Zerotogans Project Intel Image Classification
Classifying Intel Natural Scenes Images using PyTorch
This project is the result of the knowledge acquired during the course Deep Learning with PyTorch: Zero to GANs offered by Jovian.ai.
For this project, was chosen the open Intel Image Classification Dataset which contains images of nature scenes sperated in 6 categories. The main goal of the project is to define, train and test a neural network model for classifying images.
System Setup
Let's begin by installing and importing the required libraries.
# Uncomment and run the appropriate command for your operating system, if required
# Linux / Binder / Windows (No GPU)
# !pip install numpy matplotlib torch==1.7.0+cpu torchvision==0.8.1+cpu torchaudio==0.7.0 -f https://download.pytorch.org/whl/torch_stable.html
# Linux / Windows (GPU)
# pip install torch==1.7.1+cu110 torchvision==0.8.2+cu110 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html
# MacOS (NO GPU)
# !pip install numpy matplotlib torch torchvision torchaudio
!pip install opendatasets --upgradeRequirement already up-to-date: opendatasets in /usr/local/lib/python3.6/dist-packages (0.1.10)
Requirement already satisfied, skipping upgrade: tqdm in /usr/local/lib/python3.6/dist-packages (from opendatasets) (4.41.1)
Requirement already satisfied, skipping upgrade: kaggle in /usr/local/lib/python3.6/dist-packages (from opendatasets) (1.5.10)
Requirement already satisfied, skipping upgrade: click in /usr/local/lib/python3.6/dist-packages (from opendatasets) (7.1.2)
Requirement already satisfied, skipping upgrade: requests in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (2.23.0)
Requirement already satisfied, skipping upgrade: urllib3 in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (1.24.3)
Requirement already satisfied, skipping upgrade: certifi in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (2020.12.5)
Requirement already satisfied, skipping upgrade: python-slugify in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (4.0.1)
Requirement already satisfied, skipping upgrade: python-dateutil in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (2.8.1)
Requirement already satisfied, skipping upgrade: six>=1.10 in /usr/local/lib/python3.6/dist-packages (from kaggle->opendatasets) (1.15.0)
Requirement already satisfied, skipping upgrade: chardet<4,>=3.0.2 in /usr/local/lib/python3.6/dist-packages (from requests->kaggle->opendatasets) (3.0.4)
Requirement already satisfied, skipping upgrade: idna<3,>=2.5 in /usr/local/lib/python3.6/dist-packages (from requests->kaggle->opendatasets) (2.10)
Requirement already satisfied, skipping upgrade: text-unidecode>=1.3 in /usr/local/lib/python3.6/dist-packages (from python-slugify->kaggle->opendatasets) (1.3)
import os
import opendatasets as od
import numpy as np
import torch
import torchvision
from torch.utils.data import random_split
from torch.utils.data.dataloader import DataLoader
import torch.nn as nn
import torch.nn.functional as F
from torchvision.datasets.utils import download_url
from torchvision.datasets import ImageFolder
from torchvision.transforms import ToTensor
from torchvision.utils import make_grid
import matplotlib
import matplotlib.pyplot as plt
%matplotlib inline
matplotlib.rcParams['figure.facecolor'] = '#ffffff'project_name='zerotogans-project-intel-image-classification'
Rocío Cruz Linares7 months ago