Deployment an Image Classiffication Deep Learning Model

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DEFINITION OF PROBLEM

We have images of 10 different classes. We want to classify these pictures into 10 different classes. Our problem is a classification problem.

WHAT DO WE NEED?

When an image comes in I need to find out which category it falls into from 10 different classes.

WHAT AM I USING FOR THIS?

I am using the Cifar10 Dataset. Cifar10 Dataset: http://www.cs.toronto.edu/~kriz/cifar.html

HOW DID WE APPROACH THIS PROBLEM?

We acted as if we had a camera presenter who was constantly taking images. We have addressed the problem of classifying these snapshots in 10 different classes

HOW DID WE GET IT?

I got the model for the Cifar10 dataset from the adjacent book. We used the Adam optimizer as the optimizer in the model. The model gives 88 percent accuracy after 50 iterations

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System Requirements

• ORACLE VM VİRTUALBOX 6.1
• UBUNTU 18.04.5 LTS
• TENSORFLOW 2.6.0
• PYTHON 3.6.9
• RABBİT MQ

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RabbitMQ

👉🏻 https://www.rabbitmq.com

Cifar10 Dataset

👉🏻 http://www.cs.toronto.edu/~kriz/cifar.html

Tensorflow 1.x Deep Learning Cookbook

👉🏻 https://bit.ly/3zI3BbN

Ubuntu 18.04 Install Tensorflow

👉🏻 https://emineozturkk.medium.com/ubuntu-18-04-install-tensorflow-dfcc3f904b81

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Trained Model

When the model.py file is run, it gives 88 percent accuracy for 50 iterations.