Create app.py

app.py

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+import streamlit as st
+import cv2
+from services.video_service import process_video
+from services.detection_service import detect_faults_solar, detect_faults_windmill
+from services.thermal_service import detect_hotspots
+from services.shadow_detection import detect_shadows
+from PIL import Image
+import numpy as np
+
+# Load models for solar and windmill detection
+from models.solar_model import load_solar_model
+from models.windmill_model import load_windmill_model
+
+def main():
+    st.title("Solar Panel and Windmill Fault Detection")
+    
+    # Upload video file
+    uploaded_file = st.file_uploader("Upload a Video (MP4 or AVI)", type=["mp4", "avi"])
+
+    if uploaded_file is not None:
+        video_path = "/tmp/" + uploaded_file.name
+        with open(video_path, "wb") as f:
+            f.write(uploaded_file.read())
+
+        # Open the video using OpenCV
+        cap = cv2.VideoCapture(video_path)
+        
+        # Check if video was opened successfully
+        if not cap.isOpened():
+            st.error("Error opening video stream or file")
+            return
+        
+        # Process frames in real-time
+        stframe = st.empty()
+        
+        # Choose fault detection type
+        choice = st.selectbox("Choose Fault Detection", ["Solar Panel", "Windmill"])
+        model = None
+        
+        if choice == "Solar Panel":
+            model = load_solar_model()
+        else:
+            model = load_windmill_model()
+
+        while cap.isOpened():
+            ret, frame = cap.read()
+            if not ret:
+                break
+
+            # Convert the frame to RGB (Streamlit uses RGB)
+            frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+
+            # Preprocess the frame and detect faults
+            faults = detect_faults_solar(model, frame_rgb) if choice == "Solar Panel" else detect_faults_windmill(model, frame_rgb)
+
+            # Show faults on the frame
+            for fault in faults:
+                # For example, draw bounding boxes for faults on the frame
+                x, y = int(fault['location'][0]), int(fault['location'][1])
+                cv2.putText(frame, f"Fault: {fault['type']}", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 0, 255), 2)
+                cv2.rectangle(frame, (x-20, y-20), (x+80, y+40), (0, 0, 255), 2)
+
+            # Update the live feed with the processed frame
+            stframe.image(frame_rgb, channels="RGB", use_column_width=True)
+
+        cap.release()
+
+if __name__ == "__main__":
+    main()