Add library_name and project page
Browse filesThis PR adds the `library_name` to the metadata and adds the project page URL to the general information section.
README.md
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@@ -1,10 +1,11 @@
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---
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license: etalab-2.0
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tags:
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- semantic segmentation
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- pytorch
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- landcover
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-
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model-index:
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- name: FLAIR-HUB_LC-A_swinbase-unet
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results:
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@@ -14,63 +15,59 @@ model-index:
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name: IGNF/FLAIR-HUB/
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type: earth-observation-dataset
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metrics:
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-
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type: mIoU
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value: 64.803
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-
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value: 77.93
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value: 84.7
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value: 79.029
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value: 61.59
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-
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value: 76.228
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value: 57.509
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value: 64.232
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value: 90.6
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value: 63.761
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value: 54.897
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value: 58.304
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value: 37.635
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value: 78.314
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value: 72.073
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value: 62.519
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value: 30.084
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-
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pipeline_tag: image-segmentation
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---
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-
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-
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<div style="font-family:sans-serif; color:black; background-color:#F8F5F5; padding:25px; border-radius:10px; margin:auto; border:0px; ">
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<!-- Collection Section -->
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@@ -281,6 +278,7 @@ pipeline_tag: image-segmentation
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- **Contact:** [email protected]
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- **Code repository:** https://github.com/IGNF/FLAIR-HUB
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- **Paper:** https://arxiv.org/abs/2506.07080
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- **Developed by:** IGN
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- **Compute infrastructure:**
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- software: python, pytorch-lightning
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@@ -408,5 +406,4 @@ pipeline_tag: image-segmentation
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```
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Anatol Garioud, Sébastien Giordano, Nicolas David, Nicolas Gonthier.
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FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping. (2025).
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DOI: https://doi.org/10.48550/arXiv.2506.
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-
```
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---
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license: etalab-2.0
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+
pipeline_tag: image-segmentation
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tags:
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- semantic segmentation
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- pytorch
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- landcover
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library_name: pytorch
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model-index:
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- name: FLAIR-HUB_LC-A_swinbase-unet
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results:
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name: IGNF/FLAIR-HUB/
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type: earth-observation-dataset
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metrics:
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- type: mIoU
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value: 64.803
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name: mIoU
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- type: OA
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value: 77.93
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name: Overall Accuracy
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- type: IoU
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value: 84.7
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name: IoU building
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- type: IoU
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value: 79.029
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name: IoU greenhouse
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- type: IoU
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value: 61.59
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name: IoU swimming pool
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- type: IoU
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value: 76.228
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name: IoU impervious surface
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- type: IoU
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value: 57.509
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name: IoU pervious surface
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- type: IoU
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value: 64.232
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name: IoU bare soil
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- type: IoU
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value: 90.6
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name: IoU water
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- type: IoU
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value: 63.761
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name: IoU snow
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- type: IoU
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value: 54.897
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name: IoU herbaceous vegetation
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- type: IoU
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value: 58.304
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name: IoU agricultural land
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- type: IoU
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value: 37.635
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name: IoU plowed land
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- type: IoU
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value: 78.314
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name: IoU vineyard
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- type: IoU
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value: 72.073
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name: IoU deciduous
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- type: IoU
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value: 62.519
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name: IoU coniferous
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- type: IoU
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value: 30.084
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name: IoU brushwood
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---
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<div style="font-family:sans-serif; color:black; background-color:#F8F5F5; padding:25px; border-radius:10px; margin:auto; border:0px; ">
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<!-- Collection Section -->
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- **Contact:** [email protected]
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- **Code repository:** https://github.com/IGNF/FLAIR-HUB
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- **Paper:** https://arxiv.org/abs/2506.07080
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- **Project page:** https://ignf.github.io/FLAIR/FLAIR-HUB/flairhub
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- **Developed by:** IGN
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- **Compute infrastructure:**
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- software: python, pytorch-lightning
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```
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Anatol Garioud, Sébastien Giordano, Nicolas David, Nicolas Gonthier.
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FLAIR-HUB: Large-scale Multimodal Dataset for Land Cover and Crop Mapping. (2025).
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DOI: https://doi.org/10.48550/arXiv.2506.0
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