app.py

import streamlit as st
import cv2
import numpy as np
from PIL import Image
import torch

def load_image(image_file):
    img = Image.open(image_file)
    return img

def process_image(image):
    image_cv = np.array(image.convert('RGB'))
    image_cv = cv2.cvtColor(image_cv, cv2.COLOR_RGB2BGR)
    unsam_plus_output = image_cv  # Replace with UNSAM+ processing
    unsam_output = image_cv  # Replace with UNSAM processing
    return unsam_plus_output, unsam_output

st.title("UNSAM Image Processing")

image_file = st.file_uploader("Upload an Image", type=["png", "jpg", "jpeg"])

if image_file is not None:
    original_image = load_image(image_file)
    st.image(original_image, caption="Original Image", use_column_width=True)
    
    unsam_plus_output, unsam_output = process_image(original_image)
    
    st.image(unsam_plus_output, caption="UNSAM+ Output", use_column_width=True)
    st.image(unsam_output, caption="UNSAM Output", use_column_width=True)