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"model_name": "SatMAE++",
"model_type": "satmae_pp",
"architectures": [
"SatMAEPP"
],
"framework": "PyTorch",
"domain": "earth-observation",
"task": "remote-sensing-representation-learning",
"implementation": {
"entry_point": "model/satmaepp.py",
"scope": "masked autoencoding with convolutional native-scale reconstruction for RGB or grouped multispectral satellite imagery",
"train_script": "scripts/train.py",
"inference_script": "scripts/inference.py",
"evaluation_script": "scripts/result.py",
"synthetic_data_script": "scripts/fake_data.py"
},
"architecture": {
"family": "multiscale masked autoencoder with convolutional upsampling",
"runtime_profile": "smoke",
"mode": "rgb",
"image_size": 32,
"patch_size": 4,
"in_channels": 3,
"embed_dim": 64,
"encoder_depth": 2,
"encoder_heads": 4,
"decoder_dim": 32,
"decoder_depth": 1,
"decoder_heads": 4,
"mask_ratio": 0.75,
"scales": [1, 2],
"spectral_groups": null,
"spatial_mask": false,
"norm_pix_loss": false,
"proj_ratio": 4
},
"data": {
"datasets": [
"FMoW-RGB",
"FMoW-Sentinel",
"EuroSAT",
"UCMerced",
"RESISC-45"
],
"protocol": "fmow_rgb_satmaepp",
"format": "NPZ",
"input_key": "images",
"input_shape": ["N", 3, 32, 32],
"native_target_keys": ["images_2x"],
"native_target_shapes": [["N", 3, 64, 64]],
"label_key": "labels",
"label_shape": ["N"],
"num_classes": 10,
"default_train_file": "data/train.npz",
"default_test_file": "data/test.npz",
"required_metadata": ["protocol", "data_source"]
},
"configuration_sources": [
"conf/config.yaml",
"model/satmaepp.py",
"scripts/fake_data.py",
"scripts/train.py",
"scripts/inference.py",
"scripts/result.py"
]
}
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