titmy / deep-nn-imageclassification

Practice Code for CS229 Final Report

Project Title

Deep Neural Network Image Classifier for classifying warehouse products at Lowes to assist in inventory upkeep

Getting Started

Have tensorflow installed with dependencies. You can use docker container which would speed up development and production. Solves dependencies issues when shipping.

[Docker] (https://www.docker.com)

Prerequisites

Using Docker

[All Instructions here for docker] (https://codelabs.developers.google.com/codelabs/tensorflow-for-poets/?utm_campaign=chrome_series_machinelearning_063016&utm_source=gdev&utm_medium=yt-desc#0)

What things you need to install the software and how to install them

• Install TF Image

docker run -it gcr.io/tensorflow/tensorflow:latest-devel
# cd/tensorflow
gitpull

• Link Dataset to TF Image

docker run -it -v path_to_files/tf_files/folder_with_images gcr.io/tensorflow/tensorflow:latest-devel

• Run pre-written training script in tensorflow/examples

# python tensorflow/examples/image_retraining/retrain.py \
--bottleneck_dir=/tf_files/bottlenecks \
--how_many_training_steps 500 \
--model_dir=/tf_files/inception \
--output_graph=/tf_files/retrained_graph.pb \
--output_labels=/tf_files/retrained_labels.txt \
--image_dir /tf_files/flower_photos

or

Using on machine tensor

[Follow tensorflow website] (https://www.tensorflow.org/versions/r0.12/get_started/os_setup.html#requirements)

Implementation

python label_image.py path_to_file/filename.jpg

Deployment

Add additional notes about how to deploy this on a live system