ultralytics 8.0.131 NCNN, HUB and FastSAM fixes (#3587)

ultralytics/yolo/fastsam/model.py

@@ -22,7 +22,7 @@ from .predict import FastSAMPredictor
 class FastSAM(YOLO):
 
     def __init__(self, model='FastSAM-x.pt'):
-        # Call the __init__ method of the parent class (YOLO) with the updated default model
+        """Call the __init__ method of the parent class (YOLO) with the updated default model"""
         if model == 'FastSAM.pt':
             model = 'FastSAM-x.pt'
         super().__init__(model=model)

ultralytics/yolo/fastsam/utils.py

@@ -20,11 +20,10 @@ def adjust_bboxes_to_image_border(boxes, image_shape, threshold=20):
     h, w = image_shape
 
     # Adjust boxes
-    boxes[:, 0] = torch.where(boxes[:, 0] < threshold, 0, boxes[:, 0])  # x1
-    boxes[:, 1] = torch.where(boxes[:, 1] < threshold, 0, boxes[:, 1])  # y1
-    boxes[:, 2] = torch.where(boxes[:, 2] > w - threshold, w, boxes[:, 2])  # x2
-    boxes[:, 3] = torch.where(boxes[:, 3] > h - threshold, h, boxes[:, 3])  # y2
-
+    boxes[boxes[:, 0] < threshold, 0] = 0  # x1
+    boxes[boxes[:, 1] < threshold, 1] = 0  # y1
+    boxes[boxes[:, 2] > w - threshold, 2] = w  # x2
+    boxes[boxes[:, 3] > h - threshold, 3] = h  # y2
     return boxes