Image Classification using Convolutional Neural Networks in PyTorch

import os
import torch
import torchvision
import tarfile
import torch.nn as nn
import numpy as np
import torch.nn.functional as F
from torchvision.datasets.utils import download_url
from torchvision.datasets import ImageFolder
from torch.utils.data import DataLoader
import torchvision.transforms as tt
from torch.utils.data import random_split
from torchvision.utils import make_grid
import matplotlib.pyplot as plt
%matplotlib inline
!pip install jovian
import jovian

Collecting jovian
  Downloading jovian-0.2.15-py2.py3-none-any.whl (94 kB)
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Collecting uuid
  Downloading uuid-1.30.tar.gz (5.8 kB)
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Building wheels for collected packages: uuid
  Building wheel for uuid (setup.py) ... done
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Successfully built uuid
Installing collected packages: uuid, jovian
Successfully installed jovian-0.2.15 uuid-1.30

project_name='05-cifar100-cnn-live'

Exploring the Data

We'll download the images in PNG format from this page, using some helper functions from the torchvision and tarfile packages.

# Dowload the dataset
dataset_url = "https://s3.amazonaws.com/fast-ai-imageclas/imagenette-160.tgz"
download_url(dataset_url, '.')

Downloading https://s3.amazonaws.com/fast-ai-imageclas/imagenette-160.tgz to ./imagenette-160.tgz

HBox(children=(FloatProgress(value=1.0, bar_style='info', max=1.0), HTML(value='')))