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use strict;
use warnings;
package AI::PredictionClient;
$AI::PredictionClient::VERSION = '0.05';

use AI::PredictionClient::Predict;
use AI::PredictionClient::InceptionClient;

# ABSTRACT: A Perl Prediction client for Google TensorFlow Serving.

1;

__END__

=pod

=encoding UTF-8

=head1 NAME

AI::PredictionClient - A Perl Prediction client for Google TensorFlow Serving.

=head1 VERSION

version 0.05

=head1 DESCRIPTION

This is a package for creating Perl clients for TensorFlow Serving model servers. 
TensorFlow Serving is the system that allows TensorFlow neural network AI models 
to be moved from the research environment to your production environment. 

Currently this package implements a client for the Predict service and a model specific Inception client.

The Predict service 'Predict.pm' is the most versatile of the TensorFlow Serving Prediction services. 
A large portion of the model specific clients are implemented from this service.

The model specific client 'InceptionClient.pm'  is implemented. This is the most popular client. 

Additionally, a command line Inception client 'Inception.pl' is included 
as an example of a complete client built form this package.

=head2 Using the example client

The example client is installed in your local bin directory and 
will allow you to send an image to an Inception model server and display 
the classifications of what the Inception neural network model "thought" it saw.

This client implements a command line interface to the 
InceptionClient module 'AI::PredictionClient::InceptionClient', and provides 
a working example of using this module for building your own clients.

The commands for the Inception client can be displayed by running the Inception.pl client with no arguments.

 $ Inception.pl 
 image_file is missing
 USAGE: Inception.pl [-h] [long options ...]

    --debug_camel               Test using camel image
    --debug_loopback_interface  Test loopback through dummy server
    --debug_verbose             Verbose output
    --host=String               IP address of the server [Default:
                                127.0.0.1]
    --image_file=String         * Required: Path to image to be processed
    --model_name=String         Model to process image [Default: inception]
    --model_signature=String    API signature for model [Default:
                                predict_images]
    --port=String               Port number of the server [Default: 9000]
    -h                          show a compact help message

Some typical command line examples include:

 Inception.pl --image_file=anything --debug_camel --host=xx7.x11.xx3.x14 --port=9000
 Inception.pl --image_file=grace_hopper.jpg --host=xx7.x11.xx3.x14 --port=9000
 Inception.pl --image_file=anything --debug_camel --debug_loopback --port 2004 --host technologic

=head3 In the examples above, the following points are demonstrated: