import streamlit as st
import numpy as np
from PIL import Image
 
def main():
    st.title("Haltmann Diffusion Algorithm")
 
    slider = st.slider("Slider", 0, 255, 128) # default value=128, min=0, max=255
    st.title("Haltmann Diffusion Algorithm [C] 20XX ")
 
 

import streamlit as st

from PIL import Image

import numpy as np

 
def inpaint(img, mask):

    """Inpaints the given image using the given mask.

 

    Args:

        img: The image to inpaint. Must be a 3-channel RGB image.

        mask: The inpainting mask. Must be a binary 3-channel image 

            with 1s indicating the area to inpaint and 0s indicating 

            the area to leave unchanged.

 

    Returns:

        The inpainted image as a 3-channel RGB numpy array.     """
## V0.2
import streamlit as st
import numpy as np
from PIL import Image
import requests
import io


st.set_option('deprecation.showfileUploaderEncoding', False)


@st.cache(allow_output_mutation=True)
def load_image(img):
    im = Image.open(img)
    return im

    
def main():

    st.title("Dall-E Flow")

    uploaded_file = st.file_uploader("Choose an image", type="jpg")

st.markdown("Create images from textual descriptions with Dall-E!")
st.button("Edit Photo")


## [C] Haltmann Earth Divison 


import streamlit as st
import numpy as np
from PIL import Image, ImageDraw
from inpainting import HaltmannInpainter

 
st.set_option('deprecation.showfileUploaderEncoding', False)

 
def main():

    # Load the image and initialize the inpainter.    
    image = st.file_uploader("Choose an image", type=["png", "jpg"])

    if image is not None:        
        inpainter = HaltmannInpainter()        

        # Get the dimensions of the uploaded image.        
        width, height = Image.open(image).size        

        # Resize the uploaded image if it is too large for our model (> 512x512).        
        if width > 512 or height > 512:            
            max_dim = max(width, height)            

            resize_factor = 512 / max_dim            

            width, height = int(width * resize_factor), int(height * resize_factor)            
@st.cache
def load_image(image): 
    image = np.array(Image.open(image))
    return image                 

        # Inpaint!