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4c4d99c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | {
"model_name": "PrithviEO",
"model_type": "prithvi_eo",
"architectures": ["PrithviEO2", "CoordinateEncoder", "Transformer"],
"framework": "PyTorch",
"domain": "earth-observation",
"task": "multi-temporal-remote-sensing-representation-learning",
"implementation": {
"entry_point": "model/prithvi_eo.py",
"scope": "engineering reproduction of the Prithvi-EO-2.0 temporal-location masked autoencoder",
"train_script": "scripts/train.py",
"inference_script": "scripts/inference.py",
"evaluation_script": "scripts/result.py",
"synthetic_data_script": "scripts/fake_data.py"
},
"architecture": {
"family": "three-dimensional vision-transformer masked autoencoder",
"input_size": [4, 224, 224],
"patch_size": [1, 16, 16],
"in_channels": 6,
"mask_ratio": 0.75,
"encoder_dim": 96,
"encoder_depth": 2,
"encoder_heads": 4,
"decoder_dim": 64,
"decoder_depth": 1,
"decoder_heads": 4,
"metadata": ["year", "day_of_year", "latitude", "longitude"],
"outputs": ["loss", "embedding", "patch_embeddings", "reconstruction", "mask"]
},
"data": {
"datasets": ["Harmonized Landsat Sentinel-2"],
"protocol": "prithvi_eo_2_synthetic_engineering_v1",
"format": "NPZ",
"train_file": "data/train.npz",
"test_file": "data/test.npz",
"input_shape": ["N", 6, 4, 224, 224],
"temporal_shape": ["N", 4, 2],
"location_shape": ["N", 2],
"bands": ["B02", "B03", "B04", "B8A", "B11", "B12"],
"required_metadata": ["format_version", "data_source", "temporal_coords", "location_coords"]
},
"configuration_sources": ["conf/config.yaml", "model/prithvi_eo.py", "scripts/fake_data.py", "scripts/train.py", "scripts/inference.py", "scripts/result.py"]
}
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