Uploading trained parameters, config and model related images

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+multi_temporal_crop_classification.png filter=lfs diff=lfs merge=lfs -text

multi_temporal_crop_classification_Prithvi_100M.py

@@ -0,0 +1,394 @@
+dist_params = dict(backend='nccl')
+log_level = 'INFO'
+load_from = None
+resume_from = None
+cudnn_benchmark = True
+custom_imports = dict(imports=['geospatial_fm'])
+num_frames = 3
+img_size = 224
+num_workers = 2
+pretrained_weights_path = '/home/ubuntu/hls-loss-weights/Prithvi_100M.pt'
+num_layers = 6
+patch_size = 16
+embed_dim = 768
+num_heads = 8
+tubelet_size = 1
+epochs = 80
+eval_epoch_interval = 2
+experiment = 'multiclass_exp_newSplit'
+work_dir = '/home/ubuntu/clark_gfm_eval/multiclass_exp_newSplit'
+save_path = '/home/ubuntu/clark_gfm_eval/multiclass_exp_newSplit'
+gpu_ids = range(0, 1)
+dataset_type = 'GeospatialDataset'
+data_root = '/home/ubuntu/hls_cdl_reclassed/'
+img_norm_cfg = dict(
+    means=[
+        494.905781, 815.239594, 924.335066, 2968.881459, 2634.621962,
+        1739.579917, 494.905781, 815.239594, 924.335066, 2968.881459,
+        2634.621962, 1739.579917, 494.905781, 815.239594, 924.335066,
+        2968.881459, 2634.621962, 1739.579917
+    ],
+    stds=[
+        284.925432, 357.84876, 575.566823, 896.601013, 951.900334, 921.407808,
+        284.925432, 357.84876, 575.566823, 896.601013, 951.900334, 921.407808,
+        284.925432, 357.84876, 575.566823, 896.601013, 951.900334, 921.407808
+    ])
+splits = dict(
+    train=
+    '/home/ubuntu/hls-foundation-os/fine-tuning-examples/data_splits/crop_classification/training_data.txt',
+    val=
+    '/home/ubuntu/hls-foundation-os/fine-tuning-examples/data_splits/crop_classification/validation_data.txt',
+    test=
+    '/home/ubuntu/hls-foundation-os/fine-tuning-examples/data_splits/crop_classification/validation_data.txt'
+)
+bands = [0, 1, 2, 3, 4, 5]
+tile_size = 224
+orig_nsize = 512
+crop_size = (224, 224)
+train_pipeline = [
+    dict(type='LoadGeospatialImageFromFile', to_float32=True),
+    dict(type='LoadGeospatialAnnotations', reduce_zero_label=True),
+    dict(type='RandomFlip', prob=0.5),
+    dict(type='ToTensor', keys=['img', 'gt_semantic_seg']),
+    dict(
+        type='TorchNormalize',
+        means=[
+            494.905781, 815.239594, 924.335066, 2968.881459, 2634.621962,
+            1739.579917, 494.905781, 815.239594, 924.335066, 2968.881459,
+            2634.621962, 1739.579917, 494.905781, 815.239594, 924.335066,
+            2968.881459, 2634.621962, 1739.579917
+        ],
+        stds=[
+            284.925432, 357.84876, 575.566823, 896.601013, 951.900334,
+            921.407808, 284.925432, 357.84876, 575.566823, 896.601013,
+            951.900334, 921.407808, 284.925432, 357.84876, 575.566823,
+            896.601013, 951.900334, 921.407808
+        ]),
+    dict(type='TorchRandomCrop', crop_size=(224, 224)),
+    dict(type='Reshape', keys=['img'], new_shape=(6, 3, 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'])
+]
+val_pipeline = [
+    dict(type='LoadGeospatialImageFromFile', to_float32=True),
+    dict(type='LoadGeospatialAnnotations', reduce_zero_label=True),
+    dict(type='ToTensor', keys=['img', 'gt_semantic_seg']),
+    dict(
+        type='TorchNormalize',
+        means=[
+            494.905781, 815.239594, 924.335066, 2968.881459, 2634.621962,
+            1739.579917, 494.905781, 815.239594, 924.335066, 2968.881459,
+            2634.621962, 1739.579917, 494.905781, 815.239594, 924.335066,
+            2968.881459, 2634.621962, 1739.579917
+        ],
+        stds=[
+            284.925432, 357.84876, 575.566823, 896.601013, 951.900334,
+            921.407808, 284.925432, 357.84876, 575.566823, 896.601013,
+            951.900334, 921.407808, 284.925432, 357.84876, 575.566823,
+            896.601013, 951.900334, 921.407808
+        ]),
+    dict(type='TorchRandomCrop', crop_size=(224, 224)),
+    dict(type='Reshape', keys=['img'], new_shape=(6, 3, 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'],
+        meta_keys=[
+            'img_info', 'ann_info', 'seg_fields', 'img_prefix', 'seg_prefix',
+            'filename', 'ori_filename', 'img', 'img_shape', 'ori_shape',
+            'pad_shape', 'scale_factor', 'img_norm_cfg', 'gt_semantic_seg'
+        ])
+]
+test_pipeline = [
+    dict(type='LoadGeospatialImageFromFile', to_float32=True),
+    dict(type='ToTensor', keys=['img']),
+    dict(
+        type='TorchNormalize',
+        means=[
+            494.905781, 815.239594, 924.335066, 2968.881459, 2634.621962,
+            1739.579917, 494.905781, 815.239594, 924.335066, 2968.881459,
+            2634.621962, 1739.579917, 494.905781, 815.239594, 924.335066,
+            2968.881459, 2634.621962, 1739.579917
+        ],
+        stds=[
+            284.925432, 357.84876, 575.566823, 896.601013, 951.900334,
+            921.407808, 284.925432, 357.84876, 575.566823, 896.601013,
+            951.900334, 921.407808, 284.925432, 357.84876, 575.566823,
+            896.601013, 951.900334, 921.407808
+        ]),
+    dict(
+        type='Reshape',
+        keys=['img'],
+        new_shape=(6, 3, -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'
+        ])
+]
+CLASSES = (1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13)
+data = dict(
+    samples_per_gpu=2,
+    workers_per_gpu=1,
+    train=dict(
+        type='GeospatialDataset',
+        CLASSES=(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13),
+        reduce_zero_label=True,
+        data_root='/home/ubuntu/hls_cdl_reclassed/',
+        img_dir='/home/ubuntu/hls_cdl_reclassed/training_chips',
+        ann_dir='/home/ubuntu/hls_cdl_reclassed/training_chips',
+        pipeline=[
+            dict(type='LoadGeospatialImageFromFile', to_float32=True),
+            dict(type='LoadGeospatialAnnotations', reduce_zero_label=True),
+            dict(type='RandomFlip', prob=0.5),
+            dict(type='ToTensor', keys=['img', 'gt_semantic_seg']),
+            dict(
+                type='TorchNormalize',
+                means=[
+                    494.905781, 815.239594, 924.335066, 2968.881459,
+                    2634.621962, 1739.579917, 494.905781, 815.239594,
+                    924.335066, 2968.881459, 2634.621962, 1739.579917,
+                    494.905781, 815.239594, 924.335066, 2968.881459,
+                    2634.621962, 1739.579917
+                ],
+                stds=[
+                    284.925432, 357.84876, 575.566823, 896.601013, 951.900334,
+                    921.407808, 284.925432, 357.84876, 575.566823, 896.601013,
+                    951.900334, 921.407808, 284.925432, 357.84876, 575.566823,
+                    896.601013, 951.900334, 921.407808
+                ]),
+            dict(type='TorchRandomCrop', crop_size=(224, 224)),
+            dict(type='Reshape', keys=['img'], new_shape=(6, 3, 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'])
+        ],
+        img_suffix='_merged.tif',
+        seg_map_suffix='.mask.tif',
+        split=
+        '/home/ubuntu/hls-foundation-os/fine-tuning-examples/data_splits/crop_classification/training_data.txt'
+    ),
+    val=dict(
+        type='GeospatialDataset',
+        CLASSES=(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13),
+        reduce_zero_label=True,
+        data_root='/home/ubuntu/hls_cdl_reclassed/',
+        img_dir='/home/ubuntu/hls_cdl_reclassed/validation_chips',
+        ann_dir='/home/ubuntu/hls_cdl_reclassed/validation_chips',
+        pipeline=[
+            dict(type='LoadGeospatialImageFromFile', to_float32=True),
+            dict(type='ToTensor', keys=['img']),
+            dict(
+                type='TorchNormalize',
+                means=[
+                    494.905781, 815.239594, 924.335066, 2968.881459,
+                    2634.621962, 1739.579917, 494.905781, 815.239594,
+                    924.335066, 2968.881459, 2634.621962, 1739.579917,
+                    494.905781, 815.239594, 924.335066, 2968.881459,
+                    2634.621962, 1739.579917
+                ],
+                stds=[
+                    284.925432, 357.84876, 575.566823, 896.601013, 951.900334,
+                    921.407808, 284.925432, 357.84876, 575.566823, 896.601013,
+                    951.900334, 921.407808, 284.925432, 357.84876, 575.566823,
+                    896.601013, 951.900334, 921.407808
+                ]),
+            dict(
+                type='Reshape',
+                keys=['img'],
+                new_shape=(6, 3, -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'
+                ])
+        ],
+        img_suffix='_merged.tif',
+        seg_map_suffix='.mask.tif',
+        split=
+        '/home/ubuntu/hls-foundation-os/fine-tuning-examples/data_splits/crop_classification/validation_data.txt'
+    ),
+    test=dict(
+        type='GeospatialDataset',
+        CLASSES=(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13),
+        reduce_zero_label=True,
+        data_root='/home/ubuntu/hls_cdl_reclassed/',
+        img_dir='/home/ubuntu/hls_cdl_reclassed/validation_chips',
+        ann_dir='/home/ubuntu/hls_cdl_reclassed/validation_chips',
+        pipeline=[
+            dict(type='LoadGeospatialImageFromFile', to_float32=True),
+            dict(type='ToTensor', keys=['img']),
+            dict(
+                type='TorchNormalize',
+                means=[
+                    494.905781, 815.239594, 924.335066, 2968.881459,
+                    2634.621962, 1739.579917, 494.905781, 815.239594,
+                    924.335066, 2968.881459, 2634.621962, 1739.579917,
+                    494.905781, 815.239594, 924.335066, 2968.881459,
+                    2634.621962, 1739.579917
+                ],
+                stds=[
+                    284.925432, 357.84876, 575.566823, 896.601013, 951.900334,
+                    921.407808, 284.925432, 357.84876, 575.566823, 896.601013,
+                    951.900334, 921.407808, 284.925432, 357.84876, 575.566823,
+                    896.601013, 951.900334, 921.407808
+                ]),
+            dict(
+                type='Reshape',
+                keys=['img'],
+                new_shape=(6, 3, -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'
+                ])
+        ],
+        img_suffix='_merged.tif',
+        seg_map_suffix='.mask.tif',
+        split=
+        '/home/ubuntu/hls-foundation-os/fine-tuning-examples/data_splits/crop_classification/validation_data.txt'
+    ))
+optimizer = dict(
+    type='Adam', lr=1.5e-05, betas=(0.9, 0.999), weight_decay=0.05)
+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=10,
+    hooks=[dict(type='TextLoggerHook'),
+           dict(type='TensorboardLoggerHook')])
+checkpoint_config = dict(
+    by_epoch=True,
+    interval=10,
+    out_dir='/home/ubuntu/clark_gfm_eval/multiclass_exp_newSplit')
+evaluation = dict(interval=2, metric='mIoU', pre_eval=True, save_best='mIoU')
+reduce_train_set = dict(reduce_train_set=False)
+reduce_factor = dict(reduce_factor=1)
+runner = dict(type='EpochBasedRunner', max_epochs=80)
+workflow = [('train', 1), ('val', 1)]
+norm_cfg = dict(type='BN', requires_grad=True)
+loss_weights_multi = [
+    0.386375, 0.661126, 0.548184, 0.640482, 0.876862, 0.925186, 3.249462,
+    1.542289, 2.175141, 2.272419, 3.062762, 3.626097, 1.198702
+]
+loss_func = dict(
+    type='CrossEntropyLoss',
+    use_sigmoid=False,
+    class_weight=[
+        0.386375, 0.661126, 0.548184, 0.640482, 0.876862, 0.925186, 3.249462,
+        1.542289, 2.175141, 2.272419, 3.062762, 3.626097, 1.198702
+    ],
+    avg_non_ignore=True)
+output_embed_dim = 2304
+model = dict(
+    type='TemporalEncoderDecoder',
+    frozen_backbone=False,
+    backbone=dict(
+        type='TemporalViTEncoder',
+        pretrained='/home/ubuntu/hls-loss-weights/Prithvi_100M.pt',
+        img_size=224,
+        patch_size=16,
+        num_frames=3,
+        tubelet_size=1,
+        in_chans=6,
+        embed_dim=768,
+        depth=6,
+        num_heads=8,
+        mlp_ratio=4.0,
+        norm_pix_loss=False),
+    neck=dict(
+        type='ConvTransformerTokensToEmbeddingNeck',
+        embed_dim=2304,
+        output_embed_dim=2304,
+        drop_cls_token=True,
+        Hp=14,
+        Wp=14),
+    decode_head=dict(
+        num_classes=13,
+        in_channels=2304,
+        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='CrossEntropyLoss',
+            use_sigmoid=False,
+            class_weight=[
+                0.386375, 0.661126, 0.548184, 0.640482, 0.876862, 0.925186,
+                3.249462, 1.542289, 2.175141, 2.272419, 3.062762, 3.626097,
+                1.198702
+            ],
+            avg_non_ignore=True)),
+    auxiliary_head=dict(
+        num_classes=13,
+        in_channels=2304,
+        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='CrossEntropyLoss',
+            use_sigmoid=False,
+            class_weight=[
+                0.386375, 0.661126, 0.548184, 0.640482, 0.876862, 0.925186,
+                3.249462, 1.542289, 2.175141, 2.272419, 3.062762, 3.626097,
+                1.198702
+            ],
+            avg_non_ignore=True)),
+    train_cfg=dict(),
+    test_cfg=dict(mode='slide', stride=(112, 112), crop_size=(224, 224)))
+auto_resume = False

multi_temporal_crop_classification_best_mIoU_epoch_66.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ec4bbbdca96bbd7a588c78b4a6c98dfa5969e4f870b705fa256047b7203a703d
+size 1680477067

multi_temporal_crop_classification_latest.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:298953c90e6fd2c135303644e548c479c30eddccb81f350ce3b992b8df2aacb7
+size 1680477067