| import model | |
| from transformers import pipeline | |
| from transformers.image_utils import load_image | |
| pipe = pipeline( | |
| task='sscd-copy-detection', | |
| model='m3/sscd-copy-detection', | |
| batch_size=10, | |
| device='cpu', | |
| ) | |
| vec1 = pipe(load_image("http://images.cocodataset.org/val2017/000000039769.jpg")) | |
| vec2 = pipe(load_image("http://images.cocodataset.org/val2017/000000039769.jpg")) | |
| import torch.nn.functional as F | |
| cos_sim = F.cosine_similarity(vec1, vec2, dim=0) | |
| print('similarity:', round(cos_sim.item(), 3)) |