Spacing

Co-authored-by: aider (gemini/gemini-2.5-pro-preview-05-06) <aider@aider.chat>

server.py

@@ -4,6 +4,7 @@ from aiohttp import web
 import logging
 import os
 import io
+from datetime import datetime
 
 import torch
 import torch.nn.functional as F
@@ -25,6 +26,9 @@ MODEL_PATH = 'garage_door_cnn.pth'
 CLASS_NAMES = ['closed', 'open'] # From training, sorted alphabetically
 POLL_INTERVAL_SECONDS = 10
 REQUEST_TIMEOUT_SECONDS = 5
+UNSURE_CONFIDENCE_THRESHOLD = 0.97
+PREDICTION_HISTORY = []
+PREDICTION_HISTORY_MAX_LENGTH = 3
 
 # --- Model Inference ---
 def get_prediction(model, image_bytes, device):
@@ -71,13 +75,46 @@ async def monitor_garage_door(app):
                     if result:
                         prediction, confidence = result
                         logging.debug(f"Garage door status: {prediction} (confidence: {confidence:.4f})")
+
+                        # Update prediction history
+                        if confidence >= UNSURE_CONFIDENCE_THRESHOLD:
+                            PREDICTION_HISTORY.append(prediction)
+                        else:
+                            PREDICTION_HISTORY.append('unknown')
+                        
+                        # Trim history if it's too long
+                        if len(PREDICTION_HISTORY) > PREDICTION_HISTORY_MAX_LENGTH:
+                            PREDICTION_HISTORY.pop(0)
+
+                        if confidence < UNSURE_CONFIDENCE_THRESHOLD:
+                            # Sanitize timestamp for use in filename
+                            timestamp = datetime.now().isoformat().replace(':', '-')
+                            filename = f"{timestamp}.jpg"
+                            
+                            # Construct path and save file
+                            unsure_dir = os.path.join('data', 'unsure', prediction)
+                            os.makedirs(unsure_dir, exist_ok=True)
+                            filepath = os.path.join(unsure_dir, filename)
+                            
+                            with open(filepath, 'wb') as f:
+                                f.write(image_bytes)
+                            
+                            logging.info(f"Low confidence prediction: {prediction} ({confidence:.4f}). Saved for review: {filepath}")
                 else:
                     logging.error(f"Failed to fetch image. Status: {response.status}, Reason: {response.reason}")
 
         except asyncio.TimeoutError:
             logging.warning("Request to camera timed out.")
+
+            PREDICTION_HISTORY.append('unknown')
+            if len(PREDICTION_HISTORY) > PREDICTION_HISTORY_MAX_LENGTH:
+                PREDICTION_HISTORY.pop(0)
         except aiohttp.ClientError as e:
             logging.error(f"Client error during image fetch: {e}")
+
+            PREDICTION_HISTORY.append('unknown')
+            if len(PREDICTION_HISTORY) > PREDICTION_HISTORY_MAX_LENGTH:
+                PREDICTION_HISTORY.pop(0)
         except asyncio.CancelledError:
             logging.info("Monitoring task cancelled.")
             break
@@ -92,6 +129,18 @@ async def handle_root(request):
     """Handler for the root GET request."""
     return web.Response(text="hello world")
 
+async def handle_state(request):
+    """Handler for the /state GET request."""
+    state = "unknown"
+
+    if len(PREDICTION_HISTORY) == PREDICTION_HISTORY_MAX_LENGTH:
+        if all(s == "open" for s in PREDICTION_HISTORY):
+            state = "open"
+        elif all(s == "closed" for s in PREDICTION_HISTORY):
+            state = "closed"
+
+    return web.Response(text=state)
+
 async def on_startup(app):
     """Actions to perform on application startup."""
     # Set up device
@@ -126,6 +175,7 @@ async def on_cleanup(app):
 def main():
     app = web.Application()
     app.router.add_get('/', handle_root)
+    app.router.add_get('/state', handle_state)
     app.on_startup.append(on_startup)
     app.on_cleanup.append(on_cleanup)
     web.run_app(app, port=8081)