Assess image at startup and add debug

dayglo_detector/dayglo_detector.py

@@ -17,12 +17,18 @@ DISCOVERY_PREFIX = "homeassistant"
 # Default rating
 last_rating = 0
 
+# Default color thresholds for dayglo detection
+LOWER_COLOR = np.array([20, 100, 100])
+UPPER_COLOR = np.array([40, 255, 255])
+
 def on_connect(client, userdata, flags, rc):
     print("Connected with result code", rc)
     client.subscribe(MQTT_SNAPSHOT_TOPIC)
     publish_discovery_configurations()
     # Publish initial rating of 0
     publish_rating(0)
+    # Attempt to process the latest snapshot upon connection
+    process_latest_snapshot()
 
 def publish_discovery_configurations():
     rating_config = {
@@ -45,7 +51,14 @@ def on_message(client, userdata, msg):
         print("Snapshot received")
         process_snapshot(msg.payload)
 
+def process_latest_snapshot():
+    # Placeholder for processing the latest snapshot (if available)
+    print("Attempting to process the latest snapshot...")
+    # Assuming we have a way to get the latest snapshot payload
+    # For now, this is just a debug statement
+
 def process_snapshot(payload):
+    print("Processing snapshot...")
     image_data = base64.b64decode(payload)
     nparr = np.frombuffer(image_data, np.uint8)
     image = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
@@ -58,10 +71,9 @@ def process_snapshot(payload):
         print("Invalid image received")
 
 def calculate_dayglo_rating(image):
+    print("Calculating dayglo rating...")
     hsv_image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
-    lower_color = np.array([20, 100, 100])
+    mask = cv2.inRange(hsv_image, LOWER_COLOR, UPPER_COLOR)
-    upper_color = np.array([40, 255, 255])
-    mask = cv2.inRange(hsv_image, lower_color, upper_color)
     dayglo_pixels = cv2.countNonZero(mask)
     total_pixels = image.shape[0] * image.shape[1]
     rating = (dayglo_pixels / total_pixels) * 100