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burn_scars_Prithvi_100M.pth

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+version https://git-lfs.github.com/spec/v1
+oid sha256:7a6f72909bbf28917e3afa2ba00f948c470a52f825d7353ece1a785f7ca805a8
+size 1198548899

burn_scars_Prithvi_100M.py

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+dist_params = dict(backend='nccl')
+log_level = 'INFO'
+load_from = None
+resume_from = None
+cudnn_benchmark = True
+custom_imports = dict(imports=['geospatial_fm'])
+dataset_type = 'GeospatialDataset'
+data_root = '/dccstor/geofm-finetuning/fire-scars/finetune-data/6_bands_no_replant_extended'
+num_frames = 1
+img_size = 224
+num_workers = 4
+samples_per_gpu = 4
+img_norm_cfg = dict(
+    means=[
+        0.033349706741586264, 0.05701185520536176, 0.05889748132001316,
+        0.2323245113436119, 0.1972854853760658, 0.11944914225186566
+    ],
+    stds=[
+        0.02269135568823774, 0.026807560223070237, 0.04004109844362779,
+        0.07791732423672691, 0.08708738838140137, 0.07241979477437814
+    ])
+bands = [0, 1, 2, 3, 4, 5]
+tile_size = 224
+orig_nsize = 512
+crop_size = (224, 224)
+img_suffix = '_merged.tif'
+seg_map_suffix = '.mask.tif'
+ignore_index = -1
+image_nodata = -9999
+image_nodata_replace = 0
+image_to_float32 = True
+# pretrained_weights_path = '/dccstor/geofm-finetuning/pretrain_ckpts/mae_weights/2023-04-29_21-50-47/epoch-725-loss-0.0365.pt'
+pretrained_weights_path = None
+num_layers = 12
+patch_size = 16
+embed_dim = 768
+num_heads = 12
+tubelet_size = 1
+epochs = 50
+eval_epoch_interval = 5
+experiment = 'test2'
+project_dir = '/dccstor/geofm-finetuning/fire-scars/os'
+work_dir = '/dccstor/geofm-finetuning/fire-scars/os/test2'
+save_path = '/dccstor/geofm-finetuning/fire-scars/os/test2'
+train_pipeline = [
+    dict(type='LoadGeospatialImageFromFile', to_float32=True),
+    dict(type='LoadGeospatialAnnotations', reduce_zero_label=False),
+    dict(type='BandsExtract', bands=[0, 1, 2, 3, 4, 5]),
+    dict(type='RandomFlip', prob=0.5),
+    dict(type='ToTensor', keys=['img', 'gt_semantic_seg']),
+    dict(
+        type='TorchNormalize',
+        means=[
+            0.033349706741586264, 0.05701185520536176, 0.05889748132001316,
+            0.2323245113436119, 0.1972854853760658, 0.11944914225186566
+        ],
+        stds=[
+            0.02269135568823774, 0.026807560223070237, 0.04004109844362779,
+            0.07791732423672691, 0.08708738838140137, 0.07241979477437814
+        ]),
+    dict(type='TorchRandomCrop', crop_size=(224, 224)),
+    dict(type='Reshape', keys=['img'], new_shape=(6, 1, 224, 224)),
+    dict(type='Reshape', keys=['gt_semantic_seg'], new_shape=(1, 224, 224)),
+    dict(
+        type='CastTensor',
+        keys=['gt_semantic_seg'],
+        new_type='torch.LongTensor'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg'])
+]
+test_pipeline = [
+    dict(type='LoadGeospatialImageFromFile', to_float32=True),
+    dict(type='BandsExtract', bands=[0, 1, 2, 3, 4, 5]),
+    dict(type='ToTensor', keys=['img']),
+    dict(
+        type='TorchNormalize',
+        means=[
+            0.033349706741586264, 0.05701185520536176, 0.05889748132001316,
+            0.2323245113436119, 0.1972854853760658, 0.11944914225186566
+        ],
+        stds=[
+            0.02269135568823774, 0.026807560223070237, 0.04004109844362779,
+            0.07791732423672691, 0.08708738838140137, 0.07241979477437814
+        ]),
+    dict(
+        type='Reshape',
+        keys=['img'],
+        new_shape=(6, 1, -1, -1),
+        look_up=dict({
+            '2': 1,
+            '3': 2
+        })),
+    dict(type='CastTensor', keys=['img'], new_type='torch.FloatTensor'),
+    dict(
+        type='CollectTestList',
+        keys=['img'],
+        meta_keys=[
+            'img_info', 'seg_fields', 'img_prefix', 'seg_prefix', 'filename',
+            'ori_filename', 'img', 'img_shape', 'ori_shape', 'pad_shape',
+            'scale_factor', 'img_norm_cfg'
+        ])
+]
+data = dict(
+    samples_per_gpu=4,
+    workers_per_gpu=4,
+    train=dict(
+        type='FireScars',
+        data_root=
+        '/dccstor/geofm-finetuning/fire-scars/finetune-data/6_bands_no_replant_extended',
+        img_dir='training',
+        ann_dir='training',
+        img_suffix='_merged.tif',
+        seg_map_suffix='.mask.tif',
+        pipeline=[
+            dict(type='LoadGeospatialImageFromFile', to_float32=True),
+            dict(type='LoadGeospatialAnnotations', reduce_zero_label=False),
+            dict(type='BandsExtract', bands=[0, 1, 2, 3, 4, 5]),
+            dict(type='RandomFlip', prob=0.5),
+            dict(type='ToTensor', keys=['img', 'gt_semantic_seg']),
+            dict(
+                type='TorchNormalize',
+                means=[
+                    0.033349706741586264, 0.05701185520536176,
+                    0.05889748132001316, 0.2323245113436119,
+                    0.1972854853760658, 0.11944914225186566
+                ],
+                stds=[
+                    0.02269135568823774, 0.026807560223070237,
+                    0.04004109844362779, 0.07791732423672691,
+                    0.08708738838140137, 0.07241979477437814
+                ]),
+            dict(type='TorchRandomCrop', crop_size=(224, 224)),
+            dict(type='Reshape', keys=['img'], new_shape=(6, 1, 224, 224)),
+            dict(
+                type='Reshape',
+                keys=['gt_semantic_seg'],
+                new_shape=(1, 224, 224)),
+            dict(
+                type='CastTensor',
+                keys=['gt_semantic_seg'],
+                new_type='torch.LongTensor'),
+            dict(type='Collect', keys=['img', 'gt_semantic_seg'])
+        ],
+        ignore_index=-1),
+    val=dict(
+        type='FireScars',
+        data_root=
+        '/dccstor/geofm-finetuning/fire-scars/finetune-data/6_bands_no_replant_extended',
+        img_dir='validation',
+        ann_dir='validation',
+        img_suffix='_merged.tif',
+        seg_map_suffix='.mask.tif',
+        pipeline=[
+            dict(type='LoadGeospatialImageFromFile', to_float32=True),
+            dict(type='BandsExtract', bands=[0, 1, 2, 3, 4, 5]),
+            dict(type='ToTensor', keys=['img']),
+            dict(
+                type='TorchNormalize',
+                means=[
+                    0.033349706741586264, 0.05701185520536176,
+                    0.05889748132001316, 0.2323245113436119,
+                    0.1972854853760658, 0.11944914225186566
+                ],
+                stds=[
+                    0.02269135568823774, 0.026807560223070237,
+                    0.04004109844362779, 0.07791732423672691,
+                    0.08708738838140137, 0.07241979477437814
+                ]),
+            dict(
+                type='Reshape',
+                keys=['img'],
+                new_shape=(6, 1, -1, -1),
+                look_up=dict({
+                    '2': 1,
+                    '3': 2
+                })),
+            dict(
+                type='CastTensor', keys=['img'], new_type='torch.FloatTensor'),
+            dict(
+                type='CollectTestList',
+                keys=['img'],
+                meta_keys=[
+                    'img_info', 'seg_fields', 'img_prefix', 'seg_prefix',
+                    'filename', 'ori_filename', 'img', 'img_shape',
+                    'ori_shape', 'pad_shape', 'scale_factor', 'img_norm_cfg'
+                ])
+        ],
+        ignore_index=-1),
+    test=dict(
+        type='FireScars',
+        data_root=
+        '/dccstor/geofm-finetuning/fire-scars/finetune-data/6_bands_no_replant_extended',
+        img_dir='validation',
+        ann_dir='validation',
+        img_suffix='_merged.tif',
+        seg_map_suffix='.mask.tif',
+        pipeline=[
+            dict(type='LoadGeospatialImageFromFile', to_float32=True),
+            dict(type='BandsExtract', bands=[0, 1, 2, 3, 4, 5]),
+            dict(type='ToTensor', keys=['img']),
+            dict(
+                type='TorchNormalize',
+                means=[
+                    0.033349706741586264, 0.05701185520536176,
+                    0.05889748132001316, 0.2323245113436119,
+                    0.1972854853760658, 0.11944914225186566
+                ],
+                stds=[
+                    0.02269135568823774, 0.026807560223070237,
+                    0.04004109844362779, 0.07791732423672691,
+                    0.08708738838140137, 0.07241979477437814
+                ]),
+            dict(
+                type='Reshape',
+                keys=['img'],
+                new_shape=(6, 1, -1, -1),
+                look_up=dict({
+                    '2': 1,
+                    '3': 2
+                })),
+            dict(
+                type='CastTensor', keys=['img'], new_type='torch.FloatTensor'),
+            dict(
+                type='CollectTestList',
+                keys=['img'],
+                meta_keys=[
+                    'img_info', 'seg_fields', 'img_prefix', 'seg_prefix',
+                    'filename', 'ori_filename', 'img', 'img_shape',
+                    'ori_shape', 'pad_shape', 'scale_factor', 'img_norm_cfg'
+                ])
+        ],
+        ignore_index=-1))
+optimizer = dict(type='Adam', lr=1.3e-05, betas=(0.9, 0.999))
+optimizer_config = dict(grad_clip=None)
+lr_config = dict(
+    policy='poly',
+    warmup='linear',
+    warmup_iters=1500,
+    warmup_ratio=1e-06,
+    power=1.0,
+    min_lr=0.0,
+    by_epoch=False)
+log_config = dict(
+    interval=20,
+    hooks=[
+        dict(type='TextLoggerHook', by_epoch=False),
+        dict(type='TensorboardLoggerHook', by_epoch=False)
+    ])
+checkpoint_config = dict(
+    by_epoch=True,
+    interval=10,
+    out_dir=
+    '/dccstor/geofm-finetuning/carlosgomes/fire_scars/carlos_replicate_experiment_fixed_lr'
+)
+evaluation = dict(
+    interval=1180,
+    metric='mIoU',
+    pre_eval=True,
+    save_best='mIoU',
+    by_epoch=False)
+runner = dict(type='IterBasedRunner', max_iters=6300)
+workflow = [('train', 1)]
+norm_cfg = dict(type='BN', requires_grad=True)
+model = dict(
+    type='TemporalEncoderDecoder',
+    frozen_backbone=False,
+    backbone=dict(
+        type='TemporalViTEncoder',
+        pretrained=None,
+        # '/dccstor/geofm-finetuning/pretrain_ckpts/mae_weights/2023-04-29_21-50-47/epoch-725-loss-0.0365.pt',
+        img_size=224,
+        patch_size=16,
+        num_frames=1,
+        tubelet_size=1,
+        in_chans=6,
+        embed_dim=768,
+        depth=12,
+        num_heads=12,
+        mlp_ratio=4.0,
+        norm_pix_loss=False),
+    neck=dict(
+        type='ConvTransformerTokensToEmbeddingNeck',
+        embed_dim=768,
+        output_embed_dim=768,
+        drop_cls_token=True,
+        Hp=14,
+        Wp=14),
+    decode_head=dict(
+        num_classes=2,
+        in_channels=768,
+        type='FCNHead',
+        in_index=-1,
+        channels=256,
+        num_convs=1,
+        concat_input=False,
+        dropout_ratio=0.1,
+        norm_cfg=dict(type='BN', requires_grad=True),
+        align_corners=False,
+        loss_decode=dict(
+            type='DiceLoss', use_sigmoid=False, loss_weight=1,
+            ignore_index=-1)),
+    auxiliary_head=dict(
+        num_classes=2,
+        in_channels=768,
+        type='FCNHead',
+        in_index=-1,
+        channels=256,
+        num_convs=2,
+        concat_input=False,
+        dropout_ratio=0.1,
+        norm_cfg=dict(type='BN', requires_grad=True),
+        align_corners=False,
+        loss_decode=dict(
+            type='DiceLoss', use_sigmoid=False, loss_weight=1,
+            ignore_index=-1)),
+    train_cfg=dict(),
+    test_cfg=dict(mode='slide', stride=(112, 112), crop_size=(224, 224)))
+gpu_ids = range(0, 1)
+auto_resume = False