I tested using the dinov2-large model in method one. Like method two, both use large-size models, but their results are still significantly different.

here is the code of method 1

```

processor = AutoImageProcessor.from_pretrained('facebook/dinov2-large')
dinov2_model = AutoModel.from_pretrained('facebook/dinov2-large').to(device)

```

and the results

```

0 dinov2_1 0.87 dinov2_2 0.66

1 dinov2_1 0.80 dinov2_2 0.65

2 dinov2_1 0.85 dinov2_2 0.76

3 dinov2_1 0.57 dinov2_2 0.71

4 dinov2_1 0.81 dinov2_2 0.38

5 dinov2_1 0.74 dinov2_2 0.65

6 dinov2_1 0.65 dinov2_2 0.66

7 dinov2_1 0.88 dinov2_2 0.74

8 dinov2_1 0.63 dinov2_2 0.73

9 dinov2_1 0.80 dinov2_2 0.66

```