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The dataset generation failed
Error code: DatasetGenerationError
Exception: CastError
Message: Couldn't cast
video: string
video_id: string
height: int64
width: int64
expression: string
type_id: int64
exp_id: string
masks: list<item: string>
child 0, item: string
sampling_type: string
target_frames: int64
filename: string
conversations: list<item: struct<from: string, value: string>>
child 0, item: struct<from: string, value: string>
child 0, from: string
child 1, value: string
frame_idx: list<item: int64>
child 0, item: int64
to
{'video': Value('string'), 'conversations': List({'from': Value('string'), 'value': Value('string')}), 'frame_idx': List(Value('int64')), 'masks': List(Json(decode=True)), 'filename': Value('string'), 'video_id': Value('string'), 'target_frames': Value('int64'), 'sampling_type': Value('string')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1872, in _prepare_split_single
for key, table in generator:
^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 265, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/json/json.py", line 120, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_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
video: string
video_id: string
height: int64
width: int64
expression: string
type_id: int64
exp_id: string
masks: list<item: string>
child 0, item: string
sampling_type: string
target_frames: int64
filename: string
conversations: list<item: struct<from: string, value: string>>
child 0, item: struct<from: string, value: string>
child 0, from: string
child 1, value: string
frame_idx: list<item: int64>
child 0, item: int64
to
{'video': Value('string'), 'conversations': List({'from': Value('string'), 'value': Value('string')}), 'frame_idx': List(Value('int64')), 'masks': List(Json(decode=True)), 'filename': Value('string'), 'video_id': Value('string'), 'target_frames': Value('int64'), 'sampling_type': Value('string')}
because column names don't match
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 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 1739, 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 1922, 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.
video string | conversations list | frame_idx list | masks list | filename string | video_id string | target_frames int64 | sampling_type string |
|---|---|---|---|---|---|---|---|
EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment the object with the following attributes: rectangular shape, metallic exterior, black front door, located under a cabinet, contains a wrapped food item inside in the video?"
},
{
"from": "gpt",
"value": "There isn't a the object with the following att... | [
0,
37,
75,
112,
150,
187,
225,
262
] | [
"{\"0\":null,\"37\":null,\"75\":null,\"112\":null,\"150\":null,\"187\":null,\"225\":null,\"262\":null}",
"{\"0\":null,\"37\":null,\"75\":null,\"112\":null,\"150\":null,\"187\":null,\"225\":null,\"262\":null}",
"{\"0\":null,\"37\":{\"size\":[1440,1920],\"counts\":\"dl1W1i[1000N2M4L4M2M4M3M3M2N2N3M2N3M2N3M3N0O1O2... | 622c1b29-76c6-4845-95df-7e54792687d4_8f_start_000000.json | 622c1b29-76c6-4845-95df-7e54792687d4 | 8 | start |
EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment the pair of wooden chopsticks, light brown in color, initially resting on the stovetop near the frying pan and later seen being held near the sink while handling food in the video?"
},
{
"from": "gpt",
"value": "It is [SEG]."
},
{
"from": "hum... | [
18,
55,
93,
130,
168,
205,
243,
280
] | [
"{\"18\":null,\"55\":null,\"93\":null,\"130\":null,\"168\":null,\"205\":null,\"243\":null,\"280\":{\"size\":[1440,1920],\"counts\":\"UhcS27h\\\\14M1O1O2N100O2N100O100O100O100O101O0O100O100O1O100O01000O10000O10O10O101O0000O0100O1000000O0100000O100O01000O01000O10000O100000O0100000000O10000O100O10000O10O10O100O100O2OO... | 622c1b29-76c6-4845-95df-7e54792687d4_8f_middle_000001.json | 622c1b29-76c6-4845-95df-7e54792687d4 | 8 | middle |
EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment the silver rectangular microwave located on the left side of the kitchen counter, positioned near a coffee maker, paper towels, and a roll of plastic wrap, with its door opened in some frames and containing a wrapped food item in the video?"
},
{
"from": ... | [
36,
73,
111,
148,
186,
223,
261,
298
] | [
"{\"36\":null,\"73\":null,\"111\":null,\"148\":null,\"186\":null,\"223\":null,\"261\":null,\"298\":null}",
"{\"36\":null,\"73\":null,\"111\":null,\"148\":null,\"186\":{\"size\":[1440,1920],\"counts\":\"W^\\\\[28h\\\\11O1O1O2N10000001OO2O000O1O100000000O2O000O101O0O2O0O2O00000O100000001N1001O0000O1000001O000000001... | 622c1b29-76c6-4845-95df-7e54792687d4_8f_end_000002.json | 622c1b29-76c6-4845-95df-7e54792687d4 | 8 | end |
EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment wooden chopsticks on the stovetop and sink in the video?"
},
{
"from": "gpt",
"value": "It is [SEG]."
},
{
"from": "human",
"value": "Can you segment kitchen knife with the following attributes: metallic blade with a dark handle, located o... | [
0,
18,
37,
56,
75,
93,
112,
131,
150,
168,
187,
206,
225,
243,
262,
281
] | [
"{\"0\":null,\"18\":null,\"37\":null,\"56\":null,\"75\":null,\"93\":null,\"112\":null,\"131\":null,\"150\":null,\"168\":null,\"187\":{\"size\":[1440,1920],\"counts\":\"RU_W23l\\\\14M1O1O1O1O1O1O1O001O10O01O0010O0100O1O01000O010O10O0100O0100O01000O010O010O0100O010O00100O010O1O010000O100O010O010O10O10O0100O00100O0100... | 622c1b29-76c6-4845-95df-7e54792687d4_16f_start_000003.json | 622c1b29-76c6-4845-95df-7e54792687d4 | 16 | start |
EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment the object with the following attributes: metallic blade with a dark handle, located on a countertop near food items, medium-sized compared to surrounding objects in the video?"
},
{
"from": "gpt",
"value": "It is [SEG]."
},
{
"from": "human",... | [
9,
27,
46,
65,
84,
102,
121,
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159,
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196,
215,
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EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment the object with the following attributes: metallic blade with a dark handle, located on a countertop near food items, medium-sized compared to surrounding objects in the video?"
},
{
"from": "gpt",
"value": "It is [SEG]."
},
{
"from": "human",... | [
17,
35,
54,
73,
92,
110,
129,
148,
167,
185,
204,
223,
242,
260,
279,
298
] | [
"{\"17\":{\"size\":[1440,1920],\"counts\":\"UUjb23i\\\\16N1N3N1N2O1O2M2O1O1O1O1O1O1N2O1O1O1O001O1O1O00100O001O001O001O0000000RWO\"},\"35\":{\"size\":[1440,1920],\"counts\":\"QfZb27i\\\\12M2O1N3N1O1O1N2O1O1O1O1O1N2O1O001O1O1O001O1O00100O001O00001O01O01O001O0000010O00001oj4\"},\"54\":{\"size\":[1440,1920],\"counts\":... | 622c1b29-76c6-4845-95df-7e54792687d4_16f_end_000005.json | 622c1b29-76c6-4845-95df-7e54792687d4 | 16 | end |
EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment the silver microwave on the kitchen counter in the video?"
},
{
"from": "gpt",
"value": "There isn't a the silver microwave on the kitchen counter in this video."
},
{
"from": "human",
"value": "Can you segment the metallic kitchen knife w... | [
0,
9,
18,
28,
37,
46,
56,
65,
75,
84,
93,
103,
112,
121,
131,
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150,
159,
168,
178,
187,
196,
206,
215,
225,
234,
243,
253,
262,
271,
281,
290
] | [
"{\"0\":null,\"9\":null,\"18\":null,\"28\":null,\"37\":null,\"46\":null,\"56\":null,\"65\":null,\"75\":null,\"84\":null,\"93\":null,\"103\":null,\"112\":null,\"121\":null,\"131\":null,\"140\":null,\"150\":null,\"159\":null,\"168\":null,\"178\":null,\"187\":null,\"196\":null,\"206\":null,\"215\":null,\"225\":null,\"... | 622c1b29-76c6-4845-95df-7e54792687d4_32f_start_000006.json | 622c1b29-76c6-4845-95df-7e54792687d4 | 32 | start |
EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment the silver microwave on the kitchen counter in the video?"
},
{
"from": "gpt",
"value": "There isn't a the silver microwave on the kitchen counter in this video."
},
{
"from": "human",
"value": "Can you segment transparent plastic containe... | [
4,
13,
22,
32,
41,
50,
60,
69,
79,
88,
97,
107,
116,
125,
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154,
163,
172,
182,
191,
200,
210,
219,
229,
238,
247,
257,
266,
275,
285,
294
] | [
"{\"4\":null,\"13\":null,\"22\":null,\"32\":null,\"41\":null,\"50\":null,\"60\":null,\"69\":null,\"79\":null,\"88\":null,\"97\":null,\"107\":null,\"116\":null,\"125\":null,\"135\":null,\"144\":null,\"154\":null,\"163\":null,\"172\":null,\"182\":null,\"191\":null,\"200\":null,\"210\":null,\"219\":null,\"229\":null,\... | 622c1b29-76c6-4845-95df-7e54792687d4_32f_middle_000007.json | 622c1b29-76c6-4845-95df-7e54792687d4 | 32 | middle |
EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment the object that can store or hold small food items with the following attributes: small, rectangular, transparent, located on the countertop near a cutting board in the video?"
},
{
"from": "gpt",
"value": "It is [SEG]."
},
{
"from": "human",
... | [
8,
17,
26,
36,
45,
54,
64,
73,
83,
92,
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167,
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223,
233,
242,
251,
261,
270,
279,
289,
298
] | [
"{\"8\":null,\"17\":null,\"26\":{\"size\":[1440,1920],\"counts\":\"k?T1l[100000O2N1N3M2N3L3N3M2M4M2N3N1M4M2O1O2M2N2N2N2O1O2N11M3M3M3N2N2N101N1O1O2N1O2N1O1N4M1M4L3N2N2O102L5K4L4J6D<EnUna2\"},\"36\":{\"size\":[1440,1920],\"counts\":\"Vf4c0\\\\\\\\12M4L3L4L4L4N1M4K5N1N4K3N3N2eNRNagNP2fY11N2N3N1N3L3N3N1O001O0O101N1010O... | 622c1b29-76c6-4845-95df-7e54792687d4_32f_end_000008.json | 622c1b29-76c6-4845-95df-7e54792687d4 | 32 | end |
EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment kitchen knife with the following attributes: metallic blade with a dark handle, located on a countertop near food items, medium-sized compared to surrounding objects in the video?"
},
{
"from": "gpt",
"value": "It is [SEG]."
},
{
"from": "huma... | [
0,
4,
9,
14,
18,
23,
28,
32,
37,
42,
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201,
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215,
220,
225,
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EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment wooden chopsticks on the stovetop and sink in the video?"
},
{
"from": "gpt",
"value": "It is [SEG]."
},
{
"from": "human",
"value": "Can you segment the object that can cut vegetables or other food items with the following attributes: met... | [
2,
6,
11,
16,
20,
25,
30,
34,
39,
44,
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184,
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198,
203,
208,
212,
217,
222,
227... | [
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EgoMask/EgoMask/dataset/egomask-train/train/JPEGImages/622c1b29-76c6-4845-95df-7e54792687d4 | [
{
"from": "human",
"value": "Can you segment wooden chopsticks on the stovetop and sink in the video?"
},
{
"from": "gpt",
"value": "It is [SEG]."
},
{
"from": "human",
"value": "Can you segment kitchen knife with the following attributes: metallic blade with a dark handle, located o... | [
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162,
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176,
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209,
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228... | [
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