Improve dataset card: add metadata, links, and usage snippet

#3
by nielsr HF Staff - opened
Files changed (1) hide show
  1. README.md +98 -2
README.md CHANGED
@@ -1,6 +1,102 @@
1
  ---
2
  license: cc-by-4.0
 
 
 
 
 
 
3
  ---
4
- This Dataset contains the training data for the paper [Orient Anything V2: Unifying Orientation and Rotation Understanding](https://huggingface.co/papers/2601.05573).
5
 
6
- Code: https://github.com/SpatialVision/Orient-Anything-V2
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  ---
2
  license: cc-by-4.0
3
+ task_categories:
4
+ - other
5
+ tags:
6
+ - 3d
7
+ - computer-vision
8
+ - orientation-estimation
9
  ---
 
10
 
11
+ # Orient Anything V2 Dataset
12
+
13
+ [**Project Page**](https://orient-anythingv2.github.io/) | [**Paper**](https://huggingface.co/papers/2601.05573) | [**GitHub**](https://github.com/SpatialVision/Orient-Anything-V2)
14
+
15
+ **Orient Anything V2** is an enhanced foundation model for unified understanding of object 3D orientation and rotation from single or paired images. This repository contains the training data (final rendering data) used for the model.
16
+
17
+ ## Sample Usage
18
+
19
+ Below is a snippet to run inference using the model and data logic, as found in the [official GitHub repository](https://github.com/SpatialVision/Orient-Anything-V2):
20
+
21
+ ```python
22
+ import numpy as np
23
+ from PIL import Image
24
+ import torch
25
+ import tempfile
26
+ import os
27
+
28
+ from paths import *
29
+ from vision_tower import VGGT_OriAny_Ref
30
+ from inference import *
31
+ from app_utils import *
32
+
33
+ mark_dtype = torch.bfloat16 if torch.cuda.get_device_capability()[0] >= 8 else torch.float16
34
+ # device = 'cuda:0'
35
+ device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
36
+
37
+ if os.path.exists(LOCAL_CKPT_PATH):
38
+ ckpt_path = LOCAL_CKPT_PATH
39
+ else:
40
+ from huggingface_hub import hf_hub_download
41
+ ckpt_path = hf_hub_download(repo_id="Viglong/Orient-Anything-V2", filename=HF_CKPT_PATH, repo_type="model", cache_dir='./', resume_download=True)
42
+
43
+ model = VGGT_OriAny_Ref(out_dim=900, dtype=mark_dtype, nopretrain=True)
44
+ model.load_state_dict(torch.load(ckpt_path, map_location='cpu'))
45
+ model.eval()
46
+ model = model.to(device)
47
+ print('Model loaded.')
48
+
49
+ @torch.no_grad()
50
+ def run_inference(pil_ref, pil_tgt=None, do_rm_bkg=True):
51
+ if pil_tgt is not None:
52
+ if do_rm_bkg:
53
+ pil_ref = background_preprocess(pil_ref, True)
54
+ pil_tgt = background_preprocess(pil_tgt, True)
55
+ else:
56
+ if do_rm_bkg:
57
+ pil_ref = background_preprocess(pil_ref, True)
58
+
59
+ try:
60
+ ans_dict = inf_single_case(model, pil_ref, pil_tgt)
61
+ except Exception as e:
62
+ print("Inference error:", e)
63
+ raise gr.Error(f"Inference failed: {str(e)}")
64
+
65
+ def safe_float(val, default=0.0):
66
+ try:
67
+ return float(val)
68
+ except:
69
+ return float(default)
70
+
71
+ az = safe_float(ans_dict.get('ref_az_pred', 0))
72
+ el = safe_float(ans_dict.get('ref_el_pred', 0))
73
+ ro = safe_float(ans_dict.get('ref_ro_pred', 0))
74
+ alpha = int(ans_dict.get('ref_alpha_pred', 1))
75
+
76
+ if pil_tgt is not None:
77
+ rel_az = safe_float(ans_dict.get('rel_az_pred', 0))
78
+ rel_el = safe_float(ans_dict.get('rel_el_pred', 0))
79
+ rel_ro = safe_float(ans_dict.get('rel_ro_pred', 0))
80
+
81
+ print("Relative Pose: Azi",rel_az,"Ele",rel_el,"Rot",rel_ro)
82
+
83
+ image_ref_path = 'assets/examples/F35-0.jpg'
84
+ image_tgt_path = 'assets/examples/F35-1.jpg' # optional
85
+
86
+ image_ref = Image.open(image_ref_path).convert('RGB')
87
+ image_tgt = Image.open(image_tgt_path).convert('RGB')
88
+
89
+ run_inference(image_ref, image_tgt, True)
90
+ ```
91
+
92
+ ## Citation
93
+
94
+ If you find this project useful, please consider citing:
95
+
96
+ ```bibtex
97
+ @inproceedings{wangorient,
98
+ title={Orient Anything V2: Unifying Orientation and Rotation Understanding},
99
+ author={Wang, Zehan and Zhang, Ziang and Xu, Jiayang and Wang, Jialei and Pang, Tianyu and Du, Chao and Zhao, Hengshuang and Zhao, Zhou},
100
+ booktitle={The Thirty-ninth Annual Conference on Neural Information Processing Systems}
101
+ }
102
+ ```