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Updated 3 years ago
!pip install jovian --upgrade --quiet
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
import matplotlib.pyplot as plt
%matplotlib inline
matplotlib.rcParams['figure.facecolor'] = '#ffffff'
project_name='cifa10cnn'
from torchvision.datasets.utils import download_url
# Dowload the dataset
dataset_url = "https://s3.amazonaws.com/fast-ai-imageclas/cifar10.tgz"
download_url(dataset_url, '.')
# Extract from archive
with tarfile.open('./cifar10.tgz', 'r:gz') as tar:
tar.extractall(path='./data')
# Look into the data directory
data_dir = './data/cifar10'
print(os.listdir(data_dir))
classes = os.listdir(data_dir + "/train")
print(classes)
Downloading https://s3.amazonaws.com/fast-ai-imageclas/cifar10.tgz to ./cifar10.tgz
| | 0/? [00:00<?, ?it/s]
['test', 'train']
['horse', 'airplane', 'dog', 'deer', 'cat', 'bird', 'frog', 'truck', 'ship', 'automobile']
['test', 'train']
['deer', 'cat', 'ship', 'dog', 'bird', 'airplane', 'automobile', 'frog', 'horse', 'truck']