killameep/waypoint-models

Waypoint models

ONNX exports of the networks that Waypoint runs through ONNX Runtime, an image geolocation desktop app. The app downloads these files on first launch and checks each against the SHA-256 below before using it.

These are converted copies of other people's models. Each file keeps the license of the model it came from. The conversion changes the format only: the weights are the originals, exported with torch.onnx by the scripts in tools/export/ of the Waypoint repository, and checked against the PyTorch originals (see tools/parity/REPORT.md there).

License notice

• streetclip_vision.onnx is licensed under CC BY-NC 4.0, inherited from StreetCLIP. Non-commercial use only. Changes: the vision tower alone, exported to ONNX, with the CLS token (before the post-layernorm) as output.
• DINOv2, DISK and LightGlue files: Apache License 2.0. Changes: exported to ONNX; DINOv2's position embedding resampled to 336 px at export time; LightGlue split into one graph per stage.
• PLONK files: MIT, Copyright (c) Nicolas Dufour. Changes: one step of the Riemannian flow sampler exported to ONNX.

Because of StreetCLIP, the default model set as a whole can be used for non-commercial purposes only.

Files

File	What	From	License	Size	SHA-256
streetclip_vision.onnx	StreetCLIP vision tower	geolocal/StreetCLIP	CC BY-NC 4.0	1214.3 MB	f28cb3ff3f2ed69d43f31d8eea00498f48180c4078a09aa910ed039aba6ffa5d
disk_unet.onnx	DISK keypoint network	cvlab-epfl/disk (depth-save.pth)	Apache 2.0	4.4 MB	47ebf56f396249791915a101fba2f7346ea9ed36d60144b016af96c61dd7f98f
lg_front.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	0.1 MB	3d26471ae3f835297a27d2fa54ae9db79720e119514d76e1261bd6b2462fe483
lg_layer0.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	5.1 MB	418492373bda83d36252712f78cb1db5a1a118a8329358b4829b13f8b87f7179
lg_layer1.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	5.1 MB	f6a2c9ac52cad88b15e9961829521bd1c44f43228f31a196b6cbf58d4af676eb
lg_layer2.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	5.1 MB	3b0e41ee55d9b7a0ea95e884c6aeef0a0695cc96afc721383f26c63682c6f50c
lg_layer3.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	5.1 MB	68c00b6bcbecb95627eb0caf9d0bd739fa706517c8ceb6d7b66b26047a3ebda8
lg_layer4.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	5.1 MB	45f11d7d36a9835ae6b3815c375f86a3bd63a06b9e332699467f0a45e7a1e37e
lg_layer5.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	5.1 MB	06208eafee116630fd98bfaa8ec97742788eb77be16a2eabc7ee3dd39c0fce4e
lg_layer6.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	5.1 MB	ae8364c15dbb16befba2ec535258a0b618810f8b31c16d7b1e79117e270add96
lg_layer7.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	5.1 MB	daa33b674cf7e50e041441213290592bb834b37240bdd17bf6dc7e88dc0a4a78
lg_layer8.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	5.1 MB	169d0ca06bbc102c26b9ac1c9d62835f1c764299bd95e8f7a06249f30736d1de
lg_post.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	0.0 MB	8930e67cdc4d0d212a860bf80ca10bd7726d83e52f512121cdef4d1a52c045b8
lg_assign.onnx	LightGlue (DISK weights), one graph of the adaptive loop	cvg/LightGlue (disk_lightglue)	Apache 2.0	2.4 MB	ddace2667d842a69725c8e6112b3fd1111f42cd27b51885205ae8fcea1390880
plonk_osv5m_step.onnx	PLONK OSV-5M, one flow step	nicolas-dufour/PLONK_OSV_5M	MIT	144.3 MB	d0c5a8e14d0bf284cca9ff7d6e1074202a09c3a85b74bac77b9edd29590745d8
dinov2_vitl14_reg.onnx	DINOv2 ViT-L/14 with registers	facebookresearch/dinov2	Apache 2.0	1214.5 MB	a52dddb65b9b4133a10c201a2408340bab150acc738ad641f5c8d1708ca6c031
plonk_yfcc_step.onnx	PLONK YFCC, one flow step	nicolas-dufour/PLONK_YFCC	MIT	144.3 MB	7208345304e378431462146dacc84899b95c9d3ca13f6e790842ce511dd13af7
plonk_inat_step.onnx	PLONK iNaturalist, one flow step	nicolas-dufour/PLONK_iNaturalist	MIT	36.7 MB	04a00b7fd0db6c0aecebeb744dc39ea13be94830017bff2ddd0780317331966d

Credits

• StreetCLIP: Haas, Alberti, Skreta. Learning Generalized Zero-Shot Learners for Open-Domain Image Geolocalization, arXiv:2302.00275.
• PLONK: Dufour, Picard, Kalogeiton, Landrieu. Around the World in 80 Timesteps: A Generative Approach to Global Visual Geolocation, CVPR 2025, arXiv:2412.06781.
• DINOv2: Oquab et al. DINOv2: Learning Robust Visual Features without Supervision, arXiv:2304.07193; registers: Darcet et al., arXiv:2309.16588.
• DISK: Tyszkiewicz, Fua, Trulls. DISK: Learning local features with policy gradient, NeurIPS 2020.
• LightGlue: Lindenberger, Sarlin, Pollefeys. LightGlue: Local Feature Matching at Light Speed, ICCV 2023.