Allow multi_label option for NMS with PyTorch Hub (ultralytics#4728)

* Allow specifying multi_label option for NMS when using torch hub

* Reformat

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>

models/common.py

@@ -278,6 +278,7 @@ class AutoShape(nn.Module):
     conf = 0.25  # NMS confidence threshold
     iou = 0.45  # NMS IoU threshold
     classes = None  # (optional list) filter by class
+    multi_label = False  # NMS multiple labels per box
     max_det = 1000  # maximum number of detections per image
 
     def __init__(self, model):
@@ -337,7 +338,8 @@ def forward(self, imgs, size=640, augment=False, profile=False):
             t.append(time_sync())
 
             # Post-process
-            y = non_max_suppression(y, self.conf, iou_thres=self.iou, classes=self.classes, max_det=self.max_det)  # NMS
+            y = non_max_suppression(y, self.conf, iou_thres=self.iou, classes=self.classes,
+                                    multi_label=self.multi_label, max_det=self.max_det)  # NMS
             for i in range(n):
                 scale_coords(shape1, y[i][:, :4], shape0[i])