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1import birder
2from birder.inference.classification import infer_image
3
4(net, model_info) = birder.load_pretrained_model("rope_i_vit_s16_pn_aps_c1_pe-core", inference=True)
5
6# Get the image size the model was trained on
7size = birder.get_size_from_signature(model_info.signature)
8
9# Create an inference transform
10transform = birder.classification_transform(size, model_info.rgb_stats)
11
12image = "path/to/image.jpeg" # or a PIL image
13(out, embedding) = infer_image(net, image, transform, return_embedding=True)
14# embedding is a NumPy array with shape of (1, 384)1from PIL import Image
2import birder
3
4(net, model_info) = birder.load_pretrained_model("rope_i_vit_s16_pn_aps_c1_pe-core", inference=True)
5
6# Get the image size the model was trained on
7size = birder.get_size_from_signature(model_info.signature)
8
9# Create an inference transform
10transform = birder.classification_transform(size, model_info.rgb_stats)
11
12image = Image.open("path/to/image.jpeg")
13features = net.detection_features(transform(image).unsqueeze(0))
14# features is a dict (stage name -> torch.Tensor)
15print([(k, v.size()) for k, v in features.items()])
16# Output example:
17# [('neck', torch.Size([1, 384, 24, 24]))]1@misc{dosovitskiy2021imageworth16x16words,
2 title={An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale},
3 author={Alexey Dosovitskiy and Lucas Beyer and Alexander Kolesnikov and Dirk Weissenborn and Xiaohua Zhai and Thomas Unterthiner and Mostafa Dehghani and Matthias Minderer and Georg Heigold and Sylvain Gelly and Jakob Uszkoreit and Neil Houlsby},
4 year={2021},
5 eprint={2010.11929},
6 archivePrefix={arXiv},
7 primaryClass={cs.CV},
8 url={https://arxiv.org/abs/2010.11929},
9}
10
11@misc{heo2024rotarypositionembeddingvision,
12 title={Rotary Position Embedding for Vision Transformer},
13 author={Byeongho Heo and Song Park and Dongyoon Han and Sangdoo Yun},
14 year={2024},
15 eprint={2403.13298},
16 archivePrefix={arXiv},
17 primaryClass={cs.CV},
18 url={https://arxiv.org/abs/2403.13298},
19}
20
21@misc{bolya2025perceptionencoderbestvisual,
22 title={Perception Encoder: The best visual embeddings are not at the output of the network},
23 author={Daniel Bolya and Po-Yao Huang and Peize Sun and Jang Hyun Cho and Andrea Madotto and Chen Wei and Tengyu Ma and Jiale Zhi and Jathushan Rajasegaran and Hanoona Rasheed and Junke Wang and Marco Monteiro and Hu Xu and Shiyu Dong and Nikhila Ravi and Daniel Li and Piotr Dollár and Christoph Feichtenhofer},
24 year={2025},
25 eprint={2504.13181},
26 archivePrefix={arXiv},
27 primaryClass={cs.CV},
28 url={https://arxiv.org/abs/2504.13181},
29}