multi-gpu test bug fix #15

detect.py

@@ -51,7 +51,7 @@ def detect(save_img=False):
         dataset = LoadImages(source, img_size=imgsz)
 
     # Get names and colors
-    names = model.module.names if hasattr(model, 'module') else model.names
+    names = model.names if hasattr(model, 'names') else model.modules.names
     colors = [[random.randint(0, 255) for _ in range(3)] for _ in range(len(names))]
 
     # Run inference

models/yolo.py

@@ -27,11 +27,11 @@ class Detect(nn.Module):
             x[i] = x[i].view(bs, self.na, self.no, ny, nx).permute(0, 1, 3, 4, 2).contiguous()
 
             if not self.training:  # inference
-                if (self.grid[i].shape[2:4] != x[i].shape[2:4]) | (self.grid[i].device != x[i].device):
+                if self.grid[i].shape[2:4] != x[i].shape[2:4]:
                     self.grid[i] = self._make_grid(nx, ny).to(x[i].device)
 
                 y = x[i].sigmoid()
-                y[..., 0:2] = (y[..., 0:2] * 2. - 0.5 + self.grid[i]) * self.stride[i]  # xy
+                y[..., 0:2] = (y[..., 0:2] * 2. - 0.5 + self.grid[i].to(x[i].device)) * self.stride[i]  # xy
                 y[..., 2:4] = (y[..., 2:4] * 2) ** 2 * self.anchor_grid[i]  # wh
                 z.append(y.view(bs, -1, self.no))
 

test.py

@@ -75,7 +75,7 @@ def test(data,
     seen = 0
     model.eval()
     _ = model(torch.zeros((1, 3, imgsz, imgsz), device=device)) if device.type != 'cpu' else None  # run once
-    names = model.module.names if hasattr(model, 'module') else model.names
+    names = model.names if hasattr(model, 'names') else model.module.names
     coco91class = coco80_to_coco91_class()
     s = ('%20s' + '%12s' * 6) % ('Class', 'Images', 'Targets', 'P', 'R', 'mAP@.5', 'mAP@.5:.95')
     p, r, f1, mp, mr, map50, map, t0, t1 = 0., 0., 0., 0., 0., 0., 0., 0., 0.