In the name of God

AlexNet

This repository contains implementation of AlexNet (ImageNet Classification with Deep Convolutional Neural Networks) by Tensorflow and the network tested with the CIFAR-10 dataset.

Download the CIFAR-10 dataset

Before train and evaluate the network, you should download the following dataset:

• CIFAR-10 Dataset: https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz

Extract the cifar-10-python.tar.gz file, then your folder structure should be like the following image:

Training CIFAR-10 dataset

To train the network with cifar-10 dataset, type the following command at the command prompt:

python3 ./train.py

Sample images from cifar-10 dataset:

Results

Epoch 0

Train Accuracy = 0.100
Test Accuracy = 0.100

Epoch 1

Train Accuracy = 0.305
Test Accuracy = 0.303

Epoch 2

Train Accuracy = 0.408
Test Accuracy = 0.402

...

Epoch 50

Train Accuracy = 0.986
Test Accuracy = 0.721

...

Epoch 100

Final Train Accuracy = 1.000
Final Test Accuracy = 0.739

Evaluating CIFAR-10 dataset

To evaluate the network with cifar-10 dataset, type the following command at the command prompt:

python3 ./evaluate.py

Dependencies

• Python 3
• numpy
• scipy
• pillow
• tensorflow

Links

• https://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
• https://www.cs.toronto.edu/~kriz/cifar.html
• https://github.com/amir-saniyan/AlexNet