Image recognition

index.py

@@ -2,67 +2,85 @@ import streamlit as st
 import cv2
 import os
 
+# Create a folder to save captured images
+if not os.path.exists("captured_images"):
+    os.makedirs("captured_images")
+
 def main():
-    st.title('NouriScan')
+    st.title('Image Capture App')
 
     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()
-    else:
+    if button_clicked:
         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."}
-    ]
-
-    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()
 
+    # Button to capture image
     if st.button("Capture Image"):
+        capture_image(cap)
+
+    while True:
         # Read a frame from the webcam
         ret, frame = cap.read()
 
         if not ret:
             st.error("Error: Unable to read frame from the webcam.")
-        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)
+            break
 
-            # Display the captured image
-            st.image(image_path, use_column_width=True)
+        # Display the frame in the Streamlit app
+        video_placeholder.image(cv2.cvtColor(frame, cv2.COLOR_BGR2RGB), channels="RGB", use_column_width=True)
 
     # Release the VideoCapture and close the OpenCV window
     cap.release()
-    cv2.destroyAllWindows()
+
+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."}
+    ]
+
+    # Display the items with expanding boxes
+    for item in items:
+        with st.expander(item["title"]):
+            st.write(item["content"])
+
+
+
+def capture_image(cap):
+    # Read a frame from the webcam
+    ret, frame = cap.read()
+
+    if not ret:
+        st.error("Error: Unable to read frame from the webcam.")
+        return
+
+    # Save the frame as an image
+    image_path = f"captured_images/captured_image_{len(os.listdir('captured_images')) + 1}.jpg"
+    cv2.imwrite(image_path, cv2.cvtColor(frame, cv2.COLOR_BGR2RGB))
+    st.success(f"Image captured and saved as {image_path}")
 
 if __name__ == '__main__':
     main()