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README.md
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---
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license: cc0-1.0
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pipeline_tag: image-segmentation
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mlm-metadata:
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name: ChesapeakeRSC Road Segmentation U-Net
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architecture: torchgeo.models.unet
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artifact_type: torch.export.save
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framework: torch
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framework_version: 2.8.0
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accelerator: cuda
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total_parameters: 1234567
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tasks: [semantic-segmentation]
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input:
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- name: Imagery
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bands: [R, G, B, NIR]
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input:
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shape: [-1, 4, -1, -1]
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dim_order: [batch, channel, height, width]
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data_type: float32
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pre_processing_function:
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format: torch.export.load
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expression:
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id: export-transform
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name: transforms
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href: path/to/archive.pt2
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type: "application/octet-stream; framework=pytorch; profile=ExportedProgram"
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output:
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- name: segmentation-output
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tasks: [semantic-segmentation]
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result:
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shape: [-1, 2, -1, -1]
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dim_order: [batch, classes, height, width]
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data_type: float32
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classification:classes:
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- value: 0
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name: background
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- value: 1
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name: road
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---
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U-Net ResNet-18 backbone model trained on [ChesapeakeRSC dataset](https://github.com/isaaccorley/ChesapeakeRSC)
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---
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license: cc0-1.0
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pipeline_tag: image-segmentation
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---
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U-Net ResNet-18 backbone model trained on [ChesapeakeRSC dataset](https://github.com/isaaccorley/ChesapeakeRSC)
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