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The dataset generation failed
Error code: DatasetGenerationError
Exception: TypeError
Message: Couldn't cast array of type list<item: string> to string
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
for item in generator(*args, **kwargs):
~~~~~~~~~^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2312, in cast_table_to_schema
cast_array_to_feature(
~~~~~~~~~~~~~~~~~~~~~^
table[name] if name in table_column_names else pa.array([None] * len(table), type=schema.field(name).type),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
feature,
^^^^^^^^
)
^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1861, in wrapper
return pa.chunked_array([func(chunk, *args, **kwargs) for chunk in array.chunks])
~~~~^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2152, in cast_array_to_feature
return array_cast(
array,
...<2 lines>...
allow_decimal_to_str=allow_decimal_to_str,
)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 1863, in wrapper
return func(array, *args, **kwargs)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2016, in array_cast
raise TypeError(f"Couldn't cast array of type {_short_str(array.type)} to {_short_str(pa_type)}")
TypeError: Couldn't cast array of type list<item: string> to string
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
~~~~~~~~~~~~~~~~~~~~~~~~~^
builder, max_dataset_size_bytes=max_dataset_size_bytes
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
)
^
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
for job_id, done, content in self._prepare_split_single(
~~~~~~~~~~~~~~~~~~~~~~~~~~^
gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
):
^
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
raise DatasetGenerationError("An error occurred while generating the dataset") from e
datasets.exceptions.DatasetGenerationError: An error occurred while generating the datasetNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
conversations list | image string | meta dict |
|---|---|---|
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: tower</c>bridge</c>pylon</c>mobile crane</c>truck w box</c>a330</c>train station</c>ground track field</c>bus</c>liquid cargo ship</c>dry cargo ship</c>barge</c>plane</c>container crane</c>football field</c>exp... | images/train/fd/fd6df5fad2dee62208fe33e3a86fd50503ede3615dbcb61a027c530d6f06be9d.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: storage tank</c>tennis court</c>front loader bulldozer</c>unworking chimney</c>fishing vessel</c>a321</c>truck w box</c>construction site."
},
{
"from": "gpt",
"value": "<ref>storage tank</ref><box>... | images/train/ba/bae67983dfbb3f421b96dddf0524f474542d8d7b8ae06485e4ae7b3836939987.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "Power-Plant",
"density_definition": "image_content_level",
"geometry_mode": "point",
"ima... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: unworking condensing tower."
},
{
"from": "gpt",
"value": "<ref>unworking condensing tower</ref><box><677><918></box>"
}
] | images/train/3b/3b3e165b7f6ad7a5071d900d72d1b28613a0457127abaf697886fc64b0d54ef1.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "Power-Plant",
"density_definition": "image_content_level",
"geometry_mode": "point",
"ima... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: drill ship</c>airplane</c>truck w flatbed</c>small civilian aircraft</c>shipping container lot</c>small car</c>a321</c>tower</c>trailer</c>front loader bulldozer</c>storage tank</c>container group</c>other vehi... | images/train/c6/c6b3af848d1aaf213f227a8e81cb6a7541120ea4778f10e6086c8e42e970d20b.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: other ship</c>aquaculture farm</c>a220</c>dry cargo ship."
},
{
"from": "gpt",
"value": "<ref>other ship</ref><box><452><904></box><box><804><572></box><box><802><632></box><box><824><630></box><box... | images/train/27/278878955ef3e9ceeb39b1cb4573692a0f8ff15fd5966bf259a7ae03a3f6a9d8.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: container crane</c>roundabout</c>harbor</c>overpass</c>truck</c>trailer</c>shipping container</c>mobile crane</c>ground track field</c>ship</c>expressway toll station</c>bridge</c>swimming pool</c>airplane</c>o... | images/train/dc/dc2b91056043043924cf86a59871642832ac219c86cf8de3e6dcb7723e79b345.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: tennis court."
},
{
"from": "gpt",
"value": "<ref>tennis court</ref><box><496><398></box><box><609><382></box><box><719><368></box>"
}
] | images/train/33/334c546037f6c2900f0043fb7e7727ba8acfcc1ec752d4e326bb0b58cb577c3c.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: football field."
},
{
"from": "gpt",
"value": "<ref>football field</ref><box><461><551></box>"
}
] | images/train/39/399747acc969ffa5a8cfcb22cffa78d95cb58cff6848aef696956aa747d7db42.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: liquid cargo ship</c>unworking chimney."
},
{
"from": "gpt",
"value": "<ref>liquid cargo ship</ref><box><202><778></box><ref>unworking chimney</ref><box>None</box>"
}
] | images/train/96/96a642a197ebad691be4b346ba24fd84ff2f36004e63640bbf73f74e03e70da5.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: motorboat."
},
{
"from": "gpt",
"value": "<ref>motorboat</ref><box>None</box>"
}
] | images/train/cb/cb9cc748dd27f5d190481446d164f2cd4ee32f3a3997751e5a8b5a367d0a9f40.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: ground track field</c>unworking chimney</c>maritime vessel</c>straddle carrier."
},
{
"from": "gpt",
"value": "<ref>ground track field</ref><box>None</box><ref>unworking chimney</ref><box><837><103>... | images/train/93/9361ae1e1c0acbefffd0bdf8ef9617b4fad1f8f7d97a957ff13af316e8268c1a.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "Power-Plant",
"density_definition": "image_content_level",
"geometry_mode": "point",
"ima... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: mobile crane."
},
{
"from": "gpt",
"value": "<ref>mobile crane</ref><box>None</box>"
}
] | images/train/e3/e309342ea4c19c8fbe9d0ecc630968b75d38aae728cb07e5b5f802e435f63b5f.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: dump truck</c>sailboat</c>dry cargo ship</c>small car</c>boeing737</c>straddle carrier</c>building</c>wind turbine."
},
{
"from": "gpt",
"value": "<ref>dump truck</ref><box><816><602></box><ref>sail... | images/train/67/67f2921251daa8ec98662d686c8d54aff5eddd2a5b53342bb288c3d05c0b0e7a.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: ship</c>baseball diamond."
},
{
"from": "gpt",
"value": "<ref>ship</ref><box><240><292></box><ref>baseball diamond</ref><box>None</box>"
}
] | images/train/6c/6c547022a1fad112d36d683350d0b8ed7938c823e8e9201d35d02200863489c4.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: stadium</c>overpass</c>arj21</c>other ship</c>shed</c>expressway service area</c>engineering vehicle</c>cement mixer</c>truck w box</c>passenger car</c>baseball diamond</c>chimney</c>van</c>crane</c>tower crane... | images/train/2c/2c2944acec8264646b0d6e2f56069f3e30f93a4234aa8e41e4bebc94cc44a3c8.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: helicopter</c>a350</c>motorboat</c>large vehicle."
},
{
"from": "gpt",
"value": "<ref>helicopter</ref><box>None</box><ref>a350</ref><box>None</box><ref>motorboat</ref><box>None</box><ref>large vehic... | images/train/05/058ca588571848a683ab79aad93544b1e62416e6c2c275fcaccfd54965042b8e.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: small vehicle</c>swimming pool</c>helipad</c>trailer</c>liquid cargo ship</c>tower crane</c>other airplane</c>large vehicle."
},
{
"from": "gpt",
"value": "<ref>small vehicle</ref><box>None</box><re... | images/train/95/95874da6dcf97470ffcb7139125c544332af98f64c091391dc5f524173b93278.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: swimming pool</c>container</c>vehicle</c>container crane</c>tank car</c>unworking chimney</c>construction site</c>tennis court."
},
{
"from": "gpt",
"value": "<ref>swimming pool</ref><box>None</box>... | images/train/f1/f1b6ecbadfff54f9e72d4ce64f61b057fe004bde7977df6e9f131a9ebed2e598.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: cement mixer</c>aircraft hangar</c>small aircraft</c>large military aircraft</c>a220</c>damaged building</c>unworking chimney</c>dump truck</c>storage tank</c>shipping container</c>oil tanker</c>harbor</c>front... | images/train/52/5242ce635184285be9fbd66bf1beebc365d4199bf572387ebff19cb8bc697aff.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: chimney</c>shed</c>large vehicle</c>other airplane."
},
{
"from": "gpt",
"value": "<ref>chimney</ref><box>None</box><ref>shed</ref><box>None</box><ref>large vehicle</ref><box>None</box><ref>other ai... | images/train/b0/b0d94ac89562b5824b41c28b016ede3e33a897e90172a2ef51d505de8b8f2381.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: small vehicle."
},
{
"from": "gpt",
"value": "<ref>small vehicle</ref><box><248><928></box>"
}
] | images/train/cf/cf75b05ff67917ede0f8c44b5cc173bfdadd117776647d29f0b56775ef8c49a5.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: passenger ship</c>small car</c>plane</c>unworking chimney</c>van</c>c919</c>aircraft</c>large military aircraft."
},
{
"from": "gpt",
"value": "<ref>passenger ship</ref><box>None</box><ref>small car... | images/train/d0/d01600380d7a317929e5ddb04d7c4bc666f46e8c37e7b91bfc509c9dd209bc21.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: warship</c>ship</c>harbor</c>playground."
},
{
"from": "gpt",
"value": "<ref>warship</ref><box>None</box><ref>ship</ref><box>None</box><ref>harbor</ref><box><206><814></box><box><396><101></box><box... | images/train/00/0012f226cbab28644c97c6fbd3e15411a38d2955b00ef2f795be2b0f2d238bbf.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTA-v1.5_la1024_nopad",
"density_definition": "image_content_level",
"geometry_mode": "poi... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: ground grader</c>pickup truck</c>utility truck</c>aircraft</c>ship</c>stadium</c>harbor</c>a220."
},
{
"from": "gpt",
"value": "<ref>ground grader</ref><box>None</box><ref>pickup truck</ref><box>Non... | images/train/02/022c094d827f8eeb10816973a3871d7a1bfd860c5dc5ec0dd75f5970794113f8.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTA-v1.5_la1024_nopad",
"density_definition": "image_content_level",
"geometry_mode": "poi... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: swimming pool."
},
{
"from": "gpt",
"value": "<ref>swimming pool</ref><box>None</box>"
}
] | images/train/c5/c5c56afae7d07f024a6658c8d141bcefcdc00a42010f13a0495f4de13f599e4b.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: motorboat</c>aircraft hangar."
},
{
"from": "gpt",
"value": "<ref>motorboat</ref><box>None</box><ref>aircraft hangar</ref><box><47><252></box><box><100><946></box><box><149><726></box><box><142><676... | images/train/60/6099e3247dffbbfc8ca8f0cfc74b532b7ad6ff8730591d6a54a14786d8347aeb.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: fighter aircraft</c>windmill</c>harbor</c>roundabout</c>haul truck</c>barge</c>baseball field</c>train station."
},
{
"from": "gpt",
"value": "<ref>fighter aircraft</ref><box>None</box><ref>windmill... | images/train/0b/0baaa19c680df047fae3386d48dc5a384f1b0f8be3c34877ac809a4d524f444e.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: intersection</c>motorboat</c>a321</c>wind turbine."
},
{
"from": "gpt",
"value": "<ref>intersection</ref><box><724><754></box><ref>motorboat</ref><box>None</box><ref>a321</ref><box>None</box><ref>wi... | images/train/af/af21715f6eaa1e130a6efa3724b6d111324fd918722b512c3fa5a7497da22392.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: oil tank</c>working condensing tower</c>overpass</c>small vehicle</c>swimming pool</c>reach stacker</c>container crane</c>basketball court."
},
{
"from": "gpt",
"value": "<ref>oil tank</ref><box>Non... | images/train/b0/b0a500f193f5adbd3a8581e00eef0eee9562d1b49cba300c59a805128e80a487.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: van."
},
{
"from": "gpt",
"value": "<ref>van</ref><box><160><206></box><box><868><827></box><box><942><878></box><box><955><942></box>"
}
] | images/train/cb/cbad6e85d26cc7c1bac809e3b037f8139042ac56068e7a41aa291313fe045a27.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: truck w liquid</c>dump truck</c>excavator</c>passenger ship</c>truck w flatbed</c>motorboat</c>aircraft</c>baseball field."
},
{
"from": "gpt",
"value": "<ref>truck w liquid</ref><box>None</box><ref... | images/train/37/3717d0030ea78642c57416a83351fb837c6d3404cb3dc92d17a17efd189ab0a4.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: tennis court</c>plane</c>sports field</c>a220</c>a321</c>dam</c>passenger ship</c>aquaculture farm</c>boeing787</c>chimney</c>reach stacker</c>boeing737</c>large military aircraft</c>excavator</c>stadium</c>sma... | images/train/34/34c7c992b6914f374fb13ff74c5af44dd800906d2a1bd6ce6ea7485e40a80c3f.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: pylon</c>van</c>wind turbine</c>small civilian aircraft</c>bridge</c>large civilian aircraft</c>boeing777</c>a350</c>dry cargo ship</c>container group</c>tennis court</c>windmill</c>expressway toll station</c>c... | images/train/8b/8bf707a416886b438e8c3869771ed72da869583738526252e5546d2ac21abec2.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: vehicle lot."
},
{
"from": "gpt",
"value": "<ref>vehicle lot</ref><box>None</box>"
}
] | images/train/c8/c88c6c059ab38088382e34a4b4fc450d2eadb369e85f3a68fa79b2ae522a94ec.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: boeing787</c>vehicle lot</c>football field</c>crane truck</c>small car</c>tower</c>swimming pool</c>storage tank."
},
{
"from": "gpt",
"value": "<ref>boeing787</ref><box>None</box><ref>vehicle lot</... | images/train/18/1855c6a577280faf1d06cdcda1561320f950c05880775bb3a38345574f365683.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: aircraft hangar."
},
{
"from": "gpt",
"value": "<ref>aircraft hangar</ref><box><806><856></box>"
}
] | images/train/55/556052e4ea03bf9233000e8933f60eeb61e7ea7a6461ca42857e1d65da579906.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: yacht</c>a220</c>construction site</c>shipping container</c>a330</c>a350</c>boeing737</c>hut tent</c>oil tank</c>football field</c>shipping container lot</c>airplane</c>passenger ship</c>airport</c>small car</c... | images/train/32/32060896477b84131c097bc6333eece215eb54c0bcae0847ffcb02c0d1570788.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: hut tent</c>sailboat</c>overpass</c>arj21</c>shed</c>train station</c>small vehicle</c>bridge."
},
{
"from": "gpt",
"value": "<ref>hut tent</ref><box>None</box><ref>sailboat</ref><box>None</box><ref... | images/train/8b/8b65b6cd3ca18080e7c4172a74fa149dfc25851ffd51e465fa0279c754b65195.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: haul truck</c>dam</c>small civilian aircraft</c>basketball court."
},
{
"from": "gpt",
"value": "<ref>haul truck</ref><box>None</box><ref>dam</ref><box>None</box><ref>small civilian aircraft</ref><b... | images/train/d4/d4da359bf9a16e86e90316d274249ce3784b822f4a7b692ecb3216aacdac310d.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: mobile crane</c>unworking condensing tower</c>cargo plane</c>other airplane</c>railway vehicle</c>plane</c>container ship</c>boeing737</c>tennis court</c>ground grader</c>excavator</c>fighter aircraft</c>footba... | images/train/2b/2b1ecd646c969ff1aab06676f943eb359e8dd499cd61d8c6fde841a9ef29804f.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "Power-Plant",
"density_definition": "image_content_level",
"geometry_mode": "point",
"ima... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: shed</c>windmill</c>other vehicle</c>baseball diamond</c>other airplane</c>tractor</c>aquaculture farm</c>helipad."
},
{
"from": "gpt",
"value": "<ref>shed</ref><box>None</box><ref>windmill</ref><bo... | images/train/25/25bff285d58e7ad6853bd7d12e8d2036cb0320abc1941343a2125e5b79210fe3.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "SODA-A_la1024_nopad",
"density_definition": "image_content_level",
"geometry_mode": "point"... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: cargo truck</c>van</c>small car</c>container crane."
},
{
"from": "gpt",
"value": "<ref>cargo truck</ref><box><148><358></box><ref>van</ref><box><14><700></box><box><110><928></box><ref>small car</r... | images/train/a7/a74c0f7b65c3e8d331fac13368b03931b4499332c7f1ddf47727db8d669ec0bd.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: reach stacker</c>a220</c>truck</c>swimming pool</c>storage tank</c>locomotive</c>crane truck</c>playground."
},
{
"from": "gpt",
"value": "<ref>reach stacker</ref><box>None</box><ref>a220</ref><box>... | images/train/53/534af48cec018cc3ab00c0a64dfb6444b83698a8e6c73574e656554e66d9ffaf.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: engineering vehicle."
},
{
"from": "gpt",
"value": "<ref>engineering vehicle</ref><box>None</box>"
}
] | images/train/84/845d82574bd252b6479615d173ee5f01aa2d5c34cce66158cda891b042f0c30d.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTA-v1.5_la1024_nopad",
"density_definition": "image_content_level",
"geometry_mode": "poi... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: tugboat</c>sports field</c>railway vehicle</c>tower</c>front loader bulldozer</c>passenger vehicle</c>bus</c>boeing777</c>dump truck</c>bridge</c>haul truck</c>truck</c>passenger car</c>crane</c>unworking chimn... | images/train/75/75853113c1476c031567d178c9fa5e4efdbf3eec6fde758e6f0500d0195c466d.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: wind turbine</c>c919</c>roundabout</c>working condensing tower</c>container ship</c>boeing777</c>swimming pool</c>small aircraft</c>baseball field</c>front loader bulldozer</c>yacht</c>maritime vessel</c>contai... | images/train/55/55794d91d943c942be74b99ccb04f6b36229856951c6290a1d2b8e3735e92656.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: shed</c>truck w box</c>haul truck</c>other airplane</c>chimney</c>expressway toll station</c>flat car</c>truck tractor."
},
{
"from": "gpt",
"value": "<ref>shed</ref><box>None</box><ref>truck w box<... | images/train/cf/cfbf3e7f70e76f316632f854b13be4c2b5b405827d4ffc1513eec1fc275bb6ab.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: wind turbine."
},
{
"from": "gpt",
"value": "<ref>wind turbine</ref><box>None</box>"
}
] | images/train/5c/5c176c75f0f1c4eca775a18563baef6bf488cfea65b15fd53083b47edb3f76a6.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: small vehicle."
},
{
"from": "gpt",
"value": "<ref>small vehicle</ref><box><500><974></box>"
}
] | images/train/db/db4b52f549e97c454963abf9077958bd3819ebfb9122d23a3c4b6dc0dc141d5f.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTA-v1.5_la1024_nopad",
"density_definition": "image_content_level",
"geometry_mode": "poi... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: expressway toll station</c>unworking condensing tower</c>pylon</c>utility truck</c>container ship</c>shipping container</c>dam</c>truck w box</c>truck w liquid</c>football field</c>golf field</c>oil tank</c>sto... | images/train/b6/b647ce84325f8c12f5a9c26860df41247141ee5bf8e809c6552b4c8a7f1020fe.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DIOR",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_cont... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: unworking chimney</c>bus</c>airplane</c>roundabout."
},
{
"from": "gpt",
"value": "<ref>unworking chimney</ref><box>None</box><ref>bus</ref><box><47><582></box><box><82><534></box><box><90><532></bo... | images/train/e5/e5fd7c6ec17287ebc1319f0842e66685164068a4abeafd9ec562c893a46675da.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: maritime vessel</c>storage tank</c>truck tractor</c>crane truck</c>cargo car</c>chimney</c>container crane</c>a350."
},
{
"from": "gpt",
"value": "<ref>maritime vessel</ref><box>None</box><ref>stora... | images/train/eb/ebd8be9a5133c50b884989346165d802d5a20f0f1cad65b2afadae2022a44fca.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: container</c>scraper tractor</c>ground track field</c>sailboat."
},
{
"from": "gpt",
"value": "<ref>container</ref><box>None</box><ref>scraper tractor</ref><box>None</box><ref>ground track field</re... | images/train/69/69d0beabf9c5e1485c6d9021846a6249f83f8efa3d68b58c3b92ce959a8a6988.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DIOR",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_cont... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: harbor</c>ship</c>small vehicle</c>front loader bulldozer."
},
{
"from": "gpt",
"value": "<ref>harbor</ref><box><180><510></box><box><774><424></box><box><884><437></box><box><964><430></box><ref>sh... | images/train/a1/a1f1146b1574f1ff01711876da7bfd7fafc8d5b40a1a71293f7a3ba44e662a9d.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: large military aircraft</c>small vehicle</c>chimney</c>oil tanker."
},
{
"from": "gpt",
"value": "<ref>large military aircraft</ref><box>None</box><ref>small vehicle</ref><box><516><875></box><box><... | images/train/29/29e94b79a4a08d4c31e0901d841af3996f5da8c0fb3ed5c644a80fcf4e49eda2.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: hut tent</c>unworking condensing tower</c>ferry</c>working condensing tower</c>arj21</c>tower crane</c>other ship</c>aquaculture farm</c>yacht</c>roundabout</c>bridge</c>oil tanker</c>aircraft hangar</c>overpas... | images/train/71/7195042b8ccec5c13b6d8abadbdbbd421a3325886f52db55525f6da436bea4be.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: small vehicle."
},
{
"from": "gpt",
"value": "<ref>small vehicle</ref><box><330><610></box>"
}
] | images/train/c4/c4956969c2c576595aca042ecc3b4a80634ea3c73e5024b0954e7d6b18403b0b.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: tractor</c>a220</c>passenger car</c>expressway toll station."
},
{
"from": "gpt",
"value": "<ref>tractor</ref><box>None</box><ref>a220</ref><box><972><257></box><ref>passenger car</ref><box>None</bo... | images/train/61/61b13954a9e2fa6fa341f3dcc8d59f40c89d53daf5276149808a3bbb66006907.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: aquaculture farm</c>shipping container</c>arj21</c>plane</c>mobile crane</c>container group</c>bridge</c>boeing787."
},
{
"from": "gpt",
"value": "<ref>aquaculture farm</ref><box>None</box><ref>ship... | images/train/10/1072d1d35e4667018927bbe4586c6d1250e6fcbc3a6f55d8f8a7c383be19d74a.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTA-v1.5_la1024_nopad",
"density_definition": "image_content_level",
"geometry_mode": "poi... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: other vehicle</c>storage tank</c>truck w box</c>passenger car</c>aquaculture farm</c>train</c>yacht</c>crane</c>aircraft</c>truck w liquid</c>basketball court</c>golf field</c>stadium</c>container</c>working co... | images/train/97/97eb46c49ebcad76cfed73da01fd1f6f9c8ec2511e54cb5b1be485cba17e8cf0.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "SODA-A_la1024_nopad",
"density_definition": "image_content_level",
"geometry_mode": "point"... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: small vehicle</c>ground track field</c>container crane</c>other ship</c>expressway service area</c>plane</c>shed</c>straddle carrier</c>container ship</c>tower</c>swimming pool</c>train station</c>pylon</c>chim... | images/train/0b/0b2f45adbc342e0df7a31f8a795dd42e5e2d74c66dd29840e285c968ec30de8b.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: shipping container lot</c>ground track field</c>ship</c>reach stacker."
},
{
"from": "gpt",
"value": "<ref>shipping container lot</ref><box>None</box><ref>ground track field</ref><box>None</box><ref... | images/train/98/987e3c931cc7bbf59b306d8554a0e6718b59d7de09b061a70fd517ba0566bd2b.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: drill ship</c>container group</c>helipad</c>truck w box</c>bus</c>aircraft hangar</c>ship</c>damaged building."
},
{
"from": "gpt",
"value": "<ref>drill ship</ref><box>None</box><ref>container group... | images/train/d5/d5b6b5c4f2e76cd74db0d7aef4e27432384d47ce10749b788fd4f0d9301b6663.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: small car</c>maritime vessel."
},
{
"from": "gpt",
"value": "<ref>small car</ref><box><388><239></box><ref>maritime vessel</ref><box>None</box>"
}
] | images/train/42/42bcce1eb8caf26f5ba3f900cd2cbd977941912b9d701de92a0e772dc073f544.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: hut tent</c>small vehicle</c>small civilian aircraft</c>tower crane</c>aircraft</c>small aircraft</c>intersection</c>expressway toll station."
},
{
"from": "gpt",
"value": "<ref>hut tent</ref><box>N... | images/train/2f/2ff1b1b7b07bd0f633267983c749115c287a63b92497f2a986fc29f100118f6e.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: cargo plane</c>small vehicle."
},
{
"from": "gpt",
"value": "<ref>cargo plane</ref><box>None</box><ref>small vehicle</ref><box><184><118></box><box><224><128></box><box><255><190></box><box><496><97... | images/train/fc/fc8a2ec15a4e089f8ffd8fc7d05e86940cde53957f4279a49398a69b08cce4b9.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: playground</c>front loader bulldozer</c>expressway toll station</c>shipping container lot</c>bus</c>ground grader</c>hut tent</c>dry cargo ship."
},
{
"from": "gpt",
"value": "<ref>playground</ref><... | images/train/12/124e3eae8052b96bd3666d583ceff1128490cd70ed2eb676a34bf159343c86b7.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: small vehicle."
},
{
"from": "gpt",
"value": "<ref>small vehicle</ref><box><92><900></box><box><388><940></box><box><534><576></box><box><955><800></box>"
}
] | images/train/69/69df1910dc0abbf01518d0843789d260c5be1bc12b8645118b9c8b80b7a91ffd.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: motorboat</c>dry cargo ship."
},
{
"from": "gpt",
"value": "<ref>motorboat</ref><box><969><348></box><ref>dry cargo ship</ref><box>None</box>"
}
] | images/train/c5/c5451c62d1fe4dcd2380ef85ac5f5d3ddfab9a7bc4eeaa2d81b5c5117b315fa6.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: airplane</c>plane</c>roundabout</c>fishing boat</c>intersection</c>container ship</c>a321</c>container group</c>expressway service area</c>fighter aircraft</c>ground grader</c>helicopter</c>passenger ship</c>fo... | images/train/19/19a511a0420e89c5f8e1d47e011d52fa49c6431adc0e8920131f550f932cada9.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: fighter aircraft</c>other ship</c>motorboat</c>harbor."
},
{
"from": "gpt",
"value": "<ref>fighter aircraft</ref><box>None</box><ref>other ship</ref><box><514><672></box><ref>motorboat</ref><box><10... | images/train/c7/c72635adfd64b5f9d6f64080aebf54097e299314707a8da5d8fc7ff33604b589.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: harbor</c>playground</c>a350</c>large vehicle</c>boeing737</c>swimming pool</c>aircraft</c>a330</c>ground grader</c>shipping container lot</c>golf field</c>oil tank</c>pylon</c>sports field</c>tank car</c>crane... | images/train/27/27f87e1afe6d33f90a0418c60ed182c9c170409e888b074d89c5dd10b56b5189.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "SODA-A_la1024_nopad",
"density_definition": "image_content_level",
"geometry_mode": "point"... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: container</c>locomotive</c>vehicle</c>baseball field."
},
{
"from": "gpt",
"value": "<ref>container</ref><box>None</box><ref>locomotive</ref><box>None</box><ref>vehicle</ref><box>None</box><ref>base... | images/train/89/89317801d28c1f04ebbe8dfe936886d89d6de93a706450160f6e011d2c3753dd.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DIOR",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_cont... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: train</c>roundabout</c>intersection</c>cargo car</c>airplane</c>truck w flatbed</c>motorboat</c>expressway service area</c>ground track field</c>fishing boat</c>crane</c>dam</c>unworking condensing tower</c>str... | images/train/b3/b35a0066ddc96ee5844e09d9a628e87a69022537fe15c2d7f5cc98f70c7e3329.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: locomotive</c>arj21</c>unworking chimney</c>ground track field</c>bus</c>shipping container</c>oil tank</c>boeing777</c>engineering ship</c>airport</c>liquid cargo ship</c>harbor</c>tower</c>expressway toll sta... | images/train/c4/c47f606200fa0ca98b372e6859e6d19d9a33839b4e82e56b8d44d98d371867d5.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: van."
},
{
"from": "gpt",
"value": "<ref>van</ref><box><55><410></box><box><100><932></box><box><362><942></box>"
}
] | images/train/d3/d38cfbf63e7a3ac06796dc538c0cc382ec2cb570c060f20fc7cec1b5cb08ef27.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: vehicle lot</c>tennis court."
},
{
"from": "gpt",
"value": "<ref>vehicle lot</ref><box>None</box><ref>tennis court</ref><box><67><195></box><box><156><206></box><box><220><432></box><box><245><218><... | images/train/2b/2bd2b3f09cfc8f07123989cc167445136b700c262d0ff566994f6bde20b2cba9.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DIOR",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_cont... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: soccer ball field</c>shed</c>swimming pool</c>tennis court</c>barge</c>van</c>locomotive</c>utility truck</c>warship</c>train station</c>cargo car</c>truck w liquid</c>working condensing tower</c>wind turbine</... | images/train/23/23437346288efa810707181d19bbc1af8245597f8b55643fb03de56ae55a32b9.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: ship</c>truck."
},
{
"from": "gpt",
"value": "<ref>ship</ref><box><236><224></box><box><526><416></box><box><609><494></box><box><708><485></box><box><883><616></box><ref>truck</ref><box>None</box>"... | images/train/7d/7de1b14a57383f67102efce5061543710edb079297276f2a34f4085609d33b4b.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTA-v1.5_la1024_nopad",
"density_definition": "image_content_level",
"geometry_mode": "poi... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: cargo plane</c>c919</c>a350</c>ground track field</c>shipping container lot</c>a330</c>playground</c>aquaculture farm</c>straddle carrier</c>cement mixer</c>building</c>liquid cargo ship</c>windmill</c>boeing74... | images/train/5a/5a5c8bb70e3c9432ccd2e28c49ddd811cc97876bfed268cbb7d43bcbfdc22794.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: crane."
},
{
"from": "gpt",
"value": "<ref>crane</ref><box>None</box>"
}
] | images/train/32/3204d52b6f23da1165cfdda1fd820b545dbf221513f939763ac2ef5e48885081.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: passenger ship</c>reach stacker</c>fishing boat</c>working condensing tower</c>large civilian aircraft</c>aircraft hangar</c>train</c>small car."
},
{
"from": "gpt",
"value": "<ref>passenger ship</r... | images/train/d5/d59aa94b8372595f675c8e1c0cd3402315556913e5ece7f5b4a355da3c28522a.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: reach stacker</c>truck w box</c>other airplane</c>bus</c>golf field</c>wind turbine</c>expressway service area</c>truck tractor</c>truck w liquid</c>shipping container lot</c>pylon</c>passenger vehicle</c>crane... | images/train/cd/cd697ac81ad3c8dbd333f7669f3515904bdbb7f11f771ae1e647c142bb88ce98.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: small vehicle."
},
{
"from": "gpt",
"value": "<ref>small vehicle</ref><box><666><36></box>"
}
] | images/train/97/970df73ce3d000219ff5359482c1174125a63edbfce661403d605caeb2cdfca0.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTAv2",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: arj21</c>working condensing tower</c>expressway service area</c>helipad</c>engineering ship</c>truck</c>truck w box</c>tank car</c>truck w flatbed</c>passenger vehicle</c>ferry</c>maritime vessel</c>basketball ... | images/train/25/2518e4a7d3dae24ca44cdb3823cd9d30ac9e6de00b2ff5560503d3aa1149faea.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DIOR",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_cont... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: other airplane</c>boeing737."
},
{
"from": "gpt",
"value": "<ref>other airplane</ref><box>None</box><ref>boeing737</ref><box><476><60></box>"
}
] | images/train/c9/c99f7fa387dd32bb9931d9bb4facf5984661e8f6177fd726149e5e0aacfee691.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: boeing777</c>other ship</c>playground</c>dry cargo ship."
},
{
"from": "gpt",
"value": "<ref>boeing777</ref><box>None</box><ref>other ship</ref><box><704><118></box><ref>playground</ref><box>None</b... | images/train/7c/7c6f14fcc365f73fcdf22e5b5680539f6792e7fff2be618589b571a75bd285f6.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: facility</c>tugboat</c>baseball diamond</c>airplane</c>shipping container</c>hut tent</c>maritime vessel</c>boeing777</c>a321</c>shipping container lot</c>container</c>shed</c>drill ship</c>pylon</c>bridge</c>s... | images/train/fc/fc5f39b0947f2a5636b9e0351e7c078b97c0b76dcef689bca7a034a34cc2172c.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "KFGOD",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: aircraft hangar</c>building</c>pickup truck</c>boeing777</c>truck w box</c>passenger ship</c>football field</c>flat car."
},
{
"from": "gpt",
"value": "<ref>aircraft hangar</ref><box><4><550></box><... | images/train/57/574dd836441adc47499f79628db5b9edbe128d93817116839e730361e7da6d06.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: damaged building."
},
{
"from": "gpt",
"value": "<ref>damaged building</ref><box>None</box>"
}
] | images/train/4a/4ae613d08938b7fca3ff2b95f84b738d8c2c566b145d668053c5a8d0c89c76b1.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "KFGOD",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: wind turbine."
},
{
"from": "gpt",
"value": "<ref>wind turbine</ref><box>None</box>"
}
] | images/train/38/38eac429ad9580f06a9734e98c4f08479cc8436ee0c003b2e5c9bce002ccacb2.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: van</c>small civilian aircraft</c>small car</c>plane."
},
{
"from": "gpt",
"value": "<ref>van</ref><box><34><988></box><box><60><989></box><box><542><872></box><ref>small civilian aircraft</ref><box... | images/train/50/50c827843d144ba2bb4430c381c07fce111f40840557dc5e182204f73ee837fb.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: flat car."
},
{
"from": "gpt",
"value": "<ref>flat car</ref><box>None</box>"
}
] | images/train/57/57082ed9cbfc7513d62f63d449366c14ecd2f707997ca30a6f861a189bc0f539.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "KFGOD",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: sailboat."
},
{
"from": "gpt",
"value": "<ref>sailboat</ref><box>None</box>"
}
] | images/train/31/31793ed556e4d7b474e03586201fd21fec970f391e8cbd4549307f2dd4a24241.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DIOR",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_cont... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: other ship."
},
{
"from": "gpt",
"value": "<ref>other ship</ref><box><390><634></box>"
}
] | images/train/b9/b9070cf07efd7095dcd59cdb6e8fc507b5fa2e6834b4fefe68c3538b690094c0.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: bridge</c>warship."
},
{
"from": "gpt",
"value": "<ref>bridge</ref><box><896><76></box><box><936><156></box><box><940><52></box><box><968><136></box><ref>warship</ref><box>None</box>"
}
] | images/train/94/94b766020bb494b7eab722d521ad3a873024fd421ea4f350e72542d9d4d2dbf1.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "DOTA-v1.5_la1024_nopad",
"density_definition": "image_content_level",
"geometry_mode": "poi... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: aircraft hangar</c>chimney</c>boeing777</c>playground."
},
{
"from": "gpt",
"value": "<ref>aircraft hangar</ref><box><123><63></box><box><558><796></box><box><834><914></box><ref>chimney</ref><box>N... | images/train/15/15bd6e8de73b01619e80964742365195695a8903bce5a9c225b3479cb7b6ea0c.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: wind turbine</c>crane</c>oil tanker</c>shipping container lot</c>bridge</c>baseball diamond</c>airport</c>arj21</c>damaged building</c>working chimney</c>small car</c>van</c>ground grader</c>plane</c>yacht</c>r... | images/train/0f/0f85fc6d53e2c4e9b26bb32f2127a29e5a533c824a514be8970c25f83b59b05d.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: pylon</c>aircraft hangar</c>helicopter</c>sports field</c>a330</c>large military aircraft</c>bus</c>construction site."
},
{
"from": "gpt",
"value": "<ref>pylon</ref><box>None</box><ref>aircraft han... | images/train/34/344386013d8863114640e665542918f8f725590d01eb57ad7d52947ee8ac7595.jpg | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "xView",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_con... |
[
{
"from": "human",
"value": "<image>\nPoint to all instances that match the following categories: bridge."
},
{
"from": "gpt",
"value": "<ref>bridge</ref><box>None</box>"
}
] | images/train/be/be5b129383d6bf92b787c152fe1a233302b825bcf6eda70175982b7839837af4.png | {
"answer_format": "pixel_pivr_grouped_ref_points_or_explicit_None_v1",
"coordinate_space": "normalized_0_1000",
"coverage_seed": 152,
"coverage_stage": "stage1_coarse",
"curriculum_subset": "coarse",
"dataset": "FAIR1M",
"density_definition": "image_content_level",
"geometry_mode": "point",
"image_co... |
End of preview.
Pixel-PIVR 144-to-384 Full-Scale Dataset
This is the versioned pixel-pivr-hf-hbb-magnified-v2 package. It is the real pixel re-encoding
variant, not the older cached pre-projector ROI variant.
Round 1 encodes the global image and predicts target-complete point addresses.
Round 2 first encodes the same global image plus a deterministic 144 x 144
source-pixel crop resized to 384 x 384 with Lanczos, then predicts exactly one box
or <box>None</box>. There are 2,171,892 local-gate rows. A local None,
invalid box, or crop-edge box triggers one of 320,576 paired global
fallback rows. These include both large positive targets and negative addresses,
so inference never selects a route using ground truth. No target or box is clipped.
LocateAnything's unchanged image processor subsequently aligns 384 x 384 to 392 x 392 (28 x 28 MoonViT patches, or 14 x 14 = 196 projected visual tokens).
| Split | Records | Unique images | Image bytes |
|---|---|---|---|
| Stage 1 coarse | 460,263 | shared train pool | - |
| Stage 2 dense + replay | 2,100,576 | shared train pool | - |
| Validation | 105,767 | 1,000 | 0.54 GiB |
| Checkpoint-selection monitor | 2,141 | same validation pool | - |
| Test | benchmark protocols | 16,712 | 7.22 GiB |
The train, validation, and test image SHA-256 sets have zero overlap. Stage 1 and
Stage 2 may intentionally reuse training images. Use the recipes under recipes/;
do not construct splits from directory names.
Stage 2 contains 1,960,076 dense optimizer records and 140,500 replay optimizer records (6.69% replay after point-to-box expansion). Before expansion, its Round-1 source-query schedule contains 39,477 dense and 11,204 replay records (22.11% replay). These percentages describe different units and must not be interchanged.
Integrity
SHA256SUMS covers every annotation, recipe, manifest, documentation file, and
every image. IMAGE_INVENTORY.jsonl provides a machine-readable image inventory.
The training repository preflight additionally verifies this schema, crop contract,
record counts, GPU topology, sequence budget, and the pinned Eagle compatibility
patch before training can start.
Download
hf download shubhampatle/Pixel-PIVR-Magnified-v2 --repo-type dataset --local-dir Pixel-PIVR-Magnified-v2
The full operator guide is in the Pixel-PIVR code repository under
docs/A100_8GPU_FULL_SCALE_RUNBOOK.md.
License note
This is a derived research compilation. Every source dataset retains its own terms. Review the source licenses before redistribution or commercial use. No model weights are included.
Archive transport
Images are transported in deterministic uncompressed tar shards so the Hub
repository remains well below its recommended 100,000-file ceiling. The JSONL
paths still point to images/.... Run the code repository bootstrap command;
it validates every archive, extracts images atomically, and verifies every image
SHA-256 before training is unlocked. Do not train directly from the tar files.
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