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5)Please create a webserver and a client for ML inference system.

Please use multiclass_image_classification.ipynb for training your CNN. Please use training and test dataset images for model training and validation and testing purposes.

A)After training your model, you shall save the trained model as a file (model.h5); Download it and place it in the directory where your server code is placed.

B)Your system shall have a web server which starts with ./server.sh command. It shall respond to the client.sh client command.

server (display server name and port number)

3. You system shall have a client.sh script.

client - gets information from your server and prints. The information include the project name, your name, and current date/time.

e.g.,

The client command:

client

A sample output:

Rock, Paper and Scissors image classification server.

John Smith

May 1^st, 2021

client with an image file name as a parameter sends the image file to the server and displays the classified image name.

e.g.,

The client command:

client myhand.jpg

A sample output:

John Smith

Rock, Paper and Scissors image classification server.

John Smith

May 1^st, 2021

The image youve submitted is classified as a: paper

Submission

A) Create _README.docx file. It shall have 3 sections:

1. ML Web Server Description

-Just two-three sentences about what this server does, used data sets, model, web server routes etc.

2. Testing the Web Server and Clients
   1. How to test the server and its clients
3. Screen Captures of Test Run
   1. Place at least two screen capture images (running client and client ) while you are running the web server and its client.
   2. Screen capture images shall clearly show the client and server outputs.

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