app.py

import streamlit as st
from io import StringIO
from PIL import Image
import pandas as pd
import numpy as np
import glob
import os

import torch
import torch.nn as nn
from torch.utils.data import Dataset, DataLoader
import torchvision.models as models
from torchinfo import summary

from sklearn.model_selection import StratifiedKFold
from sklearn.metrics import accuracy_score

from tqdm import tqdm
import cv2
import albumentations as A # Albumentations is a computer vision tool that boosts the performance of deep convolutional neural networks. (https://albumentations.ai/)
import matplotlib.pyplot as plt
import seaborn as sns
from albumentations.pytorch.transforms import ToTensorV2

st.title("some big ML function")

uploaded_file = st.file_uploader("Choose a file")

if uploaded_file is not None:
  if ".jpg" in uploaded_file.name or ".png" in uploaded_file.name:
    image = Image.open(uploaded_file)
    st.image(image)  #show it
    
  elif ".csv" in uploaded_file.name:
    dataframe = pd.read_csv(uploaded_file)
    st.write(dataframe)