fixed rgb issue

utils.py

@@ -18,7 +18,7 @@ def plot_predictions(
     ) -> np.ndarray:
 
     image_source = cv2.imread(image)
-    image_source = cv2.cvtColor(image_source, cv2.COLOR_BGR2RGB)
+    image_source_rgb = cv2.cvtColor(image_source, cv2.COLOR_BGR2RGB)
 
     boxes = sv.Detections(xyxy=boxes)
 
@@ -28,7 +28,7 @@ def plot_predictions(
         in zip(labels, scores)
     ]
 
-    height, width, _ = image_source.shape
+    height, width, _ = image_source_rgb.shape
     thickness = math.ceil(width/200)
     text_scale = width/1500
     text_thickness = math.ceil(text_scale*1.5)
@@ -37,20 +37,18 @@ def plot_predictions(
     label_annotator = sv.LabelAnnotator(color_lookup=sv.ColorLookup.INDEX, text_scale=text_scale, text_thickness=text_thickness)
 
     # Create a semi-transparent overlay
-    overlay = image_source.copy()
+    overlay = image_source_rgb.copy()
 
     # Apply bounding box annotations to the overlay
     overlay = bbox_annotator.annotate(scene=overlay, detections=boxes)
     overlay = label_annotator.annotate(scene=overlay, detections=boxes, labels=labels)
 
-    # annotated_frame = cv2.cvtColor(image_source, cv2.COLOR_RGB2BGR)
-    # annotated_frame = bbox_annotator.annotate(scene=annotated_frame, detections=boxes)
-    # annotated_frame = label_annotator.annotate(scene=annotated_frame, detections=boxes, labels=labels)
-
     # Blend overlay with original image using the specified opacity
-    annotated_frame = cv2.addWeighted(overlay, opacity, image_source, 1 - opacity, 0)
+    annotated_frame = cv2.addWeighted(overlay, opacity, image_source_rgb, 1 - opacity, 0)
+
+    annotated_frame_bgr = cv2.cvtColor(annotated_frame, cv2.COLOR_RGB2BGR)
 
-    return annotated_frame
+    return annotated_frame_bgr
 
 def mp4_to_png(input_path: str, save_path: str, scale_factor: float) -> str: 
     """ Converts mp4 to pngs for each frame of the video.