ashhadulislam

import streamlit as st
from lib import commons
import torch

def app():
    header=st.container()
    result_all = st.container()
    with header:
        st.subheader("Test whether an area is affected by any natural disaster")
        image_file = st.file_uploader("Upload Images", type=["png","jpg","jpeg"])

ashhadulislam

import streamlit as st
from lib import commons

def app():
    header=st.container()
    with header:
        st.subheader("Test whether an area is affected by any natural disaster")
        image_file = st.file_uploader("Upload Images", type=["png","jpg","jpeg"])
        if image_file is not None:
            # To See details

ashhadulislam

import streamlit as st
from lib import commons

def app():
    header=st.container()
    with header:
        st.subheader("Test whether an area is affected by any natural disaster")
        proxy_img_file="data/joplin-tornado_00000001_post_disaster.png"
        st.image(commons.load_image(proxy_img_file),width=250)
        image_for_model=commons.image_loader(proxy_img_file)

ashhadulislam

import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data.sampler import SubsetRandomSampler
from torch.utils.data import DataLoader
from torchvision import datasets, transforms
import torch.nn as nn
import torch.nn.functional as F

ashhadulislam

import os
import streamlit as st
import numpy as np
from PIL import  Image

# Custom imports 
from multipage import MultiPage

from pages import disasterAnalysis
# Create an instance of the app 

ashhadulislam

import streamlit as st

def app():
    header=st.container()
    with header:
	    st.subheader("Test whether an area is affected by any natural disaster")

ashhadulislam

import os
import streamlit as st
import numpy as np
from PIL import  Image
# Custom imports 
from multipage import MultiPage

# Create an instance of the app 
app = MultiPage()

ashhadulislam

import os
import streamlit as st
import numpy as np
from PIL import  Image
# Custom imports 
from multipage import MultiPage

# Create an instance of the app 
app = MultiPage()

ashhadulislam

"""
This file is the framework for generating multiple Streamlit applications 
through an object oriented framework. 
"""

# Import necessary libraries 
import streamlit as st

# Define the multipage class to manage the multiple apps in our program 
class MultiPage: 

ashhadulislam

# read an image
from PIL import Image
from torch.autograd import Variable

loader = transforms.Compose([transforms.Resize(dim[0]), 
                             transforms.ToTensor(),
                            transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])

def image_loader(image_name):
    """load image, returns cuda tensor"""