Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,17 +1,26 @@
-import streamlit as st
 import cv2
 import numpy as np
+import streamlit as st
+from streamlit_webrtc import webrtc_streamer, VideoTransformerBase
+
+st.title("Live Fault Detection in Utility Poles")
+
+class FaultDetector(VideoTransformerBase):
+    def transform(self, frame):
+        img = frame.to_ndarray(format="bgr24")
+
+        # Convert to grayscale
+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
 
-st.title("OpenCV Image Display Example")
+        # Apply Gaussian blur
+        blurred = cv2.GaussianBlur(gray, (5, 5), 0)
 
-# Create a black image
-image = np.zeros((200, 200, 3), dtype=np.uint8)
+        # Perform Canny edge detection
+        edges = cv2.Canny(blurred, 50, 150)
 
-# Draw a red circle
-cv2.circle(image, (100, 100), 50, (0, 0, 255), -1)
+        # Convert edges to 3-channel image
+        edges_colored = cv2.cvtColor(edges, cv2.COLOR_GRAY2BGR)
 
-# Convert BGR to RGB
-image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+        return edges_colored
 
-# Display the image in Streamlit
-st.image(image_rgb, caption="Red Circle", use_column_width=True)
+webrtc_streamer(key="fault_detection", video_transformer_factory=FaultDetector)