with tensorflow==1.12. Feel free to contribute and waive this particular requirement.

Troubleshooting

Can not load indexer when indexing twice

I didn't implement features like "incremental indexing" in this simple demo. So please make sure you clean up the existing index before doing python index.py.

rm $TEST_WORKDIR/*.bin

OSError: [Errno 24] Too many open files

This often happens when replicas/num_parallel is set to a big number. Solution to that is to increase this (session-wise) allowance via:

ulimit -n 4096

objc[15934]: +[__NSPlaceholderDictionary initialize] may have been in progress in another thread when fork() was called.

Probably MacOS only.

export OBJC_DISABLE_INITIALIZE_FORK_SAFETY=YES

Why tensorflow==1.12, why not 2.0?

In this demo, I simply use the inceptionV4 model from tf.contrib.slim. There are some major changes in TF2.0, and the model can not be directly used. Fortunately, contribute/port an external model to GNES is extremely simple. Feel free to follow the instruction in GNES Hub and make a contribution to this demo.

It stuck/crash in Jupyter Notebook

Please try running python index.py or python query.py outside the Jupyter Notebook. As far as I know, Jupyter Notebook is employing ZeroMQ in the backend and this can sometimes mess up with GNES sockets (or the other way around). If you find the demo still crash/stuck when running as independent Python script, then please report an issue to this repository or the GNES main repository.