Detect.inplace=False for multithread-safe inference (#8801)

Detect.inplace=False for safe multithread inference

hubconf.py

@@ -55,6 +55,7 @@ def _create(name, pretrained=True, channels=3, classes=80, autoshape=True, verbo
                 if len(ckpt['model'].names) == classes:
                     model.names = ckpt['model'].names  # set class names attribute
         if autoshape:
+            model.model.model[-1].inplace = False  # Detect.inplace=False for safe multithread inference
             model = AutoShape(model)  # for file/URI/PIL/cv2/np inputs and NMS
         if not verbose:
             LOGGER.setLevel(logging.INFO)  # reset to default

models/yolo.py

@@ -50,7 +50,7 @@ def __init__(self, nc=80, anchors=(), ch=(), inplace=True):  # detection layer
         self.anchor_grid = [torch.zeros(1)] * self.nl  # init anchor grid
         self.register_buffer('anchors', torch.tensor(anchors).float().view(self.nl, -1, 2))  # shape(nl,na,2)
         self.m = nn.ModuleList(nn.Conv2d(x, self.no * self.na, 1) for x in ch)  # output conv
-        self.inplace = inplace  # use in-place ops (e.g. slice assignment)
+        self.inplace = inplace  # use inplace ops (e.g. slice assignment)
 
     def forward(self, x):
         z = []  # inference output