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README.md
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<p>The general characteristics of this specific model <strong>FLAIR-INC_rgbi_15cl_resnet34-unet</strong> are :</p>
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<ul style="list-style-type:disc;">
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<li>Trained with the FLAIR-INC dataset</li>
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<li>RGBI images (true colours + infrared )</li>
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<li>U-Net with a Resnet-34 encoder</li>
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<li>15 class nomenclature : [building, pervious surface, impervious surface, bare soil, water, coniferous, deciduous, brushwood, vineyard, herbaceous, agricultural land, plowed land, swimming pool, snow, greenhouse]</li>
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- **Compute infrastructure:**
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- software: python, pytorch-lightning
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- hardware: HPC/AI resources provided by GENCI-IDRIS
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- **License:**
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---
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<p>The general characteristics of this specific model <strong>FLAIR-INC_rgbi_15cl_resnet34-unet</strong> are :</p>
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<ul style="list-style-type:disc;">
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<li>Trained with the FLAIR-INC dataset</li>
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<li>Trained with the SegmentationModelsPytorch library</li>
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<li>RGBI images (true colours + infrared )</li>
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<li>U-Net with a Resnet-34 encoder</li>
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<li>15 class nomenclature : [building, pervious surface, impervious surface, bare soil, water, coniferous, deciduous, brushwood, vineyard, herbaceous, agricultural land, plowed land, swimming pool, snow, greenhouse]</li>
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- **Compute infrastructure:**
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- software: python, pytorch-lightning
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- hardware: HPC/AI resources provided by GENCI-IDRIS
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- **License:** Etalab 2.0
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