license: etalab-2.0
tags:
- segmentation
- pytorch
- aerial imagery
- landcover
- IGN
model-index:
- name: FLAIR-INC_RVBIE_unetresnet34_15cl_norm
results:
- task:
type: semantic-segmentation
dataset:
name: IGNF/FLAIR#1-TEST
type: earth-observation-dataset
metrics:
- name: mIoU
type: mIoU
value: 54.72
- name: IoU Buildings
type: IoU
value: 82.3
pipeline_tag: image-segmentation
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Model Informations
- Repository: https://github.com/IGNF/FLAIR-1-AI-Challenge
- Paper [optional]: https://arxiv.org/pdf/2211.12979.pdf
- Developed by: IGN
- Compute infrastructure:
- software: python, pytorch-lightning
- hardware: GENCI, XXX
- License: : Apache 2.0
Uses
Bias, Risks, and Limitations
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Recommendations
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How to Get Started with the Model
Use the code below to get started with the model.
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Training Details
Training Data
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Training Procedure
Preprocessing [optional]
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Training Hyperparameters
- Training regime: {{ training_regime | default("[More Information Needed]", true)}}
Speeds, Sizes, Times [optional]
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Evaluation
Testing Data, Factors & Metrics
Testing Data
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Metrics
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Results
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Summary
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Technical Specifications [optional]
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Citation [optional]
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