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Final project: - Weather Image Classification using CNN in PyTorch.

import os
import torch
import torchvision
import tarfile
from torchvision.datasets.utils import download_url
from torch.utils.data import random_split
project_name='cnn-weather-image-classification'

DataSet Used

For this assignmente the folowing dataset was used:

Multi-class Weather Dataset for Image Classification
Published: 13-09-2018
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Version 1
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DOI:
10.17632/4drtyfjtfy.1
Contributor:
Gbeminiyi Ajayi.
Description.
Multi-class weather dataset(MWD) for image classification is a valuable dataset used in the research paper entitled “Multi-class weather recognition from still image using heterogeneous ensemble method”. The dataset provides a platform for outdoor weather analysis by extracting various features for recognizing different weather conditions.

https://data.mendeley.com/datasets/4drtyfjtfy/1

The original dataset was modified for having a set of 32x32 images, and the same number of samples for each of four classes considered (cloudy, rain, shune and sunrise). This modified dataset can be downloaded from:

https://drive.google.com/file/d/13gxMPYy5saMKp4vrTnPdOb4VzSIRPvCf/view?usp=sharing

from google.colab import drive
drive.mount('/content/gdrive')
Drive already mounted at /content/gdrive; to attempt to forcibly remount, call drive.mount("/content/gdrive", force_remount=True).