Image recognition

index.py

@@ -1,76 +1,68 @@
 import streamlit as st
 import cv2
-# import pandas as pd
-# import numpy as np
+import os
+
 def main():
     st.title('NouriScan')
 
     st.sidebar.header('Ingredients & Nutrition')
     
-
     option1 = st.sidebar.checkbox('Banana')
     option2 = st.sidebar.checkbox('Strawberry')
     option3 = st.sidebar.checkbox('Kale')
     option4 = st.sidebar.checkbox('Orange Juice')
     option5 = st.sidebar.checkbox('Almond Milk')
+    
     button_clicked = st.sidebar.button('Done')
+    
     if not button_clicked:
         videoCapture()
-    if button_clicked:
+    else:
         displayRecipes()
 
 def displayRecipes():
     items = [
-    {"title": "Item 1", "content": "Content for Item 1."},
-    {"title": "Item 2", "content": "Content for Item 2."},
-    {"title": "Item 3", "content": "Content for Item 3."}
+        {"title": "Item 1", "content": "Content for Item 1."},
+        {"title": "Item 2", "content": "Content for Item 2."},
+        {"title": "Item 3", "content": "Content for Item 3."}
     ]
 
-    # Display the items with expanding boxes
     for item in items:
         with st.expander(item["title"]):
             st.write(item["content"])
 
-    
-
 def videoCapture():
-    
-    # Create a VideoCapture object to access the webcam
     cap = cv2.VideoCapture(0)
-
-    # Set the video frame width and height (optional)
     cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
     cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)
 
-    # Check if the webcam is opened correctly
     if not cap.isOpened():
         st.error("Error: Unable to access the webcam.")
         return
 
+    st.write("Click 'Capture Image' to capture an image.")
+
     # Display a placeholder for the video stream
     video_placeholder = st.empty()
 
-    while True:
+    if st.button("Capture Image"):
         # Read a frame from the webcam
         ret, frame = cap.read()
 
         if not ret:
             st.error("Error: Unable to read frame from the webcam.")
-            break
-
-        # Display the frame in the Streamlit app
-        video_placeholder.image(frame, channels="BGR", use_column_width=True)
+        else:
+            # Save the captured frame as an image
+            image_path = "captured_image.jpg"
+            cv2.imwrite(image_path, cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
+            st.write("Image captured and saved as", image_path)
 
-        # Check if the user pressed the 'q' key to quit
-        if cv2.waitKey(1) & 0xFF == ord('q'):
-            break
+            # Display the captured image
+            st.image(image_path, use_column_width=True)
 
     # Release the VideoCapture and close the OpenCV window
     cap.release()
     cv2.destroyAllWindows()
-    
-
-
 
 if __name__ == '__main__':
-    main()
+    main()