Image Classification Using ResNets

Deep Learning Course Project

I have used intel-image-classification dataset for this course project. It has classes like of images like buildings, forest, glacier, mountain, sea, street each containing images of shape of 150 x 150 pixels. The task is to classify this images and train a model to predict any previously unseen images which belongs to one of these classes with max accuracy using deep neural network, CNN and ResNets (Here, ResNet9).

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First the necessary imports!

# !pip install jovian --upgrade --quiet

import os
import torch
import jovian
import torchvision
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from torch.utils.data import random_split
from torchvision.transforms import ToTensor
from torchvision.datasets import ImageFolder
from torchvision.utils import make_grid

project_name = "deep-learning-course-project-resnet"