new visual

Author: Koldim2001

patched_yolo_infer/functions_extra.py

@@ -79,10 +79,6 @@ def visualize_results_usual_yolo_inference(
 
     class_names = model.names
 
-    # Map class IDs to indices in the color list
-    all_classes = set(cls for pred in predictions for cls in pred.boxes.cls.cpu().int().tolist())
-    class_to_color_index = {cls_id: idx for idx, cls_id in enumerate(all_classes)}
-
     # Process each prediction
     for pred in predictions:
 
@@ -120,7 +116,7 @@ def visualize_results_usual_yolo_inference(
                 random.seed(int(classes[i] + delta_colors))
                 color = (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))
             else:
-                color = list_of_class_colors[class_to_color_index[class_index]]
+                color = list_of_class_colors[class_index]
 
             box = boxes[i]
             x_min, y_min, x_max, y_max = box
@@ -148,7 +144,7 @@ def visualize_results_usual_yolo_inference(
                     label = str(class_name)
                 (text_width, text_height), _ = cv2.getTextSize(label, font, font_scale, thickness)
                 background_color = (
-                    color_class_background[class_to_color_index[class_index]]
+                    color_class_background[class_index]
                     if isinstance(color_class_background, list)
                     else color_class_background
                 )
@@ -339,10 +335,6 @@ def visualize_results(
     if random_object_colors:
         random.seed(int(delta_colors))
 
-    # Map class IDs to indices in the color list
-    unique_classes = set(classes_ids)
-    class_to_color_index = {cls_id: idx for idx, cls_id in enumerate(unique_classes)}
-
     # Process each prediction
     for i in range(len(classes_ids)):
         # Get the class for the current detection
@@ -361,7 +353,7 @@ def visualize_results(
             random.seed(int(classes_ids[i] + delta_colors))
             color = (random.randint(0, 255), random.randint(0, 255), random.randint(0, 255))
         else:
-            color = list_of_class_colors[class_to_color_index[classes_ids[i]]]
+            color = list_of_class_colors[classes_ids[i]]
 
         box = boxes[i]
         x_min, y_min, x_max, y_max = box
@@ -409,7 +401,7 @@ def visualize_results(
                 label = str(class_name)
             (text_width, text_height), _ = cv2.getTextSize(label, font, font_scale, thickness)
             background_color = (
-                color_class_background[class_to_color_index[classes_ids[i]]]
+                color_class_background[classes_ids[i]]
                 if isinstance(color_class_background, list)
                 else color_class_background
             )