Create app.py

app.py

@@ -0,0 +1,29 @@
+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)