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Human Protein Multi Label Image Classification

import os
import torch
import pandas as pd
import numpy as np
from torch.utils.data import Dataset, random_split, DataLoader
from PIL import Image
import torchvision.models as models
import matplotlib.pyplot as plt
from tqdm.notebook import tqdm
import torchvision.transforms as T
from sklearn.metrics import f1_score
import torch.nn.functional as F
import torch.nn as nn
from torchvision.utils import make_grid
%matplotlib inline

Preparing data

Constants to acess the data directories and CSV files.

DATA_DIR = '../input/jovian-pytorch-z2g/Human protein atlas'

TRAIN_DIR = DATA_DIR + '/train'                           # Contains training images
TEST_DIR = DATA_DIR + '/test'                             # Contains test images

TRAIN_CSV = DATA_DIR + '/train.csv'                       # Contains real labels for training images
TEST_CSV = '../input/jovian-pytorch-z2g/submission.csv'   # Contains dummy labels for test image

The train.csv file contains image IDs and labels for training data. Note that this is a multi-label classification problem. Each image can have more than one type of protein.