Update app.py

app.py

@@ -22,7 +22,7 @@ def inference(net, input_img):
     tmpImg[:, :, 2] = (input_img[:, :, 0] - 0.485) / 0.229
     tmpImg = torch.from_numpy(tmpImg.transpose((2, 0, 1))[np.newaxis, :, :, :]).type(torch.FloatTensor)
     tmpImg = Variable(tmpImg.cuda() if torch.cuda.is_available() else tmpImg)
-    d1, *, *, *, *, *, * = net(tmpImg)
+    d1, d2, d3, d4, d5, d6, d7 = net(tmpImg)
     pred = normPRED(1.0 - d1[:, 0, :, :])
     return pred.cpu().data.numpy().squeeze()