add spacing

src/super_gradients/training/utils/visualization/classification.py

@@ -2,12 +2,8 @@
 import numpy as np
 
 
-def draw_label(image: np.ndarray, label: str, confidence: float) -> np.ndarray:
-    """Draw a label and confidence on an image.
-    :param image:       The image on which to draw the label and confidence, in RGB format, and Channel Last (H, W, C)
-    :param label:       The label to draw.
-    :param confidence:  The confidence of the label.
-    """
+def draw_label(image: np.ndarray, label: str, confidence: str) -> np.ndarray:
+    """Draw a label and confidence on an image."""
 
     # Format confidence as a percentage
     confidence_str = f"{confidence * 100:.3f}%"
@@ -16,13 +12,16 @@ def draw_label(image: np.ndarray, label: str, confidence: float) -> np.ndarray:
     fontScale = 0.8
     thickness = 1
 
+    # Define additional spacing between the two lines
+    line_spacing = 5
+
     # Determine the size of the label and confidence text
     label_size = cv2.getTextSize(label, cv2.FONT_HERSHEY_SIMPLEX, fontScale, thickness)[0]
     confidence_size = cv2.getTextSize(confidence_str, cv2.FONT_HERSHEY_SIMPLEX, fontScale, thickness)[0]
 
     # Determine the size of the bounding rectangle
     text_width = max(label_size[0], confidence_size[0])
-    text_height = label_size[1] + confidence_size[1] + thickness * 3
+    text_height = label_size[1] + confidence_size[1] + thickness * 3 + line_spacing
 
     # Calculate the position to draw the label, centered horizontally and at the top
     start_x = (image.shape[1] - text_width) // 2
@@ -38,7 +37,7 @@ def draw_label(image: np.ndarray, label: str, confidence: float) -> np.ndarray:
     alpha = 0.6
     cv2.addWeighted(overlay, alpha, image, 1 - alpha, 0, image)
 
-    # Center the label and confidence text within the bounding rectangle
+    # Center the label and confidence text within the bounding rectangle, with additional spacing
     text_color = (0, 0, 0)  # Black
     cv2.putText(
         image,
@@ -53,7 +52,7 @@ def draw_label(image: np.ndarray, label: str, confidence: float) -> np.ndarray:
     cv2.putText(
         image,
         confidence_str,
-        (start_x + (text_width - confidence_size[0]) // 2, start_y + label_size[1] + confidence_size[1] + thickness),
+        (start_x + (text_width - confidence_size[0]) // 2, start_y + label_size[1] + confidence_size[1] + thickness + line_spacing),
         cv2.FONT_HERSHEY_SIMPLEX,
         fontScale,
         text_color,