test

supervision/draw/utils.py

@@ -1,3 +1,4 @@
+import os
 from typing import Optional, Union
 
 import cv2
@@ -171,40 +172,59 @@ def draw_text(
 
 
 def draw_image(
-    scene: np.ndarray, image: Union[str, np.ndarray], opacity: float, rect: Rect
+    scene: np.ndarray,
+    image: Union[str, np.ndarray],
+    opacity: float,
+    rect: Rect
 ) -> np.ndarray:
     """
     Draws an image onto a given scene with specified opacity and dimensions.
+
+    Args:
+        scene (np.ndarray): Background image where the new image will be drawn.
+        image (Union[str, np.ndarray]): Image to draw.
+        opacity (float): Opacity of the image to be drawn.
+        rect (Rect): Rectangle specifying where to draw the image.
+
+    Returns:
+        np.ndarray: The updated scene.
+
+    Raises:
+        FileNotFoundError: If the image path does not exist.
+        ValueError: For invalid opacity or rectangle dimensions.
     """
 
-    # Load image if a path is provided
+    # Validate and load image
     if isinstance(image, str):
+        if not os.path.exists(image):
+            raise FileNotFoundError(f"Image path ('{image}') does not exist.")
         image = cv2.imread(image, cv2.IMREAD_UNCHANGED)
 
-    # Resize the image
+    # Validate opacity
+    if not 0.0 <= opacity <= 1.0:
+        raise ValueError("Opacity must be between 0.0 and 1.0.")
+
+    # Validate rectangle dimensions
+    if rect.x < 0 or rect.y < 0 or \
+            rect.x + rect.width > scene.shape[1] or rect.y + rect.height > scene.shape[
+        0]:
+        raise ValueError("Invalid rectangle dimensions.")
+
+    # Resize and isolate alpha channel
     image = cv2.resize(image, (rect.width, rect.height))
+    alpha_channel = image[:, :, 3] if image.shape[2] == 4 else np.ones(
+        (rect.height, rect.width), dtype=image.dtype) * 255
+    alpha_scaled = cv2.convertScaleAbs(alpha_channel * opacity)
 
-    # Separate the alpha channel if present
-    if image.shape[2] == 4:
-        alpha_channel = image[:, :, 3]
-        image = image[:, :, :3]
-    else:
-        alpha_channel = np.ones((rect.height, rect.width), dtype=np.uint8) * 255
+    # Perform blending
+    scene_roi = scene[rect.y:rect.y + rect.height, rect.x:rect.x + rect.width]
+    alpha_float = alpha_scaled.astype(np.float32) / 255.0
+    blended_roi = cv2.convertScaleAbs(
+        (1 - alpha_float[..., np.newaxis]) * scene_roi + alpha_float[
+            ..., np.newaxis] * image[:, :, :3]
+    )
 
-    # Apply opacity to the alpha channel
-    alpha_channel = cv2.convertScaleAbs(alpha_channel * opacity)
-
-    # Get the ROI from the scene
-    scene_roi = scene[rect.y : rect.y + rect.height, rect.x : rect.x + rect.width]
-
-    # Manually apply alpha blending
-    alpha_float = alpha_channel.astype(np.float32) / 255.0
-    blended_roi = (
-        (1.0 - alpha_float[..., np.newaxis]) * scene_roi.astype(np.float32)
-    ) + (alpha_float[..., np.newaxis] * image.astype(np.float32))
-    blended_roi = blended_roi.astype(np.uint8)
-
-    # Insert blended ROI back into the scene
-    scene[rect.y : rect.y + rect.height, rect.x : rect.x + rect.width] = blended_roi
+    # Update the scene
+    scene[rect.y:rect.y + rect.height, rect.x:rect.x + rect.width] = blended_roi
 
     return scene