parse image path from argument

test.py

@@ -1,10 +1,16 @@
+#!/usr/bin/env python3
+
+import sys
+
 from ultralytics import YOLO
 
+image_path = sys.argv[1]
+
 # Load the small pretrained YOLOv8 object-detection model.
 model = YOLO("yolov8n.pt")
 
 # Run object detection on a test image.
-results = model("bus4.jpg")
+results = model(image_path)
 
 has_bus = False
 max_confidence = 0.0
@@ -13,7 +19,7 @@ for result in results:
     class_names = result.names
     detected_classes = result.boxes.cls.tolist()
     confidences = result.boxes.conf.tolist()
-    
+
     # Check each detected object and its matching confidence score
     for cls_id, conf in zip(detected_classes, confidences):
         if class_names[int(cls_id)] == "bus":