isSTAC
large_stringlengths 1
1
| target
large_stringlengths 0
0
| hello
large_stringlengths 5
5
| id
large_stringlengths 7
7
| crs
large_stringlengths 9
9
| geotransform
large_stringlengths 18
18
| input
large_stringlengths 0
0
| start_datetime
large_stringlengths 19
19
| end_datetime
large_stringlengths 19
19
| isText
large_stringlengths 1
1
| target__dtype
large_stringlengths 3
3
| target__shape
large_stringlengths 13
13
| target__offset
large_stringlengths 11
11
| input__dtype
large_stringlengths 3
3
| input__shape
large_stringlengths 14
14
| input__offset
large_stringlengths 16
16
| _checksum
large_stringlengths 32
32
|
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | world | 0000001 | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | 3d4f55982675315b6aa5a0347c472a2e |
||
1 | world | 0000002 | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | e6090d22144413e146766469aadad899 |
||
1 | world | 0000003 | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | efd5de45fb0bd2526ec00e8083bad952 |
||
1 | world | 0000004 | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | baa7813552c3e0d582204d393910a910 |
||
1 | world | 0000005 | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | 23e269d9b20d88886a1bbd056a2fe1fb |
||
1 | world | 0000006 | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | e5407be1f2b0277399b43b361913e1ae |
||
1 | world | 0000007 | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | 20d8c716039369b5fdf538cb6435eaad |
||
1 | world | 0000008 | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | 45f7adfd1c6205fbe34e6ca69c044b59 |
||
1 | world | 0000009 | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | c31d8ed3cf8757d664c0a2eda72945dd |
||
1 | world | 000000A | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | af87acbba5b8b75ccf22f664a5651ed0 |
||
1 | world | 000000B | EPSG:4326 | [0 ,1 ,0 ,0 ,0 ,1] | 2020-01-01T00:00:00 | 2020-01-01T00:00:00 | 0 | I64 | [1, 128, 128] | [0, 131072] | F32 | [13, 128, 128] | [131072, 983040] | 47a64fa38aa91ab4033f446c7cea7a1b |
cloudsen12
A dataset about clouds from Sentinel-2
CloudSEN12 is a LARGE dataset (~1 TB) for cloud semantic understanding that consists of 49,400 image patches (IP) that are evenly spread throughout all continents except Antarctica. Each IP covers 5090 x 5090 meters and contains data from Sentinel-2 levels 1C and 2A, hand-crafted annotations of thick and thin clouds and cloud shadows, Sentinel-1 Synthetic Aperture Radar (SAR), digital elevation model, surface water occurrence, land cover classes, and cloud mask results from six cutting-edge cloud detection algorithms. CloudSEN12 is designed to support both weakly and self-/semi-supervised learning strategies by including three distinct forms of hand-crafted labeling data: high-quality, scribble and no-annotation. For more details on how we created the dataset see our paper: CloudSEN12 - a global dataset for semantic understanding of cloud and cloud shadow in Sentinel-2.
ML-STAC Snippet
import mlstac
secret = 'https://huggingface.co/datasets/jfloresf/mlstac-demo/resolve/main/main.json'
train_db = mlstac.load(secret, framework='torch', stream=True, device='cpu')
Sensor: Sentinel2 - MSI
ML-STAC Task: TensorToTensor, TensorSegmentation
Data raw repository: https://cloudsen12.github.io/
Dataset discussion: https://github.com/IPL-UV/ML-STAC/discussions/2
Review mean score: 5.0
Split_strategy: random
Paper: https://www.nature.com/articles/s41597-022-01878-2
Data Providers
Name | Role | URL |
---|---|---|
Image & Signal Processing | ['host'] | https://isp.uv.es/ |
ESA | ['producer'] | https://www.esa.int/ |
Curators
Name | Organization | URL |
---|---|---|
Jair Flores | OEFA | http://jflores.github.io/ |
Reviewers
Name | Organization | URL | Score |
---|---|---|---|
Cesar Aybar | Image & Signal Processing | http://csaybar.github.io/ | 5 |
Labels
Name | Value |
---|---|
clear | 0 |
thick-cloud | 1 |
thin-cloud | 2 |
cloud-shadow | 3 |
Dimensions
input
Axis | Name | Description |
---|---|---|
0 | C | Spectral bands |
1 | H | Height |
2 | W | Width |
target
Axis | Name | Description |
---|---|---|
0 | C | Hand-crafted labels |
1 | H | Height |
2 | W | Width |
Spectral Bands
Name | Common Name | Description | Center Wavelength | Full Width Half Max | Index |
---|---|---|---|---|---|
B01 | coastal aerosol | Band 1 - Coastal aerosol - 60m | 443.5 | 17.0 | 0 |
B02 | blue | Band 2 - Blue - 10m | 496.5 | 53.0 | 1 |
B03 | green | Band 3 - Green - 10m | 560.0 | 34.0 | 2 |
B04 | red | Band 4 - Red - 10m | 664.5 | 29.0 | 3 |
B05 | red edge 1 | Band 5 - Vegetation red edge 1 - 20m | 704.5 | 13.0 | 4 |
B06 | red edge 2 | Band 6 - Vegetation red edge 2 - 20m | 740.5 | 13.0 | 5 |
B07 | red edge 3 | Band 7 - Vegetation red edge 3 - 20m | 783.0 | 18.0 | 6 |
B08 | NIR | Band 8 - Near infrared - 10m | 840.0 | 114.0 | 7 |
B8A | red edge 4 | Band 8A - Vegetation red edge 4 - 20m | 864.5 | 19.0 | 8 |
B09 | water vapor | Band 9 - Water vapor - 60m | 945.0 | 18.0 | 9 |
B10 | cirrus | Band 10 - Cirrus - 60m | 1375.5 | 31.0 | 10 |
B11 | SWIR 1 | Band 11 - Shortwave infrared 1 - 20m | 1613.5 | 89.0 | 11 |
B12 | SWIR 2 | Band 12 - Shortwave infrared 2 - 20m | 2199.5 | 173.0 | 12 |
- Downloads last month
- 82