VST
Collection
A comprehensive framework designed to cultivate VLMs with human-like visuospatial abilities. • 6 items • Updated • 6
Dataset Preview
The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 2 new columns ({'data_source', 'question'}) and 6 missing columns ({'category_cn', 'camera_extrinsics', 'extra_info', 'camera_intrinsics', 'height', 'width'}).
This happened while the json dataset builder was generating data using
hf://datasets/rayruiyang/vst_3d_grounding_benchmark/sunrgbd/annotations/sunrgbd_val_total3d-prompt_v4_norm.json (at revision 497c8f67fe3a3f41672363ffb76c0e65976904af), [/tmp/hf-datasets-cache/medium/datasets/39553047813114-config-parquet-and-info-rayruiyang-vst_3d_groundi-597c3485/hub/datasets--rayruiyang--vst_3d_grounding_benchmark/snapshots/497c8f67fe3a3f41672363ffb76c0e65976904af/sunrgbd/annotations/sunrgbd_total3d_val_metaqa_20250321.json (origin=hf://datasets/rayruiyang/vst_3d_grounding_benchmark@497c8f67fe3a3f41672363ffb76c0e65976904af/sunrgbd/annotations/sunrgbd_total3d_val_metaqa_20250321.json), /tmp/hf-datasets-cache/medium/datasets/39553047813114-config-parquet-and-info-rayruiyang-vst_3d_groundi-597c3485/hub/datasets--rayruiyang--vst_3d_grounding_benchmark/snapshots/497c8f67fe3a3f41672363ffb76c0e65976904af/sunrgbd/annotations/sunrgbd_val_total3d-prompt_v4_norm.json (origin=hf://datasets/rayruiyang/vst_3d_grounding_benchmark@497c8f67fe3a3f41672363ffb76c0e65976904af/sunrgbd/annotations/sunrgbd_val_total3d-prompt_v4_norm.json)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 674, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
uid: string
image_path: string
question: string
answer: list<item: struct<bbox_3d: list<item: double>, label: string>>
child 0, item: struct<bbox_3d: list<item: double>, label: string>
child 0, bbox_3d: list<item: double>
child 0, item: double
child 1, label: string
category: string
data_source: string
-- schema metadata --
pandas: '{"index_columns": [], "column_indexes": [], "columns": [{"name":' + 817
to
{'uid': Value('string'), 'image_path': Value('string'), 'camera_intrinsics': {'cx': Value('float64'), 'cy': Value('float64'), 'fx': Value('float64'), 'fy': Value('float64')}, 'camera_extrinsics': List(List(Value('int64'))), 'width': Value('int64'), 'height': Value('int64'), 'answer': List(List(Value('float64'))), 'category': Value('string'), 'category_cn': Value('string'), 'extra_info': {'K': List(List(Value('float64'))), 'R': List(List(Value('float64'))), 'annotations': List({'R_bbox2cam': List(List(Value('float64'))), 'bbox2D_proj': List(Value('float64')), 'bbox2D_tight': List(Value('float64')), 'bbox2D_trunc': List(Value('float64')), 'bbox3D_cam': List(List(Value('float64'))), 'category': Value('string'), 'category_cn': Value('string'), 'category_old': Value('string'), 'category_original': Value('string'), 'category_total3d': Value('string'), 'centroid_cam': List(Value('float64')), 'dimensions': List(Value('float64')), 'id': Value('int64'), 'image_id': Value('int64'), 'image_uid': Value('string'), 'uid': Value('string')}), 'file_name': Value('string'), 'height': Value('int64'), 'history': {'file_name_votenate': Value('string')}, 'id': Value('int64'), 'src_90_rotate': Value('bool'), 'uid': Value('string'), 'width': Value('int64')}}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1347, in compute_config_parquet_and_info_response
parquet_operations = convert_to_parquet(builder)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 980, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1736, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1889, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 2 new columns ({'data_source', 'question'}) and 6 missing columns ({'category_cn', 'camera_extrinsics', 'extra_info', 'camera_intrinsics', 'height', 'width'}).
This happened while the json dataset builder was generating data using
hf://datasets/rayruiyang/vst_3d_grounding_benchmark/sunrgbd/annotations/sunrgbd_val_total3d-prompt_v4_norm.json (at revision 497c8f67fe3a3f41672363ffb76c0e65976904af), [/tmp/hf-datasets-cache/medium/datasets/39553047813114-config-parquet-and-info-rayruiyang-vst_3d_groundi-597c3485/hub/datasets--rayruiyang--vst_3d_grounding_benchmark/snapshots/497c8f67fe3a3f41672363ffb76c0e65976904af/sunrgbd/annotations/sunrgbd_total3d_val_metaqa_20250321.json (origin=hf://datasets/rayruiyang/vst_3d_grounding_benchmark@497c8f67fe3a3f41672363ffb76c0e65976904af/sunrgbd/annotations/sunrgbd_total3d_val_metaqa_20250321.json), /tmp/hf-datasets-cache/medium/datasets/39553047813114-config-parquet-and-info-rayruiyang-vst_3d_groundi-597c3485/hub/datasets--rayruiyang--vst_3d_grounding_benchmark/snapshots/497c8f67fe3a3f41672363ffb76c0e65976904af/sunrgbd/annotations/sunrgbd_val_total3d-prompt_v4_norm.json (origin=hf://datasets/rayruiyang/vst_3d_grounding_benchmark@497c8f67fe3a3f41672363ffb76c0e65976904af/sunrgbd/annotations/sunrgbd_val_total3d-prompt_v4_norm.json)]
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
uid string | image_path string | camera_intrinsics dict | camera_extrinsics list | width int64 | height int64 | answer list | category string | category_cn string | extra_info dict |
|---|---|---|---|---|---|---|---|---|---|
6d410a16-449d-46bd-a5f6-96799c4b1e20 | sunrgbd/val/sunrgbd_000001.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
0,
0,
0
],
[
0,
1,
0,
0
],
[
0,
0,
1,
0
]
] | 730 | 530 | [
[
-1.07,
-0.31,
1.8900000000000001,
0.71,
2.1,
1.56,
7.14,
5.09,
12.3
],
[
-0.8,
-0.47000000000000003,
3.83,
0.6000000000000001,
2.04,
1.9500000000000002,
7.14,
5.29,
12.32
]
] | dresser | 梳妆台 | {
"K": [
[
529.5,
0,
365
],
[
0,
529.5,
265
],
[
0,
0,
1
]
],
"R": [
[
0.9795900000000001,
0.012593,
0.20061
],
[
0.20061,
-0.12377,
-0.9718200000000001
],
[
0.012593,
... |
7a1be633-438a-4a2e-b89c-09bcf034000a | sunrgbd/val/sunrgbd_000001.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
0,
0,
0
],
[
0,
1,
0,
0
],
[
0,
0,
1,
0
]
] | 730 | 530 | [
[
1.03,
-0.07,
4.18,
2.3,
1.97,
1.8900000000000001,
131.9,
80.43,
143.97
]
] | bed | 床 | {
"K": [
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529.5,
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],
[
0,
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],
"R": [
[
0.9795900000000001,
0.012593,
0.20061
],
[
0.20061,
-0.12377,
-0.9718200000000001
],
[
0.012593,
... |
aea8bbf2-4148-46b7-9212-234d3e46f0ec | sunrgbd/val/sunrgbd_000001.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
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0,
0
],
[
0,
1,
0,
0
],
[
0,
0,
1,
0
]
] | 730 | 530 | [
[
2.6,
-0.19,
4.78,
0.43,
0.88,
0.64,
137.43,
79.46,
149.58
]
] | lamp | 灯 | {
"K": [
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529.5,
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[
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529.5,
265
],
[
0,
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1
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],
"R": [
[
0.9795900000000001,
0.012593,
0.20061
],
[
0.20061,
-0.12377,
-0.9718200000000001
],
[
0.012593,
... |
1a9dac58-3273-4b71-b98c-c2f8e9f04744 | sunrgbd/val/sunrgbd_000002.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
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],
[
0,
1,
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],
[
0,
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]
] | 730 | 530 | [
[
-0.6000000000000001,
0.1,
2.59,
2.4,
1.5899999999999999,
2.14,
153.07,
75.18,
165.55
]
] | bed | 床 | {
"K": [
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529.5,
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"R": [
[
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0.011826999999999999,
0.20136
],
[
0.20136,
-0.11586,
-0.9726400000000001
],
[
0.01... |
0aaba9ed-3932-4112-b905-987b5fd51fb4 | sunrgbd/val/sunrgbd_000003.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
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[
0,
1,
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],
[
0,
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]
] | 730 | 530 | [
[
-0.23,
0.2,
3.19,
2.25,
1.4100000000000001,
1.65,
118.11,
84.84,
126.26
]
] | bed | 床 | {
"K": [
[
529.5,
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529.5,
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[
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"R": [
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0.9902000000000001,
0.005575999999999999,
0.13957
],
[
0.13957,
-0.079386,
-0.9870300000000001
],
[
0.0... |
2f4877ac-0827-4de8-9df9-99d541e2385c | sunrgbd/val/sunrgbd_000003.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
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[
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] | 730 | 530 | [
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1.9500000000000002,
1.56,
140.25,
82.87,
148.52
],
[
-1.65,
0.14,
4.1,
0.63,
0.86,
1.19,
115.42,
84.96,
123.55
]
] | dresser | 梳妆台 | {
"K": [
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529.5,
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],
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],
[
0.13957,
-0.079386,
-0.9870300000000001
],
[
0.0... |
d5a0f3b8-a3d5-4770-8b2c-87a5d0141cd8 | sunrgbd/val/sunrgbd_000003.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
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1,
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[
0,
1,
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[
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] | 730 | 530 | [
[
1.09,
0.1,
4.13,
0.29,
0.67,
0.44,
65.18,
84.98,
73.15
]
] | lamp | 灯 | {
"K": [
[
529.5,
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[
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],
"R": [
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0.9902000000000001,
0.005575999999999999,
0.13957
],
[
0.13957,
-0.079386,
-0.9870300000000001
],
[
0.0... |
b118db91-32da-47b2-a1e6-58c0b11732a7 | sunrgbd/val/sunrgbd_000004.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
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],
[
0,
1,
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],
[
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] | 730 | 530 | [
[
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3.1,
1.99,
1.58,
1.81,
49.79,
74.21,
48.88
]
] | bed | 床 | {
"K": [
[
529.5,
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[
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],
[
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],
"R": [
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],
[
0.003104,
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-0.97816
],
[
0.000326,
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f0c9138d-d2bf-47d2-bbb7-b4636eb7238e | sunrgbd/val/sunrgbd_000004.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
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] | 730 | 530 | [
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0.8200000000000001,
0.47000000000000003,
42.95,
72.24,
41.74
]
] | lamp | 灯 | {
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],
[
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-0.20783000000000001,
-0.97816
],
[
0.000326,
0.97816,... |
2649e8c0-ff0e-4ecf-8d30-88df067fb185 | sunrgbd/val/sunrgbd_000005.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
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0,
0
],
[
0,
1,
0,
0
],
[
0,
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] | 730 | 530 | [
[
1.5899999999999999,
0.32,
2.08,
0.42,
1.8399999999999999,
1.04,
174.42,
42.46,
-177.19
]
] | dresser | 梳妆台 | {
"K": [
[
529.5,
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],
[
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529.5,
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],
[
0,
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],
"R": [
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0.11422000000000002
],
[
0.11422000000000002,
-0.071675,
-0.99087
],
[
0.004112,
... |
6acb336e-fa49-4c6a-9700-bde334c87b39 | sunrgbd/val/sunrgbd_000005.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
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1,
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0
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[
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1,
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[
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] | 730 | 530 | [
[
0.08,
0.23,
2.55,
2.22,
1.5899999999999999,
1.45,
174.66,
39.65,
-176.84
]
] | bed | 床 | {
"K": [
[
529.5,
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],
[
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[
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],
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0.11422000000000002
],
[
0.11422000000000002,
-0.071675,
-0.99087
],
[
0.004112,
... |
72cf6802-4609-441e-88a7-f2b442e3eaa9 | sunrgbd/val/sunrgbd_000006.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
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1,
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0
],
[
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1,
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],
[
0,
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]
] | 730 | 530 | [
[
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2.6,
2.1,
1.6,
1.8,
85.9,
83.53,
89.91
]
] | bed | 床 | {
"K": [
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529.5,
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[
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[
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],
"R": [
[
0.99755,
0.003939,
0.06981000000000001
],
[
0.06981000000000001,
-0.11236000000000002,
-0.99121
],
[
0.... |
11402c73-b3d7-47d4-af7f-1ae0af819fab | sunrgbd/val/sunrgbd_000006.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
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[
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[
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] | 730 | 530 | [
[
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1.48,
1.16,
72.71,
83.24,
76.63
]
] | dresser | 梳妆台 | {
"K": [
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529.5,
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[
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],
[
0,
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],
"R": [
[
0.99755,
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],
[
0.06981000000000001,
-0.11236000000000002,
-0.99121
],
[
0.... |
80ab2d89-d732-4dc3-8bbf-594b9317c827 | sunrgbd/val/sunrgbd_000006.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
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0,
0
],
[
0,
1,
0,
0
],
[
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] | 730 | 530 | [
[
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3.41,
0.30000000000000004,
0.85,
0.42,
87.99,
83.54,
92.01
]
] | lamp | 灯 | {
"K": [
[
529.5,
0,
365
],
[
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529.5,
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],
[
0,
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1
]
],
"R": [
[
0.99755,
0.003939,
0.06981000000000001
],
[
0.06981000000000001,
-0.11236000000000002,
-0.99121
],
[
0.... |
c27fdfa7-94c5-4c79-8e63-017909408c76 | sunrgbd/val/sunrgbd_000007.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
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0,
0
],
[
0,
1,
0,
0
],
[
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]
] | 730 | 530 | [
[
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0.36,
3.38,
2.29,
1.4,
1.6400000000000001,
14.31,
72.58,
21.51
]
] | bed | 床 | {
"K": [
[
529.5,
0,
365
],
[
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0,
0
],
[
0,
0,
1,
0
]
] | 730 | 530 | [
[
-0.05,
0.31,
2.88,
2.19,
1.53,
1.67,
6.95,
55.65,
10.95
]
] | bed | 床 | {
"K": [
[
529.5,
0,
365
],
[
0,
529.5,
265
],
[
0,
0,
1
]
],
"R": [
[
0.99589,
0.0030989999999999998,
0.090547
],
[
0.090547,
-0.06823699999999999,
-0.99355
],
[
0.003098999... |
81d7ce74-ef3e-4df8-9646-20d14adaa997 | sunrgbd/val/sunrgbd_000016.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
0,
0,
0
],
[
0,
1,
0,
0
],
[
0,
0,
1,
0
]
] | 730 | 530 | [
[
-1.55,
-0.24,
2.95,
0.4,
0.72,
0.47000000000000003,
7.13,
56.65,
11.17
]
] | lamp | 灯 | {
"K": [
[
529.5,
0,
365
],
[
0,
529.5,
265
],
[
0,
0,
1
]
],
"R": [
[
0.99589,
0.0030989999999999998,
0.090547
],
[
0.090547,
-0.06823699999999999,
-0.99355
],
[
0.003098999... |
8162c5b5-5cc9-40f0-b31f-1acf17e15859 | sunrgbd/val/sunrgbd_000016.jpg | {
"cx": 365,
"cy": 265,
"fx": 529.5,
"fy": 529.5
} | [
[
1,
0,
0,
0
],
[
0,
1,
0,
0
],
[
0,
0,
1,
0
]
] | 730 | 530 | [
[
2.16,
0.38,
3.14,
0.44,
1.8399999999999999,
1.2,
175.22,
35.08,
-177.55
],
[
0.97,
0.43,
4.42,
0.54,
1.37,
0.9,
104.03,
85.97,
109.27
]
] | dresser | 梳妆台 | {
"K": [
[
529.5,
0,
365
],
[
0,
529.5,
265
],
[
0,
0,
1
]
],
"R": [
[
0.99589,
0.0030989999999999998,
0.090547
],
[
0.090547,
-0.06823699999999999,
-0.99355
],
[
0.003098999... |
End of preview.
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Visual Spatial Tuning
This dataset is the 3D object detection benchmark used in VST. Please follow VST/benchmark to evaluate the models.
git clone https://github.com/Yangr116/VST.git
python tools/download_hf_data.py --repo_id="rayruiyang/vst_3d_grounding_benchmark" --local_dir $YOUR_LOCAL_PATH
cd $YOUR_LOCAL_PATH/vst_3d_grounding_benchmark
tar -zxvf arkit/arkit_omni3d_test_640x480.tar.gz -C arkit
tar -zxvf sunrgbd/sunrgbd_val.tar.gz -C sunrgbd
And, you will get:
$YOUR_LOCAL_PATH/vst_3d_grounding_benchmark
├── arkit
│ ├── annotations
│ └── arkit_wo_rotation
│ └── arkit_omni3d_test_640x480
└── sunrgbd
├── annotations
└── sunrgbd
└── val
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