Improve dataset card: Add metadata (task category, library, license) and sample usage
Browse filesThis PR enhances the dataset card for Copernicus-Bench by:
- Updating the `task_categories` to include `other`, reflecting the broad scope of this benchmark dataset.
- Adding the `library_name: datasets` metadata tag for better discoverability and integration with the Hugging Face `datasets` library.
- Setting the `license: other` metadata tag, as the benchmark integrates multiple datasets with diverse licenses, and the dataset card itself states "See individual datasets" for licensing details.
- Adding the `multimodal` tag to reflect the dataset's use of various sensor modalities.
- Including a `Sample Usage` section to provide clear instructions on how to load and use the dataset with the `datasets` library.
These changes align with community guidelines for comprehensive and user-friendly dataset documentation.
README.md
CHANGED
|
@@ -2,12 +2,16 @@
|
|
| 2 |
task_categories:
|
| 3 |
- image-classification
|
| 4 |
- image-segmentation
|
|
|
|
| 5 |
pretty_name: Copernicus-Bench
|
| 6 |
tags:
|
| 7 |
- earth-observation
|
| 8 |
- remote-sensing
|
| 9 |
- benchmark
|
| 10 |
- foundation-model
|
|
|
|
|
|
|
|
|
|
| 11 |
---
|
| 12 |
|
| 13 |
# Dataset Card for Copernicus-Bench
|
|
@@ -22,26 +26,43 @@ A hierarchical ML benchmark for Copernicus Sentinels, with 15 datasets spread in
|
|
| 22 |
|
| 23 |
<!-- Provide a longer summary of what this dataset is. -->
|
| 24 |
|
| 25 |
-
| Level | Name
|
| 26 |
-
|
| 27 |
-
| L1
|
| 28 |
-
| L1
|
| 29 |
-
| L2
|
| 30 |
-
| L2
|
| 31 |
-
| L2
|
| 32 |
-
| L2
|
| 33 |
-
| L2
|
| 34 |
-
| L2
|
| 35 |
-
| L2
|
| 36 |
-
| L2
|
| 37 |
-
| L3
|
| 38 |
-
| L3
|
| 39 |
-
| L3
|
| 40 |
-
| L3
|
| 41 |
-
| L3
|
| 42 |
|
| 43 |
L1: preprocessing, L2: base applications, L3: specialized applications. *: time series available.
|
| 44 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 45 |
## Related Sources
|
| 46 |
|
| 47 |
<!-- Provide the basic links for the dataset. -->
|
|
|
|
| 2 |
task_categories:
|
| 3 |
- image-classification
|
| 4 |
- image-segmentation
|
| 5 |
+
- other
|
| 6 |
pretty_name: Copernicus-Bench
|
| 7 |
tags:
|
| 8 |
- earth-observation
|
| 9 |
- remote-sensing
|
| 10 |
- benchmark
|
| 11 |
- foundation-model
|
| 12 |
+
- multimodal
|
| 13 |
+
library_name: datasets
|
| 14 |
+
license: other
|
| 15 |
---
|
| 16 |
|
| 17 |
# Dataset Card for Copernicus-Bench
|
|
|
|
| 26 |
|
| 27 |
<!-- Provide a longer summary of what this dataset is. -->
|
| 28 |
|
| 29 |
+
| Level | Name | Modality | Task | # Images | Image Size | # Classes | Source | License |
|
| 30 |
+
|---|---|---|---|---|---|---|---|---|
|
| 31 |
+
| L1 | Cloud-S2 | S2 TOA | segmentation (cloud) | 1699/567/551 | 512x512x13 | 4 | [CloudSEN12](https://huggingface.co/datasets/tacofoundation/cloudsen12) | CC 0 1.0 |
|
| 32 |
+
| L1 | Cloud-S3 | S3 OLCI | segmentation (cloud) | 1197/399/399 | 256x256x21 | 5 | new | CC BY 4.0 |
|
| 33 |
+
| L2 | EuroSAT-S1 | S1 GRD | classification (LULC) | 16200/5400/5400 | 64x64x2 | 10 | [EuroSAT-SAR](https://huggingface.co/datasets/wangyi111/EuroSAT-SAR) | CC BY 4.0 |
|
| 34 |
+
| L2 | EuroSAT-S2 | S2 TOA | classification (LULC) | 16200/5400/5400 | 64x64x13 | 10 | [EuroSAT](https://github.com/phelber/EuroSAT) | MIT |
|
| 35 |
+
| L2 | BigEarthNet-S1 | S1 GRD | classification (LULC) | 11894/6117/5991 | 120x120x12 | 19 | [BigEarthNet v2.0](https://bigearth.net/) | CDLA-Permissive-1.0 |
|
| 36 |
+
| L2 | BigEarthNet-S2 | S2 SR | classification (LULC) | 11894/6117/5991 | 120x120x12 | 19 | [BigEarthNet v2.0](https://bigearth.net/) | CDLA-Permissive-1.0 |
|
| 37 |
+
| L2 | LC100Cls-S3 | S3 OLCI | classification (LULC) | 5181/1727/1727* | 96x96x21 | 23 | new | CC BY 4.0 |
|
| 38 |
+
| L2 | DFC2020-S1 | S1 GRD | segmentation (LULC) | 3156/986/986 | 256x256x13 | 10 | [DFC2020](https://ieee-dataport.org/competitions/2020-ieee-grss-data-fusion-contest) | CC BY 4.0 |
|
| 39 |
+
| L2 | DFC2020-S2 | S2 TOA | segmentation (LULC) | 3156/986/986 | 256x256x13 | 10 | [DFC2020](https://ieee-dataport.org/competitions/2020-ieee-grss-data-fusion-contest) | CC BY 4.0 |
|
| 40 |
+
| L2 | LC100Seg-S3 | S3 OLCI | segmentation (LULC) | 5181/1727/1727* | 96x96x21 (288x288) | 23 | new | CC BY 4.0 |
|
| 41 |
+
| L3 | Flood-S1 | S1 GRD | change detection (flood) | 3000/1000/1000 | 224x224x2 | 3 | [Kuro Siwo](https://github.com/Orion-AI-Lab/KuroSiwo) | MIT |
|
| 42 |
+
| L3 | LCZ-S2 | S2 TOA | classification (local climate zone) | 15000/5000/5000 | 32x32x10 | 17 | [So2Sat LCZ42](https://github.com/zhu-xlab/So2Sat-LCZ42) | CC BY 4.0 |
|
| 43 |
+
| L3 | Biomass-S3 | S3 OLCI | regression (biomass) | 3000/1000/1000* | 96x96x21 (288x288) | 1 | new | CC BY 4.0 |
|
| 44 |
+
| L3 | AQ-NO2-S5P | S5P NO2 | regression (air quality) | 1480/493/494* | 56x56x1 | 1 | new | CC BY 4.0 |
|
| 45 |
+
| L3 | AQ-O3-S5P | S5P O3 | regression (air quality) | 1480/493/494* | 56x56x1 | 1 | new | CC BY 4.0 |
|
| 46 |
|
| 47 |
L1: preprocessing, L2: base applications, L3: specialized applications. *: time series available.
|
| 48 |
|
| 49 |
+
## Sample Usage
|
| 50 |
+
|
| 51 |
+
You can load the dataset using the `datasets` library:
|
| 52 |
+
|
| 53 |
+
```python
|
| 54 |
+
from datasets import load_dataset
|
| 55 |
+
|
| 56 |
+
# Load the entire Copernicus-Bench benchmark
|
| 57 |
+
dataset = load_dataset("wangyi111/Copernicus-Bench")
|
| 58 |
+
|
| 59 |
+
# Or load a specific sub-dataset, for example, Cloud-S2
|
| 60 |
+
cloud_s2_dataset = load_dataset("wangyi111/Copernicus-Bench", "Cloud-S2")
|
| 61 |
+
|
| 62 |
+
print(dataset)
|
| 63 |
+
print(cloud_s2_dataset)
|
| 64 |
+
```
|
| 65 |
+
|
| 66 |
## Related Sources
|
| 67 |
|
| 68 |
<!-- Provide the basic links for the dataset. -->
|