I decided to follow the steps from the first tutorial. I tried to predict output for only one picture, but I’ve only got something with tensor. I don’t know what it is.

I read on some threads that this is the class, which it belongs to and the rest are the predictions for every label. Is there a way to convert it to a more visual way?

```
learn.predict(img)
```

(Category tensor(33),

tensor(33),

tensor([1.5564e-01, 3.9526e-02, 1.1031e-04, 3.4905e-04, 1.3358e-03, 1.1689e-03,

8.2174e-02, 5.6140e-05, 1.4628e-03, 9.4156e-05, 9.5288e-05, 1.3874e-04,

2.9548e-03, 7.6530e-04, 5.3943e-04, 2.3488e-01, 3.1597e-04, 2.3862e-03,

8.4716e-05, 2.9317e-05, 1.1785e-04, 3.1248e-05, 1.1121e-04, 2.9346e-03,

2.8736e-06, 1.9130e-05, 1.4326e-04, 2.6213e-06, 1.4470e-03, 3.1161e-05,

6.7871e-03, 6.7637e-05, 2.7770e-05, 4.6307e-01, 2.2835e-04, 1.2616e-04,

7.4217e-04]))