store new image in processed_image

src/Python/flask/web/app.py

@@ -11,34 +11,36 @@ model = YOLO("yolo11n.pt")  # pretrained YOLO11n model
 
 kobuki_message = ""
 latest_image = None
+processed_image = None
 yolo_results = []
 
-# https://medium.com/@Mert.A/how-to-segment-objects-with-yolov11-68593eb49fa8
+# List of class names (example for COCO dataset)
 yolo_classes = list(model.names.values())
 
 def on_message(client, userdata, message):
-    global kobuki_message, latest_image, yolo_results
+    global kobuki_message, latest_image, processed_image, yolo_results
     if message.topic == "kobuki/data":
         kobuki_message = str(message.payload.decode("utf-8"))
     elif message.topic == "kobuki/cam":
         latest_image = np.frombuffer(message.payload, np.uint8)
         latest_image = cv2.imdecode(latest_image, cv2.IMREAD_COLOR)
+        processed_image = latest_image.copy()  # Create a copy for processing
         # Process the image with YOLO
         results = model(latest_image)
         yolo_results = []
         for result in results:
             for box in result.boxes:
-                class_id = int(box.cls.item()) # Convert to integer
+                class_id = int(box.cls.item())
                 class_name = yolo_classes[class_id]
                 yolo_results.append({
                     "class": class_name,
                     "confidence": box.conf.item(),
                     "bbox": box.xyxy.tolist()
                 })
-                # Draw bounding box on the image
+                # Draw bounding box on the processed image
-                x1, y1, x2, y2 = map(int, box.xyxy[0])
+                x1, y1, x2, y2 = map(int, box.xyxy)
-                cv2.rectangle(latest_image, (x1, y1), (x2, y2), (0, 255, 0), 2)
+                cv2.rectangle(processed_image, (x1, y1), (x2, y2), (0, 255, 0), 2)
-                cv2.putText(latest_image, f"{class_name} {box.conf.item():.2f}", (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
+                cv2.putText(processed_image, f"{class_name} {box.conf.item():.2f}", (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.9, (0, 255, 0), 2)
 
 # Create an MQTT client instance
 mqtt_client = mqtt.Client()
@@ -48,20 +50,21 @@ mqtt_client.loop_start()
 mqtt_client.subscribe("kobuki/data")
 mqtt_client.subscribe("kobuki/cam")
 
-mqtt_client.on_message = on_message # this lines needs to be under the function definition otherwise it cant find which function it needs to use
+mqtt_client.on_message = on_message  # this line needs to be under the function definition otherwise it can't find which function it needs to use
 
 @app.route('/')
 def index():
     return render_template('index.html')
 
 
-@app.route('/control', methods=["GET","POST"])
+@app.route('/control', methods=["GET", "POST"])
 def control():
     if request.authorization and request.authorization.username == 'ishak' and request.authorization.password == 'kobuki':
         return render_template('control.html')
     else:
         return ('Unauthorized', 401, {'WWW-Authenticate': 'Basic realm="Login Required"'})
 
+
 @app.route('/move', methods=['POST'])
 def move():
     data = request.get_json()
@@ -78,19 +81,22 @@ def move():
 def data():
     return kobuki_message
 
+
 @app.route('/image')
 def image():
-    global latest_image
+    global processed_image
-    if latest_image is not None:
+    if processed_image is not None:
-        _, buffer = cv2.imencode('.jpg', latest_image)
+        _, buffer = cv2.imencode('.jpg', processed_image)
         return Response(buffer.tobytes(), mimetype='image/jpeg')
     else:
         return "No image available", 404
 
+
 @app.route('/yolo_results', methods=['GET'])
 def yolo_results_endpoint():
     global yolo_results
     return jsonify(yolo_results)
 
+
 if __name__ == '__main__':
     app.run(debug=True, port=5000)