Update app.py

app.py

@@ -1,15 +1,18 @@
-import streamlit as st
+import gradio as gr
 import cv2
 from llm import llm
 import numpy as np
-image = st.file_uploader("Choose a Clear Image of the Neutrition Facts Table", type=["jpg", "jpeg", "png"])
 
-# Display the uploaded image
-if image is not None:
-    image = np.asarray(bytearray(image.read()), dtype=np.uint8)
-        
-        # Read the image using OpenCV
-    img = cv2.imdecode(image, cv2.IMREAD_COLOR)
-    st.image(img, caption="Uploaded Image.", use_column_width=True)
+def process_image(image):
+    # Convert Gradio Image to OpenCV format
+    img = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
+    
+    # Perform your image processing
+    result = llm(img)
 
-    st.markdown(llm(img))
+    return result
+
+iface = gr.Interface(fn=process_image, inputs="image", outputs=gr.Markdown(), live=True, title="Nutrition Content Based LLM", description="The llm based project needs a clear image of only the Nutrition Facts Box at the back of a product, \n The llm shows the content and give health advice based on the Nutritions Facts.")
+
+
+iface.launch()