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Classifying Pokemon images using PyTorch

In thie project we will apply machine learning on Pokemon images.
The goal is to identify pokemon name from images.

Data source1: Kaggle Pokemon Image Dataset
Source zip file contains image of 149 first generation pokemon images.

We will seperate dataset into train and val dataset.

For testing dataset, we will use random pic from google image. In this project we will use a GPU for faster training

project_name = 'course-project-pokemon-classification'
import warnings
import os
import torch
import torchvision
import tarfile
import math
import torch.nn as nn
import numpy as np
import pandas as pd
import torch.nn.functional as F
import PIL
from numpy import genfromtxt
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
import shutil
%matplotlib inline

matplotlib.rcParams['figure.facecolor'] = '#ffffff'

Downloading and Exploring the Data

We can use the opendatasets library to download the dataset from Kaggle.

!pip install opendatasets --upgrade --quiet