flair-2
Engage in a semantic segmentation challenge for land cover description using multimodal remote sensing earth observation data, delving into real-world scenarios with a dataset comprising 70,000+ aerial imagery patches and 50,000 Sentinel-2 satellite acquisitions.
Science Score: 26.0%
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○CITATION.cff file
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✓codemeta.json file
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✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Committers with academic emails
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (11.5%) to scientific vocabulary
Keywords
Keywords from Contributors
Repository
Engage in a semantic segmentation challenge for land cover description using multimodal remote sensing earth observation data, delving into real-world scenarios with a dataset comprising 70,000+ aerial imagery patches and 50,000 Sentinel-2 satellite acquisitions.
Basic Info
- Host: GitHub
- Owner: association-rosia
- License: mit
- Language: Jupyter Notebook
- Default Branch: main
- Homepage: https://codalab.lisn.upsaclay.fr/competitions/13447
- Size: 44.7 MB
Statistics
- Stars: 8
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 0
Topics
Metadata Files
README.md
FLAIR #2
The challenge involves a semantic segmentation task focusing on land cover description using multimodal remote sensing earth observation data. Participants will explore heterogeneous data fusion methods in a real-world scenario. Upon registration, access is granted to a dataset containing 70,000+ aerial imagery patches with pixel-based annotations and 50,000 Sentinel-2 satellite acquisitions.
This project was made possible by our compute partners 2CRSi and NVIDIA.
Challenge ranking
The score of the challenge was the mIoU.
Our solution was the 8th one (out of 30 teams) with a mIoU equal to 0.62610 .
The podium:
strakajk - 0.64130
Breizhchess - 0.63550
qwerty64 - 0.63510
Result example
Aerial input image | Multi-class label | Multi-class pred
:--------------------:|:--------------------:|:--------------------:|
| 
| 
View more results on the WandB project.
Model architecture
# Command lines
Launch a training
bash
python src/models/train_model.py <hyperparams args>
Create a submission
bash
python src/models/predict_model.py -n {model.ckpt}
References
Chen, L. C., Papandreou, G., Schroff, F., & Adam, H. (2017). Rethinking atrous convolution for semantic image segmentation. arXiv preprint arXiv:1706.05587.
Garioud, A., De Wit, A., Poupe, M., Valette, M., Giordano, S., & Wattrelos, B. (2023). FLAIR# 2: textural and temporal information for semantic segmentation from multi-source optical imagery. arXiv preprint arXiv:2305.14467.
Xie, E., Wang, W., Yu, Z., Anandkumar, A., Alvarez, J. M., & Luo, P. (2021). SegFormer: Simple and efficient design for semantic segmentation with transformers. Advances in Neural Information Processing Systems, 34, 12077-12090.
Citing
@misc{RebergaUrgell:2023,
Author = {Louis Reberga and Baptiste Urgell},
Title = {FLAIR #2},
Year = {2023},
Publisher = {GitHub},
Journal = {GitHub repository},
Howpublished = {\url{https://github.com/association-rosia/flair-2}}
}
License
Project is distributed under MIT License
Contributors
Louis
REBERGA 
Baptiste
URGELL 
Owner
- Name: RosIA
- Login: association-rosia
- Kind: organization
- Location: France
- Twitter: AssoRosIA
- Repositories: 1
- Profile: https://github.com/association-rosia
GitHub Events
Total
- Watch event: 1
Last Year
- Watch event: 1
Committers
Last synced: about 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Louis REBERGA | l****a@g****m | 368 |
| BaptisteUrgell | b****u@g****m | 80 |
| rbrgAlou | 6****a | 25 |
| Baptiste Urgell | 7****l | 17 |
Issues and Pull Requests
Last synced: about 2 years ago
All Time
- Total issues: 25
- Total pull requests: 38
- Average time to close issues: 4 days
- Average time to close pull requests: about 15 hours
- Total issue authors: 2
- Total pull request authors: 2
- Average comments per issue: 0.32
- Average comments per pull request: 0.03
- Merged pull requests: 36
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 25
- Pull requests: 38
- Average time to close issues: 4 days
- Average time to close pull requests: about 15 hours
- Issue authors: 2
- Pull request authors: 2
- Average comments per issue: 0.32
- Average comments per pull request: 0.03
- Merged pull requests: 36
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- BaptisteUrgell (12)
- louisreberga (12)
- hubert10 (1)
Pull Request Authors
- louisreberga (19)
- BaptisteUrgell (15)
Top Labels
Issue Labels
Pull Request Labels
Dependencies
- pip
- python 3.10.*