Update app.py

app.py

@@ -5,22 +5,22 @@ import requests
 from flask import Flask, render_template, request, jsonify
 from ultralytics import YOLO
 from datetime import datetime
+import threading
 
 app = Flask(__name__)
 
 # --- CONFIGURATION ---
-# PASTE YOUR MICROMIND API URL HERE (The one ending in /prediction/...)
 MICROMIND_API_URL = "https://training.aimicromind.com/api/v1/prediction/606f1092-e94c-42f8-ba6f-09671904a15e"
 
-# GLOBAL SETTINGS (Controlled by MicroMind Agent later)
+# GLOBAL SETTINGS
 current_settings = {
-    "target_class_id": 0,       # 0 = person
+    "target_class_id": 0,
     "target_label": "person",
     "confidence": 0.5,
     "status": "ARMED"
 }
 
-# Load AI Model (Runs once when server starts)
+# Load AI Model
 print("--- Loading AI Model... ---")
 try:
     model = YOLO('yolov8n.pt')
@@ -28,6 +28,15 @@ try:
 except Exception as e:
     print(f"⚠️ Model download/load warning: {e}")
 
+# Alert sender function
+def send_alert(alert_msg):
+    """Sends alert in background - fully non-blocking."""
+    try:
+        requests.post(MICROMIND_API_URL, json={"question": alert_msg}, timeout=5)
+        print(f"✅ Alert sent to MicroMind")
+    except Exception as e:
+        print(f"⚠️ Alert sending failed: {e}")
+
 @app.route('/')
 def index():
     """Serves the webpage to the user."""
@@ -46,8 +55,8 @@ def process_frame():
         npimg = np.frombuffer(file, np.uint8)
         img = cv2.imdecode(npimg, cv2.IMREAD_COLOR)
 
-        # 2. Run YOLO AI
-        results = model(img, verbose=False)
+        # 2. Run YOLO AI with optimized settings
+        results = model(img, verbose=False, conf=current_settings['confidence'])
         
         detected = False
         detections_list = []
@@ -59,7 +68,7 @@ def process_frame():
                 conf = float(box.conf[0])
                 
                 # Check against current settings
-                if cls_id == current_settings['target_class_id'] and conf > current_settings['confidence']:
+                if cls_id == current_settings['target_class_id']:
                     detected = True
                     detections_list.append({
                         "label": current_settings['target_label'],
@@ -67,7 +76,7 @@ def process_frame():
                         "bbox": box.xyxy[0].tolist()
                     })
 
-        # 4. Alert MicroMind (Fire and Forget)
+        # 4. Alert MicroMind (Fully Non-blocking)
         if detected:
             print(f"🚨 THREAT: {current_settings['target_label']} detected!")
             
@@ -75,11 +84,11 @@ def process_frame():
                          f"Source: Cloud Web Cam\n"
                          f"Confidence: {detections_list[0]['confidence']}")
             
-            try:
-                # Send alert to Agent (Timeout is short to keep video smooth)
-                requests.post(MICROMIND_API_URL, json={"question": alert_msg}, timeout=0.5)
-            except:
-                pass 
+            # Send alert in separate thread - fully fire-and-forget
+            threading.Thread(
+                target=lambda: send_alert(alert_msg),
+                daemon=True
+            ).start()
 
         return jsonify({
             "status": "ARMED",
@@ -121,6 +130,5 @@ def update_settings():
     return jsonify({"status": "success", "current_state": current_settings})
 
 if __name__ == '__main__':
-    # Hugging Face Spaces sets PORT env var to 7860
     port = int(os.environ.get("PORT", 7860))
     app.run(host='0.0.0.0', port=port)