Hugging Face's logo

wherobots
/
mlm-stac

English
Model card Files Community
rybavery commited on
Commit
f4fec64
•
1 Parent(s): a80d255

example MLM v1.2.0 model metadata and artifacts

Browse files
Files changed (6) hide show
  1. classification/landcover-eurosat-sentinel2/model-metadata.json +267 -0
  2. classification/landcover-eurosat-sentinel2/scripting/model.pt +3 -0
  3. object-detection/marine-satlas-sentinel2/model-metadata.json +270 -0
  4. object-detection/marine-satlas-sentinel2/scripting/model.pt +3 -0
  5. semantic-segmentation/solar-satlas-sentinel2/inductor/gpu/aot_inductor_gpu_tensor_cores.zip +3 -0
  6. semantic-segmentation/solar-satlas-sentinel2/model-metadata.json +342 -0
classification/landcover-eurosat-sentinel2/model-metadata.json ADDED
@@ -0,0 +1,267 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "type": "Feature",
3
+ "stac_version": "1.0.0",
4
+ "id": "item_landcover_eurosat_sentinel2",
5
+ "properties": {
6
+ "start_datetime": "1900-01-01T00:00:00Z",
7
+ "end_datetime": "9999-01-01T00:00:00Z",
8
+ "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.",
9
+ "mlm:framework": "pytorch",
10
+ "mlm:framework_version": "2.3.0+cu121",
11
+ "file:size": 91000000,
12
+ "mlm:memory_size": 94452432,
13
+ "mlm:batch_size_suggestion": 3300,
14
+ "mlm:accelerator": "cuda",
15
+ "mlm:accelerator_constrained": false,
16
+ "mlm:accelerator_summary": "Unknown",
17
+ "mlm:name": "Resnet-18 Sentinel-2 ALL MOCO",
18
+ "mlm:architecture": "ResNet-18",
19
+ "mlm:tasks": [
20
+ "scene-classification"
21
+ ],
22
+ "mlm:input": [
23
+ {
24
+ "name": "13 Band Sentinel-2 Batch",
25
+ "bands": [
26
+ "B01",
27
+ "B02",
28
+ "B03",
29
+ "B04",
30
+ "B05",
31
+ "B06",
32
+ "B07",
33
+ "B08",
34
+ "B8A",
35
+ "B09",
36
+ "B10",
37
+ "B11",
38
+ "B12"
39
+ ],
40
+ "input": {
41
+ "shape": [
42
+ -1,
43
+ 13,
44
+ 64,
45
+ 64
46
+ ],
47
+ "dim_order": [
48
+ "batch",
49
+ "channel",
50
+ "height",
51
+ "width"
52
+ ],
53
+ "data_type": "float32"
54
+ },
55
+ "norm_by_channel": true,
56
+ "norm_type": "z-score",
57
+ "statistics": [
58
+ {
59
+ "mean": 1354.40546513,
60
+ "stddev": 245.71762908
61
+ },
62
+ {
63
+ "mean": 1118.24399958,
64
+ "stddev": 333.00778264
65
+ },
66
+ {
67
+ "mean": 1042.92983953,
68
+ "stddev": 395.09249139
69
+ },
70
+ {
71
+ "mean": 947.62620298,
72
+ "stddev": 593.75055589
73
+ },
74
+ {
75
+ "mean": 1199.47283961,
76
+ "stddev": 566.4170017
77
+ },
78
+ {
79
+ "mean": 1999.79090914,
80
+ "stddev": 861.18399006
81
+ },
82
+ {
83
+ "mean": 2369.22292565,
84
+ "stddev": 1086.63139075
85
+ },
86
+ {
87
+ "mean": 2296.82608323,
88
+ "stddev": 1117.98170791
89
+ },
90
+ {
91
+ "mean": 732.08340178,
92
+ "stddev": 404.91978886
93
+ },
94
+ {
95
+ "mean": 12.11327804,
96
+ "stddev": 4.77584468
97
+ },
98
+ {
99
+ "mean": 1819.01027855,
100
+ "stddev": 1002.58768311
101
+ },
102
+ {
103
+ "mean": 1118.92391149,
104
+ "stddev": 761.30323499
105
+ },
106
+ {
107
+ "mean": 2594.14080798,
108
+ "stddev": 1231.58581042
109
+ }
110
+ ],
111
+ "pre_processing_function": {
112
+ "format": "python",
113
+ "expression": "torchgeo.datamodules.eurosat.EuroSATDataModule.collate_fn"
114
+ }
115
+ }
116
+ ],
117
+ "mlm:output": [
118
+ {
119
+ "name": "scene-classification",
120
+ "tasks": [
121
+ "scene-classification"
122
+ ],
123
+ "result": {
124
+ "shape": [
125
+ -1,
126
+ 10
127
+ ],
128
+ "dim_order": [
129
+ "batch",
130
+ "class"
131
+ ],
132
+ "data_type": "float32"
133
+ },
134
+ "classification:classes": [
135
+ {
136
+ "value": 0,
137
+ "name": "Annual Crop",
138
+ "description": "Annual Crop"
139
+ },
140
+ {
141
+ "value": 1,
142
+ "name": "Forest",
143
+ "description": "Forest"
144
+ },
145
+ {
146
+ "value": 2,
147
+ "name": "Herbaceous Vegetation",
148
+ "description": "Herbaceous Vegetation"
149
+ },
150
+ {
151
+ "value": 3,
152
+ "name": "Highway",
153
+ "description": "Highway"
154
+ },
155
+ {
156
+ "value": 4,
157
+ "name": "Industrial Buildings",
158
+ "description": "Industrial Buildings"
159
+ },
160
+ {
161
+ "value": 5,
162
+ "name": "Pasture",
163
+ "description": "Pasture"
164
+ },
165
+ {
166
+ "value": 6,
167
+ "name": "Permanent Crop",
168
+ "description": "Permanent Crop"
169
+ },
170
+ {
171
+ "value": 7,
172
+ "name": "Residential Buildings",
173
+ "description": "Residential Buildings"
174
+ },
175
+ {
176
+ "value": 8,
177
+ "name": "River",
178
+ "description": "River"
179
+ },
180
+ {
181
+ "value": 9,
182
+ "name": "SeaLake",
183
+ "description": "SeaLake"
184
+ }
185
+ ],
186
+ "post_processing_function": null
187
+ }
188
+ ],
189
+ "mlm:total_parameters": 11700000,
190
+ "mlm:pretrained": true,
191
+ "mlm:pretrained_source": "EuroSat Sentinel-2",
192
+ "datetime": null
193
+ },
194
+ "geometry": {
195
+ "type": "Polygon",
196
+ "coordinates": [
197
+ [
198
+ [
199
+ -7.882190080512502,
200
+ 37.13739173208318
201
+ ],
202
+ [
203
+ -7.882190080512502,
204
+ 58.21798141355221
205
+ ],
206
+ [
207
+ 27.911651652899923,
208
+ 58.21798141355221
209
+ ],
210
+ [
211
+ 27.911651652899923,
212
+ 37.13739173208318
213
+ ],
214
+ [
215
+ -7.882190080512502,
216
+ 37.13739173208318
217
+ ]
218
+ ]
219
+ ]
220
+ },
221
+ "links": [
222
+ {
223
+ "rel": "derived_from",
224
+ "href": "https://earth-search.aws.element84.com/v1/collections/sentinel-2-l2a",
225
+ "type": "application/json"
226
+ },
227
+ {
228
+ "rel": "self",
229
+ "href": "s3://wherobots-modelhub-prod/community/classification/landcover-eurosat-sentinel2/model-metadata.json/item_landcover_eurosat_sentinel2.json",
230
+ "type": "application/json"
231
+ }
232
+ ],
233
+ "assets": {
234
+ "model": {
235
+ "href": "s3://wherobots-modelhub-prod/community/classification/landcover-eurosat-sentinel2/scripting/model.pt",
236
+ "type": "application/octet-stream; application=pytorch",
237
+ "title": "Pytorch weights checkpoint",
238
+ "description": "A Resnet-18 classification model trained on normalized Sentinel-2 imagery with Eurosat landcover labels with torchgeo.",
239
+ "mlm_artifact_type": "torch.jit.script",
240
+ "file:size": 43000000,
241
+ "roles": [
242
+ "mlm:model",
243
+ "data"
244
+ ]
245
+ },
246
+ "source_code": {
247
+ "href": "https://github.com/microsoft/torchgeo/blob/61efd2e2c4df7ebe3bd03002ebbaeaa3cfe9885a/torchgeo/models/resnet.py#L207",
248
+ "type": "text/x-python",
249
+ "title": "Model implementation.",
250
+ "description": "Source code to run the model.",
251
+ "roles": [
252
+ "mlm:model",
253
+ "code"
254
+ ]
255
+ }
256
+ },
257
+ "bbox": [
258
+ -7.882190080512502,
259
+ 37.13739173208318,
260
+ 27.911651652899923,
261
+ 58.21798141355221
262
+ ],
263
+ "stac_extensions": [
264
+ "https://stac-extensions.github.io/file/v2.1.0/schema.json",
265
+ "https://crim-ca.github.io/mlm-extension/v1.2.0/schema.json"
266
+ ]
267
+ }
classification/landcover-eurosat-sentinel2/scripting/model.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:509b72ac9ba7e27ab190e80df28cc2c51b3d00154dce5f9842ecc120c918443c
3
+ size 94609271
object-detection/marine-satlas-sentinel2/model-metadata.json ADDED
@@ -0,0 +1,270 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "type": "Feature",
3
+ "stac_version": "1.0.0",
4
+ "id": "item_marine_satlas_sentinel2",
5
+ "properties": {
6
+ "start_datetime": "1900-01-01T00:00:00Z",
7
+ "end_datetime": "9999-01-01T00:00:00Z",
8
+ "description": "Sourced from satlas source code released by Allen AI under Apache 2.0. The forward pass was rewritten for torchscripting. Batch size suggestion is based on running on a NVIDIA 3090 with 24GB of GPU memory",
9
+ "mlm:framework": "pytorch",
10
+ "mlm:framework_version": "2.3.0+cu121",
11
+ "file:size": 333000000,
12
+ "mlm:memory_size": 389750988,
13
+ "mlm:batch_size_suggestion": 9,
14
+ "mlm:accelerator": "cuda",
15
+ "mlm:accelerator_constrained": false,
16
+ "mlm:accelerator_summary": "It is recommended to use a GPU due to the computational demands of the model.",
17
+ "mlm:name": "Satlas Marine Infrastucture Detection",
18
+ "mlm:architecture": "Swin Transformer V2 with R-CNN head",
19
+ "mlm:tasks": [
20
+ "object-detection"
21
+ ],
22
+ "mlm:input": [
23
+ {
24
+ "name": "3 Band Sentinel-2 3 Time Step Series Batch",
25
+ "bands": [
26
+ "B02",
27
+ "B03",
28
+ "B04",
29
+ "B02",
30
+ "B03",
31
+ "B04",
32
+ "B02",
33
+ "B03",
34
+ "B04"
35
+ ],
36
+ "input": {
37
+ "shape": [
38
+ -1,
39
+ 9,
40
+ 1024,
41
+ 1024
42
+ ],
43
+ "dim_order": [
44
+ "batch",
45
+ "channel",
46
+ "height",
47
+ "width"
48
+ ],
49
+ "data_type": "float32"
50
+ },
51
+ "norm_by_channel": true,
52
+ "norm_type": "min-max",
53
+ "resize_type": "crop",
54
+ "statistics": [
55
+ {
56
+ "minimum": 0,
57
+ "maximum": 255
58
+ },
59
+ {
60
+ "minimum": 0,
61
+ "maximum": 255
62
+ },
63
+ {
64
+ "minimum": 0,
65
+ "maximum": 255
66
+ },
67
+ {
68
+ "minimum": 0,
69
+ "maximum": 255
70
+ },
71
+ {
72
+ "minimum": 0,
73
+ "maximum": 255
74
+ },
75
+ {
76
+ "minimum": 0,
77
+ "maximum": 255
78
+ },
79
+ {
80
+ "minimum": 0,
81
+ "maximum": 255
82
+ },
83
+ {
84
+ "minimum": 0,
85
+ "maximum": 255
86
+ },
87
+ {
88
+ "minimum": 0,
89
+ "maximum": 255
90
+ }
91
+ ],
92
+ "pre_processing_function": {
93
+ "format": "documentation-link",
94
+ "expression": "https://github.com/allenai/satlas/blob/main/Normalization.md#sentinel-2-example"
95
+ }
96
+ }
97
+ ],
98
+ "mlm:output": [
99
+ {
100
+ "name": "bboxes",
101
+ "tasks": [
102
+ "object-detection"
103
+ ],
104
+ "result": {
105
+ "shape": [
106
+ -1,
107
+ -1,
108
+ 4
109
+ ],
110
+ "dim_order": [
111
+ "batch",
112
+ "detections",
113
+ "coordinates"
114
+ ],
115
+ "data_type": "float32"
116
+ },
117
+ "classification:classes": [
118
+ {
119
+ "value": 1,
120
+ "name": "wind_turbine",
121
+ "description": "wind_turbine"
122
+ },
123
+ {
124
+ "value": 2,
125
+ "name": "platform",
126
+ "description": "platform"
127
+ }
128
+ ],
129
+ "post_processing_function": null
130
+ },
131
+ {
132
+ "name": "labels",
133
+ "tasks": [
134
+ "object-detection"
135
+ ],
136
+ "result": {
137
+ "shape": [
138
+ -1,
139
+ -1
140
+ ],
141
+ "dim_order": [
142
+ "batch",
143
+ "detections"
144
+ ],
145
+ "data_type": "int64"
146
+ },
147
+ "classification:classes": [
148
+ {
149
+ "value": 1,
150
+ "name": "wind_turbine",
151
+ "description": "wind_turbine"
152
+ },
153
+ {
154
+ "value": 2,
155
+ "name": "platform",
156
+ "description": "platform"
157
+ }
158
+ ],
159
+ "post_processing_function": null
160
+ },
161
+ {
162
+ "name": "classes",
163
+ "tasks": [
164
+ "object-detection"
165
+ ],
166
+ "result": {
167
+ "shape": [
168
+ -1,
169
+ -1
170
+ ],
171
+ "dim_order": [
172
+ "batch",
173
+ "detections"
174
+ ],
175
+ "data_type": "float32"
176
+ },
177
+ "classification:classes": [
178
+ {
179
+ "value": 1,
180
+ "name": "wind_turbine",
181
+ "description": "wind_turbine"
182
+ },
183
+ {
184
+ "value": 2,
185
+ "name": "platform",
186
+ "description": "platform"
187
+ }
188
+ ],
189
+ "post_processing_function": null
190
+ }
191
+ ],
192
+ "mlm:total_parameters": 89748193,
193
+ "mlm:pretrained": true,
194
+ "mlm:pretrained_source": "Sentinel-2 imagery and SATLAS labels",
195
+ "datetime": null
196
+ },
197
+ "geometry": {
198
+ "type": "Polygon",
199
+ "coordinates": [
200
+ [
201
+ [
202
+ -7.882190080512502,
203
+ 37.13739173208318
204
+ ],
205
+ [
206
+ -7.882190080512502,
207
+ 58.21798141355221
208
+ ],
209
+ [
210
+ 27.911651652899923,
211
+ 58.21798141355221
212
+ ],
213
+ [
214
+ 27.911651652899923,
215
+ 37.13739173208318
216
+ ],
217
+ [
218
+ -7.882190080512502,
219
+ 37.13739173208318
220
+ ]
221
+ ]
222
+ ]
223
+ },
224
+ "links": [
225
+ {
226
+ "rel": "derived_from",
227
+ "href": "https://earth-search.aws.element84.com/v1/collections/sentinel-2-l1c",
228
+ "type": "application/json"
229
+ },
230
+ {
231
+ "rel": "self",
232
+ "href": "s3://wherobots-modelhub-prod/professional/object-detection/marine-satlas-sentinel2/model-metadata.json/item_marine_satlas_sentinel2.json",
233
+ "type": "application/json"
234
+ }
235
+ ],
236
+ "assets": {
237
+ "model": {
238
+ "href": "s3://wherobots-modelhub-prod/professional/object-detection/marine-satlas-sentinel2/scripting/model.pt",
239
+ "type": "application/octet-stream; application=pytorch",
240
+ "title": "TorchScript model exported from private, edited, hard fork of Satlas github repo.",
241
+ "description": "A Swin Transformer backbone with an R-CNN based head trained on the visual Sentinel-2 Top of Atmosphere product.",
242
+ "mlm_artifact_type": "torch.jit.script",
243
+ "file:size": 333000000,
244
+ "roles": [
245
+ "mlm:model",
246
+ "data"
247
+ ]
248
+ },
249
+ "source_code": {
250
+ "href": "https://github.com/wherobots/modelhub/blob/main/model-forge/satlas/marine/export.py",
251
+ "type": "text/x-python",
252
+ "title": "Model implementation.",
253
+ "description": "Source code to export the model.",
254
+ "roles": [
255
+ "mlm:model",
256
+ "code"
257
+ ]
258
+ }
259
+ },
260
+ "bbox": [
261
+ -7.882190080512502,
262
+ 37.13739173208318,
263
+ 27.911651652899923,
264
+ 58.21798141355221
265
+ ],
266
+ "stac_extensions": [
267
+ "https://stac-extensions.github.io/file/v2.1.0/schema.json",
268
+ "https://crim-ca.github.io/mlm-extension/v1.2.0/schema.json"
269
+ ]
270
+ }
object-detection/marine-satlas-sentinel2/scripting/model.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:750db01db1b5620280e4fbb26a15d6acd36e32e102cfde9997d808160a13718e
3
+ size 390116647
semantic-segmentation/solar-satlas-sentinel2/inductor/gpu/aot_inductor_gpu_tensor_cores.zip ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b0d83883eb4bb502dda877b3199459229dd60881e1fc61c73c76024cc5b949e4
3
+ size 656424207
semantic-segmentation/solar-satlas-sentinel2/model-metadata.json ADDED
@@ -0,0 +1,342 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "type": "Feature",
3
+ "stac_version": "1.0.0",
4
+ "id": "item_solar_satlas_sentinel2",
5
+ "properties": {
6
+ "start_datetime": "1900-01-01T00:00:00Z",
7
+ "end_datetime": "9999-01-01T00:00:00Z",
8
+ "description": "Sourced from satlas source code released by Allen AI under Apache 2.0",
9
+ "mlm:framework": "pytorch",
10
+ "mlm:framework_version": "2.3.0+cu121",
11
+ "file:size": 333000000,
12
+ "mlm:memory_size": 1,
13
+ "mlm:batch_size_suggestion": 10,
14
+ "mlm:accelerator": "cuda",
15
+ "mlm:accelerator_constrained": true,
16
+ "mlm:accelerator_summary": "It is necessary to use GPU since it was compiled for NVIDIA Ampere and newer architectures with AOTInductor and the computational demands of the model.",
17
+ "mlm:name": "Satlas Solar Farm Segmentation",
18
+ "mlm:architecture": "Swin Transformer V2 with U-Net head",
19
+ "mlm:tasks": [
20
+ "semantic-segmentation",
21
+ "segmentation"
22
+ ],
23
+ "mlm:input": [
24
+ {
25
+ "name": "9 Band Sentinel-2 4 Time Step Series Batch",
26
+ "bands": [
27
+ "B02",
28
+ "B03",
29
+ "B04",
30
+ "B05",
31
+ "B06",
32
+ "B07",
33
+ "B08",
34
+ "B11",
35
+ "B12",
36
+ "B02",
37
+ "B03",
38
+ "B04",
39
+ "B05",
40
+ "B06",
41
+ "B07",
42
+ "B08",
43
+ "B11",
44
+ "B12",
45
+ "B02",
46
+ "B03",
47
+ "B04",
48
+ "B05",
49
+ "B06",
50
+ "B07",
51
+ "B08",
52
+ "B11",
53
+ "B12",
54
+ "B02",
55
+ "B03",
56
+ "B04",
57
+ "B05",
58
+ "B06",
59
+ "B07",
60
+ "B08",
61
+ "B11",
62
+ "B12"
63
+ ],
64
+ "input": {
65
+ "shape": [
66
+ -1,
67
+ 36,
68
+ 1024,
69
+ 1024
70
+ ],
71
+ "dim_order": [
72
+ "batch",
73
+ "channel",
74
+ "height",
75
+ "width"
76
+ ],
77
+ "data_type": "float32"
78
+ },
79
+ "norm_by_channel": true,
80
+ "norm_type": "min-max",
81
+ "resize_type": "crop",
82
+ "statistics": [
83
+ {
84
+ "minimum": 0,
85
+ "maximum": 255
86
+ },
87
+ {
88
+ "minimum": 0,
89
+ "maximum": 255
90
+ },
91
+ {
92
+ "minimum": 0,
93
+ "maximum": 255
94
+ },
95
+ {
96
+ "minimum": 0,
97
+ "maximum": 255
98
+ },
99
+ {
100
+ "minimum": 0,
101
+ "maximum": 255
102
+ },
103
+ {
104
+ "minimum": 0,
105
+ "maximum": 255
106
+ },
107
+ {
108
+ "minimum": 0,
109
+ "maximum": 255
110
+ },
111
+ {
112
+ "minimum": 0,
113
+ "maximum": 255
114
+ },
115
+ {
116
+ "minimum": 0,
117
+ "maximum": 255
118
+ },
119
+ {
120
+ "minimum": 0,
121
+ "maximum": 255
122
+ },
123
+ {
124
+ "minimum": 0,
125
+ "maximum": 255
126
+ },
127
+ {
128
+ "minimum": 0,
129
+ "maximum": 255
130
+ },
131
+ {
132
+ "minimum": 0,
133
+ "maximum": 255
134
+ },
135
+ {
136
+ "minimum": 0,
137
+ "maximum": 255
138
+ },
139
+ {
140
+ "minimum": 0,
141
+ "maximum": 255
142
+ },
143
+ {
144
+ "minimum": 0,
145
+ "maximum": 255
146
+ },
147
+ {
148
+ "minimum": 0,
149
+ "maximum": 255
150
+ },
151
+ {
152
+ "minimum": 0,
153
+ "maximum": 255
154
+ },
155
+ {
156
+ "minimum": 0,
157
+ "maximum": 255
158
+ },
159
+ {
160
+ "minimum": 0,
161
+ "maximum": 255
162
+ },
163
+ {
164
+ "minimum": 0,
165
+ "maximum": 255
166
+ },
167
+ {
168
+ "minimum": 0,
169
+ "maximum": 255
170
+ },
171
+ {
172
+ "minimum": 0,
173
+ "maximum": 255
174
+ },
175
+ {
176
+ "minimum": 0,
177
+ "maximum": 255
178
+ },
179
+ {
180
+ "minimum": 0,
181
+ "maximum": 255
182
+ },
183
+ {
184
+ "minimum": 0,
185
+ "maximum": 255
186
+ },
187
+ {
188
+ "minimum": 0,
189
+ "maximum": 255
190
+ },
191
+ {
192
+ "minimum": 0,
193
+ "maximum": 255
194
+ },
195
+ {
196
+ "minimum": 0,
197
+ "maximum": 255
198
+ },
199
+ {
200
+ "minimum": 0,
201
+ "maximum": 255
202
+ },
203
+ {
204
+ "minimum": 0,
205
+ "maximum": 255
206
+ },
207
+ {
208
+ "minimum": 0,
209
+ "maximum": 255
210
+ },
211
+ {
212
+ "minimum": 0,
213
+ "maximum": 255
214
+ },
215
+ {
216
+ "minimum": 0,
217
+ "maximum": 255
218
+ },
219
+ {
220
+ "minimum": 0,
221
+ "maximum": 255
222
+ },
223
+ {
224
+ "minimum": 0,
225
+ "maximum": 255
226
+ }
227
+ ],
228
+ "pre_processing_function": {
229
+ "format": "documentation-link",
230
+ "expression": "https://github.com/allenai/satlas/blob/main/CustomInference.md#sentinel-2-inference-example"
231
+ }
232
+ }
233
+ ],
234
+ "mlm:output": [
235
+ {
236
+ "name": "confidence array",
237
+ "tasks": [
238
+ "semantic-segmentation"
239
+ ],
240
+ "result": {
241
+ "shape": [
242
+ -1,
243
+ 1,
244
+ 1024,
245
+ 1024
246
+ ],
247
+ "dim_order": [
248
+ "batch",
249
+ "height",
250
+ "width"
251
+ ],
252
+ "data_type": "float32"
253
+ },
254
+ "classification:classes": [
255
+ {
256
+ "value": 1,
257
+ "name": "Solar Farm",
258
+ "description": "Solar Farm"
259
+ }
260
+ ],
261
+ "post_processing_function": null
262
+ }
263
+ ],
264
+ "mlm:total_parameters": 89748193,
265
+ "mlm:pretrained": true,
266
+ "mlm:pretrained_source": "Sentinel-2 imagery and SATLAS labels",
267
+ "datetime": null
268
+ },
269
+ "geometry": {
270
+ "type": "Polygon",
271
+ "coordinates": [
272
+ [
273
+ [
274
+ -7.882190080512502,
275
+ 37.13739173208318
276
+ ],
277
+ [
278
+ -7.882190080512502,
279
+ 58.21798141355221
280
+ ],
281
+ [
282
+ 27.911651652899923,
283
+ 58.21798141355221
284
+ ],
285
+ [
286
+ 27.911651652899923,
287
+ 37.13739173208318
288
+ ],
289
+ [
290
+ -7.882190080512502,
291
+ 37.13739173208318
292
+ ]
293
+ ]
294
+ ]
295
+ },
296
+ "links": [
297
+ {
298
+ "rel": "derived_from",
299
+ "href": "https://earth-search.aws.element84.com/v1/collections/sentinel-2-l1c",
300
+ "type": "application/json"
301
+ },
302
+ {
303
+ "rel": "self",
304
+ "href": "s3://wherobots-modelhub-prod/professional/semantic-segmentation/solar-satlas-sentinel2/model-metadata.json/item_solar_satlas_sentinel2.json",
305
+ "type": "application/json"
306
+ }
307
+ ],
308
+ "assets": {
309
+ "model": {
310
+ "href": "s3://wherobots-modelhub-prod/professional/semantic-segmentation/solar-satlas-sentinel2/inductor/gpu/aot_inductor_gpu_tensor_cores.zip",
311
+ "type": "application/zip; application=pytorch",
312
+ "title": "AOTInductor model exported from private, edited, hard fork of Satlas github repo.",
313
+ "description": "A Swin Transformer backbone with a U-net head trained on the 9-band Sentinel-2 Top of Atmosphere product.",
314
+ "mlm_artifact_type": "torch.jit.script",
315
+ "file:size": 333000000,
316
+ "roles": [
317
+ "mlm:model",
318
+ "data"
319
+ ]
320
+ },
321
+ "source_code": {
322
+ "href": "https://github.com/wherobots/modelhub/blob/main/model-forge/satlas/solar/export.py",
323
+ "type": "text/x-python",
324
+ "title": "Model implementation.",
325
+ "description": "Source code to export the model.",
326
+ "roles": [
327
+ "mlm:model",
328
+ "code"
329
+ ]
330
+ }
331
+ },
332
+ "bbox": [
333
+ -7.882190080512502,
334
+ 37.13739173208318,
335
+ 27.911651652899923,
336
+ 58.21798141355221
337
+ ],
338
+ "stac_extensions": [
339
+ "https://stac-extensions.github.io/file/v2.1.0/schema.json",
340
+ "https://crim-ca.github.io/mlm-extension/v1.2.0/schema.json"
341
+ ]
342
+ }