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Created 4 years ago
Human Protein Multi Label Image Classification
This is a starter notebook for the competition Zero to GANs - Human Protein 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
import torchvision.transforms as transforms
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
Exploring the Data
When you create a notebook with the "Notebooks" tab of a Kaggle competition, the data is automatically included in the ../input
folder. You can explore the files in the sidebar. Let us create some constants 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.