timm
/

Image Feature Extraction
timm
PyTorch
Safetensors
rwightman HF staff commited on
Commit
b999a3f
1 Parent(s): 30ee801
Files changed (4) hide show
  1. README.md +111 -0
  2. config.json +34 -0
  3. model.safetensors +3 -0
  4. pytorch_model.bin +3 -0
README.md ADDED
@@ -0,0 +1,111 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - image-classification
4
+ - timm
5
+ library_name: timm
6
+ license: cc-by-nc-4.0
7
+ ---
8
+ # Model card for vit_base_patch14_dinov2.lvd142m
9
+
10
+ A Vision Transformer (ViT) image feature model. Pretrained on LVD-142M with self-supervised DINOv2 method.
11
+
12
+
13
+ ## Model Details
14
+ - **Model Type:** Image classification / feature backbone
15
+ - **Model Stats:**
16
+ - Params (M): 86.6
17
+ - GMACs: 151.7
18
+ - Activations (M): 397.6
19
+ - Image size: 518 x 518
20
+ - **Papers:**
21
+ - DINOv2: Learning Robust Visual Features without Supervision: https://arxiv.org/abs/2304.07193
22
+ - An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: https://arxiv.org/abs/2010.11929v2
23
+ - **Original:** https://github.com/facebookresearch/dinov2
24
+ - **Pretrain Dataset:** LVD-142M
25
+
26
+ ## Model Usage
27
+ ### Image Classification
28
+ ```python
29
+ from urllib.request import urlopen
30
+ from PIL import Image
31
+ import timm
32
+
33
+ img = Image.open(urlopen(
34
+ 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
35
+ ))
36
+
37
+ model = timm.create_model('vit_base_patch14_dinov2.lvd142m', pretrained=True)
38
+ model = model.eval()
39
+
40
+ # get model specific transforms (normalization, resize)
41
+ data_config = timm.data.resolve_model_data_config(model)
42
+ transforms = timm.data.create_transform(**data_config, is_training=False)
43
+
44
+ output = model(transforms(img).unsqueeze(0)) # unsqueeze single image into batch of 1
45
+
46
+ top5_probabilities, top5_class_indices = torch.topk(output.softmax(dim=1) * 100, k=5)
47
+ ```
48
+
49
+ ### Image Embeddings
50
+ ```python
51
+ from urllib.request import urlopen
52
+ from PIL import Image
53
+ import timm
54
+
55
+ img = Image.open(urlopen(
56
+ 'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png'
57
+ ))
58
+
59
+ model = timm.create_model(
60
+ 'vit_base_patch14_dinov2.lvd142m',
61
+ pretrained=True,
62
+ num_classes=0, # remove classifier nn.Linear
63
+ )
64
+ model = model.eval()
65
+
66
+ # get model specific transforms (normalization, resize)
67
+ data_config = timm.data.resolve_model_data_config(model)
68
+ transforms = timm.data.create_transform(**data_config, is_training=False)
69
+
70
+ output = model(transforms(img).unsqueeze(0)) # output is (batch_size, num_features) shaped tensor
71
+
72
+ # or equivalently (without needing to set num_classes=0)
73
+
74
+ output = model.forward_features(transforms(img).unsqueeze(0))
75
+ # output is unpooled, a (1, 1370, 768) shaped tensor
76
+
77
+ output = model.forward_head(output, pre_logits=True)
78
+ # output is a (1, num_features) shaped tensor
79
+ ```
80
+
81
+ ## Model Comparison
82
+ Explore the dataset and runtime metrics of this model in timm [model results](https://github.com/huggingface/pytorch-image-models/tree/main/results).
83
+
84
+ ## Citation
85
+ ```bibtex
86
+ @misc{oquab2023dinov2,
87
+ title={DINOv2: Learning Robust Visual Features without Supervision},
88
+ author={Oquab, Maxime and Darcet, Timothée and Moutakanni, Theo and Vo, Huy V. and Szafraniec, Marc and Khalidov, Vasil and Fernandez, Pierre and Haziza, Daniel and Massa, Francisco and El-Nouby, Alaaeldin and Howes, Russell and Huang, Po-Yao and Xu, Hu and Sharma, Vasu and Li, Shang-Wen and Galuba, Wojciech and Rabbat, Mike and Assran, Mido and Ballas, Nicolas and Synnaeve, Gabriel and Misra, Ishan and Jegou, Herve and Mairal, Julien and Labatut, Patrick and Joulin, Armand and Bojanowski, Piotr},
89
+ journal={arXiv:2304.07193},
90
+ year={2023}
91
+ }
92
+ ```
93
+ ```bibtex
94
+ @article{dosovitskiy2020vit,
95
+ title={An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale},
96
+ author={Dosovitskiy, Alexey and Beyer, Lucas and Kolesnikov, Alexander and Weissenborn, Dirk and Zhai, Xiaohua and Unterthiner, Thomas and Dehghani, Mostafa and Minderer, Matthias and Heigold, Georg and Gelly, Sylvain and Uszkoreit, Jakob and Houlsby, Neil},
97
+ journal={ICLR},
98
+ year={2021}
99
+ }
100
+ ```
101
+ ```bibtex
102
+ @misc{rw2019timm,
103
+ author = {Ross Wightman},
104
+ title = {PyTorch Image Models},
105
+ year = {2019},
106
+ publisher = {GitHub},
107
+ journal = {GitHub repository},
108
+ doi = {10.5281/zenodo.4414861},
109
+ howpublished = {\url{https://github.com/huggingface/pytorch-image-models}}
110
+ }
111
+ ```
config.json ADDED
@@ -0,0 +1,34 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "architecture": "vit_base_patch14_dinov2",
3
+ "num_classes": 0,
4
+ "num_features": 768,
5
+ "global_pool": "token",
6
+ "pretrained_cfg": {
7
+ "tag": "lvd142m",
8
+ "custom_load": false,
9
+ "input_size": [
10
+ 3,
11
+ 518,
12
+ 518
13
+ ],
14
+ "fixed_input_size": true,
15
+ "interpolation": "bicubic",
16
+ "crop_pct": 1.0,
17
+ "crop_mode": "center",
18
+ "mean": [
19
+ 0.485,
20
+ 0.456,
21
+ 0.406
22
+ ],
23
+ "std": [
24
+ 0.229,
25
+ 0.224,
26
+ 0.225
27
+ ],
28
+ "num_classes": 0,
29
+ "pool_size": null,
30
+ "first_conv": "patch_embed.proj",
31
+ "classifier": "head",
32
+ "license": "cc-by-nc-4.0"
33
+ }
34
+ }
model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:55cbb5d887b336d430e649c277b85a1429e724871f9d02ac16203235886d8c7b
3
+ size 346334872
pytorch_model.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:c8f07b5edc5f37f0ec8205fd8777d8c594281d05fc7abd4569f273ea3838e4d6
3
+ size 346381893