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example MLM v1.2.0 model metadata and artifacts
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{
"type": "Feature",
"stac_version": "1.0.0",
"id": "item_landcover_eurosat_sentinel2",
"properties": {
"start_datetime": "1900-01-01T00:00:00Z",
"end_datetime": "9999-01-01T00:00:00Z",
"description": "Sourced from torchgeo python library, identifier is ResNet18_Weights.SENTINEL2_ALL_MOCO. The batch size suggestion is 3300, which almost maxes out an NVIDIA 3090's 24 GB CUDA memory.",
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"mlm:accelerator": "cuda",
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"mlm:accelerator_summary": "Unknown",
"mlm:name": "Resnet-18 Sentinel-2 ALL MOCO",
"mlm:architecture": "ResNet-18",
"mlm:tasks": [
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],
"mlm:input": [
{
"name": "13 Band Sentinel-2 Batch",
"bands": [
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"B05",
"B06",
"B07",
"B08",
"B8A",
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"input": {
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"data_type": "float32"
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"norm_by_channel": true,
"norm_type": "z-score",
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}
],
"mlm:output": [
{
"name": "scene-classification",
"tasks": [
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],
"result": {
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"classification:classes": [
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"description": "Annual Crop"
},
{
"value": 1,
"name": "Forest",
"description": "Forest"
},
{
"value": 2,
"name": "Herbaceous Vegetation",
"description": "Herbaceous Vegetation"
},
{
"value": 3,
"name": "Highway",
"description": "Highway"
},
{
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"name": "Industrial Buildings",
"description": "Industrial Buildings"
},
{
"value": 5,
"name": "Pasture",
"description": "Pasture"
},
{
"value": 6,
"name": "Permanent Crop",
"description": "Permanent Crop"
},
{
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"name": "Residential Buildings",
"description": "Residential Buildings"
},
{
"value": 8,
"name": "River",
"description": "River"
},
{
"value": 9,
"name": "SeaLake",
"description": "SeaLake"
}
],
"post_processing_function": null
}
],
"mlm:total_parameters": 11700000,
"mlm:pretrained": true,
"mlm:pretrained_source": "EuroSat Sentinel-2",
"datetime": null
},
"geometry": {
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]
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},
"links": [
{
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"href": "https://earth-search.aws.element84.com/v1/collections/sentinel-2-l2a",
"type": "application/json"
},
{
"rel": "self",
"href": "s3://wherobots-modelhub-prod/community/classification/landcover-eurosat-sentinel2/model-metadata.json/item_landcover_eurosat_sentinel2.json",
"type": "application/json"
}
],
"assets": {
"model": {
"href": "s3://wherobots-modelhub-prod/community/classification/landcover-eurosat-sentinel2/scripting/model.pt",
"type": "application/octet-stream; application=pytorch",
"title": "Pytorch weights checkpoint",
"description": "A Resnet-18 classification model trained on normalized Sentinel-2 imagery with Eurosat landcover labels with torchgeo.",
"mlm_artifact_type": "torch.jit.script",
"file:size": 43000000,
"roles": [
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"data"
]
},
"source_code": {
"href": "https://github.com/microsoft/torchgeo/blob/61efd2e2c4df7ebe3bd03002ebbaeaa3cfe9885a/torchgeo/models/resnet.py#L207",
"type": "text/x-python",
"title": "Model implementation.",
"description": "Source code to run the model.",
"roles": [
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"code"
]
}
},
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],
"stac_extensions": [
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"https://crim-ca.github.io/mlm-extension/v1.2.0/schema.json"
]
}