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"model_id": "rohitm9/surfaceWaterGlobal",
"version": "2.0.0-labelclass",
"framework": [
"pytorch",
"fastai"
],
"task": "binary-semantic-segmentation",
"architecture": "resnet34-unet-with-aef-bottleneck",
"training_target": "Dynamic World label band, class 0 (water)",
"training_tiles": {
"total": 5278,
"train": 4222,
"valid": 1056
},
"inputs": {
"sentinel_1": {
"bands": 3,
"order": [
"VV",
"VH",
"angle"
],
"source": "Earth Engine COPERNICUS/S1_GRD, dB, 10 m"
},
"alphaearth": {
"bands": 64,
"order": "source order",
"source": "AlphaEarth Foundations annual embeddings v1"
}
},
"aef_projection": {
"input_channels": 64,
"output_channels": 16,
"kernel_size": 1
},
"classes": [
"other",
"water"
],
"checkpoint": "models/s1aef_bottleneck_resnet34_best.pth",
"normalization": "band_stats.npz",
"checkpoint_sha256": "dd0252e2d08c693e3f88949a0a34a846f91dc7ab1668d91ba7ac0ddb688b06ec",
"thresholds": {
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"paper_reference_set": 0.3,
"test_time_augmentation": "four flips"
},
"variants": {
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"model_kind": "s1",
"checkpoint": "models/s1dw_resnet34_best.pth",
"checkpoint_sha256": "a5eab4f07d68256d5a7922a8943efb1b0a14cbc0a513315aff737426a57b6e68"
},
"variants/s1_aef_previous_year_k16_seed42": {
"model_kind": "s1aef",
"checkpoint": "models/s1aef_bottleneck_resnet34_best.pth",
"checkpoint_sha256": "5bd312409fcf86e0a49258c37aa95a53867a5a6b2cef4f73d2e527a3d6fb2717"
}
},
"evaluation_status": "published",
"evaluation": {
"validation_split": {
"water_iou": 0.697666,
"threshold": 0.5,
"tta": true
},
"planetscope_53_scenes": {
"threshold": 0.3,
"pooled_water_iou": 0.850797,
"per_scene_mean_water_iou": 0.755753
},
"s1s2water_15_scenes": {
"grid_m": 30,
"threshold": 0.5,
"pooled_water_iou_mean_3_seeds": 0.9529,
"opera_dswx_s1_pooled_water_iou": 0.869
}
},
"supersedes": {
"tag": "v1-mixed-labels",
"checkpoint_sha256": "3b89c5b768be8d8b5a00260693ca5d2a051ec63969234702903677b9e326138f",
"reason": "trained on a mixture of binarized DW water probability and DW label class"
}
}
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