Create app.py

app.py

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+import streamlit as st
+import cv2
+from PIL import Image
+import time
+import numpy as np
+
+# Placeholder function for analyzing images and returning descriptions
+def analyze_image(image):
+    # Implement object recognition here
+    # This function should return a list of descriptions for detected objects
+    # For example:
+    return ["chair on the left", "table in the center", "cat on the right"]
+
+def main():
+    st.title("Object Recognition Assistant for the Visually Impaired")
+
+    # Setup webcam capture
+    cap = cv2.VideoCapture(0)  # Use 0 for the default webcam
+
+    FRAME_WINDOW = st.image([])
+    last_time = time.time()
+
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            continue
+
+        # Convert the image color to RGB
+        frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        img = Image.fromarray(frame)
+
+        # Display the current frame
+        FRAME_WINDOW.image(img)
+
+        # Check if 10 seconds have passed
+        if time.time() - last_time > 10:
+            last_time = time.time()
+
+            # Analyze the image and get descriptions
+            descriptions = analyze_image(img)
+
+            # Display the descriptions
+            st.write("Detected objects:")
+            for desc in descriptions:
+                st.write("- " + desc)
+
+        time.sleep(0.1)
+
+if __name__ == "__main__":
+    main()