RS pretrained models in huggingface style
Project description
rshf
Remote sensing pretrained models easy loading using huggingface -- PyTorch (for fast benchmarking)
Installation:
pip install rshf
Example:
from rshf.satmae import SatMAE
model = SatMAE.from_pretrained("MVRL/satmae-vitlarge-fmow-pretrain-800")
input = model.transform(torch.randint(0, 256, (224, 224, 3)).float().numpy(), 224).unsqueeze(0)
print(model.forward_encoder(input, mask_ratio=0.0)[0].shape)
TODO:
- Add transforms for each model
- Add Documentation (https://rshf-docs.readthedocs.io/en/latest/)
- Add initial set of models
Citations
| Model Type | Venue | Citation |
|---|---|---|
| BioCLIP | CVPR'24 | link |
| Climplicit | ICLRW'25 | link |
| CLIP | ICML'21 | link |
| CROMA | NeurIPS'23 | link |
| DinoV3 Sat | link | |
| GeoCLAP | BMVC'23 | link |
| GeoCLIP | NeurIPS'23 | link |
| Presto | link | |
| Prithvi | link | |
| ProM3E | CVPR'26 | link |
| RANGE | CVPR'25 | link |
| RCME | ICCV'25 | link |
| RemoteCLIP | TGRS'23 | link |
| RVSA | TGRS'22 | link |
| Sat2Cap | EarthVision'24 | link |
| SatClip | AAAI'25 | link |
| SatMAE | NeurIPS'22 | link |
| SatMAE++ | CVPR'24 | link |
| ScaleMAE | ICCV'23 | link |
| SenCLIP | WACV'25 | link |
| SINR | ICML'23 | link |
| StreetCLIP | link | |
| TaxaBind | WACV'25 | link |
List of models available here: Link
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
rshf-0.2.1.tar.gz
(2.0 MB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
rshf-0.2.1-py3-none-any.whl
(2.0 MB
view details)
File details
Details for the file rshf-0.2.1.tar.gz.
File metadata
- Download URL: rshf-0.2.1.tar.gz
- Upload date:
- Size: 2.0 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.9.25
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
db78b054d6d34a2c8bf7e4711d1e7a61e0248a2c4c0ae453a8dff864614043e3
|
|
| MD5 |
cb005bb35661ebdfb06047b28c5c1bca
|
|
| BLAKE2b-256 |
80424601c2d563dac0f77c3b0300cec11ffda07d367ca7a14649cd352a332fbf
|
File details
Details for the file rshf-0.2.1-py3-none-any.whl.
File metadata
- Download URL: rshf-0.2.1-py3-none-any.whl
- Upload date:
- Size: 2.0 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.9.25
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
d184a5be2d0d08e79370f51f2ca807655c9da4334957523909486352cddd9890
|
|
| MD5 |
f45e8ed51bee80f3ec6c7bc7be79a2e7
|
|
| BLAKE2b-256 |
d2749f8aeb49feaefc1dbc4c22fac696c4e626d50105a81ffe37e020258fb66f
|
