multi-gpu test bug fix #15

models/yolo.py

@@ -20,7 +20,7 @@ class Detect(nn.Module):
         self.export = False  # onnx export
 
     def forward(self, x):
-        x = x.copy() # for profiling
+        x = x.copy()  # for profiling
         z = []  # inference output
         self.training |= self.export
         for i in range(self.nl):
@@ -67,6 +67,25 @@ class Model(nn.Module):
         print('')
 
     def forward(self, x, augment=False, profile=False):
+        if augment:
+            img_size = x.shape[-2:]  # height, width
+            s = [0.83, 0.67]  # scales
+            y = []
+            for i, xi in enumerate((x,
+                                    torch_utils.scale_img(x.flip(3), s[0], same_shape=False),  # flip-lr and scale
+                                    torch_utils.scale_img(x, s[1], same_shape=False),  # scale
+                                    )):
+                # cv2.imwrite('img%g.jpg' % i, 255 * xi[0].numpy().transpose((1, 2, 0))[:, :, ::-1])
+                y.append(self.forward_once(xi)[0])
+
+            y[1][..., :4] /= s[0]  # scale
+            y[1][..., 0] = img_size[1] - y[1][..., 0]  # flip lr
+            y[2][..., :4] /= s[1]  # scale
+            return torch.cat(y, 1), None  # augmented inference, train
+        else:
+            return self.forward_once(x, profile)  # single-scale inference, train
+
+    def forward_once(self, x, profile=False):
         y, dt = [], []  # outputs
         for m in self.model:
             if m.f != -1:  # if not from previous layer