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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 ({'shards', 'version'}) and 4 missing columns ({'filename', 'no', 'selected_indices', 'keyword'}).
This happened while the json dataset builder was generating data using
hf://datasets/mesolitica/google-image-malaysia-location-dedup/embedding/index.json (at revision dc5881f9ff33f960877dc1d2e10ecce024f49eba)
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 "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table
pa_table = table_cast(pa_table, self._schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
shards: list<item: struct<column_encodings: list<item: string>, column_names: list<item: string>, column_sizes: list<item: int64>, compression: null, format: string, hashes: list<item: string>, raw_data: struct<basename: string, bytes: int64, hashes: struct<sha1: string, xxh64: string>>, samples: int64, size_limit: int64, version: int64, zip_data: null>>
child 0, item: struct<column_encodings: list<item: string>, column_names: list<item: string>, column_sizes: list<item: int64>, compression: null, format: string, hashes: list<item: string>, raw_data: struct<basename: string, bytes: int64, hashes: struct<sha1: string, xxh64: string>>, samples: int64, size_limit: int64, version: int64, zip_data: null>
child 0, column_encodings: list<item: string>
child 0, item: string
child 1, column_names: list<item: string>
child 0, item: string
child 2, column_sizes: list<item: int64>
child 0, item: int64
child 3, compression: null
child 4, format: string
child 5, hashes: list<item: string>
child 0, item: string
child 6, raw_data: struct<basename: string, bytes: int64, hashes: struct<sha1: string, xxh64: string>>
child 0, basename: string
child 1, bytes: int64
child 2, hashes: struct<sha1: string, xxh64: string>
child 0, sha1: string
child 1, xxh64: string
child 7, samples: int64
child 8, size_limit: int64
child 9, version: int64
child 10, zip_data: null
version: int64
to
{'filename': Value(dtype='string', id=None), 'keyword': Value(dtype='string', id=None), 'no': Value(dtype='int64', id=None), 'selected_indices': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)}
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 1319, in compute_config_parquet_and_info_response
parquet_operations, partial = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 912, in stream_convert_to_parquet
builder._prepare_split(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split
for job_id, done, content in self._prepare_split_single(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, 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 ({'shards', 'version'}) and 4 missing columns ({'filename', 'no', 'selected_indices', 'keyword'}).
This happened while the json dataset builder was generating data using
hf://datasets/mesolitica/google-image-malaysia-location-dedup/embedding/index.json (at revision dc5881f9ff33f960877dc1d2e10ecce024f49eba)
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? Open a discussion for direct support.
filename
string | keyword
string | no
int64 | selected_indices
sequence |
|---|---|---|---|
train-00048-of-01000.parquet | Bekenu - Beg Berkunci Bekenu | 15 | [
4019,
4023,
4025,
4028,
4032
] |
train-00242-of-01000.parquet | Jalan Senohong 17/44 Shah Alam | 46 | [
2220,
2226
] |
train-00812-of-01000.parquet | Taman Megah Jaya Ayer Tawar | 16 | [
2556,
2560,
2575,
2577,
2586,
2587
] |
train-00299-of-01000.parquet | Kampung Batu 13 Teluk Intan | 17 | [
397,
404
] |
train-00272-of-01000.parquet | Jalan Ushawan Kuala Lumpur | 16 | [
666,
684,
701,
708,
723,
732,
743,
752
] |
train-00911-of-01000.parquet | Taman Seri Sementa Klang | 15 | [
1535,
1556,
1702,
1727,
1731,
1739,
1769,
1789
] |
train-00465-of-01000.parquet | Limbang Limbang | 6 | [
720,
723,
727,
766,
769,
776,
785,
792,
804,
940,
959,
1025,
1037,
1079,
1107,
1120,
1152,
1166,
1205,
1208,
1249,
1256,
1261,
1262,
1263,
1285,
1286,
1325
] |
train-00284-of-01000.parquet | Kampung Aji Hilir Bota | 75 | [
2312,
2314,
2316
] |
train-00356-of-01000.parquet | Kampung Palimbayan Kuala Lumpur | 25 | [
579,
586,
622,
627,
634,
645
] |
train-00686-of-01000.parquet | Taman Bersatu (Jalan Betong) Pengkalan Hulu | 32 | [
2975,
2979,
2982,
2986,
2987
] |
train-00199-of-01000.parquet | Jalan Imam Haji Ismail Machang | 31 | [] |
train-00123-of-01000.parquet | Ijok Batang Berjuntai | 9 | [
992,
1008,
1045,
1073,
1104,
1117
] |
train-00836-of-01000.parquet | Taman Orchidwood Kuching | 5 | [
206,
254,
281,
283,
298,
306
] |
train-00427-of-01000.parquet | Kompleks Perumahan Guuru Langkawi | 38 | [
3947,
3955
] |
train-00351-of-01000.parquet | Kampung Nerusa Johol | 62 | [
3422,
3425,
3431
] |
train-00260-of-01000.parquet | Jalan TR 9/2 Petaling Jaya | 35 | [
1232,
1238,
1258,
1274,
1278,
1282
] |
train-00359-of-01000.parquet | Kampung Pasir ( Kuala Dipang ) Jeram | 74 | [
2711,
2713,
2718
] |
train-00466-of-01000.parquet | Lintang Damai Bukit Mertajam | 53 | [
2265,
2283,
2287
] |
train-00377-of-01000.parquet | Kampung Semadong Kangar | 22 | [
781,
782,
787,
795
] |
train-00387-of-01000.parquet | Kampung Sungai Kota Tanjong Piandang | 45 | [
2525,
2526,
2529
] |
train-00372-of-01000.parquet | Kampung Rantau Panjang Kampung Gajah | 3 | [
103,
104
] |
train-00627-of-01000.parquet | Senai Industrial Park Senai | 6 | [
2089,
2119,
2137,
2168,
2210,
2217,
2227,
2255,
2284,
2354,
2363,
2374,
2429,
2545,
2613,
2641,
2693
] |
train-00791-of-01000.parquet | Taman Kuala Idaman Masjid Tanah | 6 | [
2677,
2699,
2700
] |
train-00369-of-01000.parquet | Kampung Pulau Kudur Kota Bharu | 73 | [
2659,
2661,
2675,
2676,
2687,
2690
] |
train-00549-of-01000.parquet | Parit Simin Semerah | 1 | [
17,
26,
28,
32
] |
train-00350-of-01000.parquet | Kampung Mukut Mersing | 60 | [
3306,
3328,
3401,
3405,
3434,
3454
] |
train-00483-of-01000.parquet | Lorong Masjid India (2 & 4) Kuala Lumpur | 16 | [
382,
390,
406,
434,
455,
504,
506,
511,
533
] |
train-00050-of-01000.parquet | Beluran | 26 | [
1836,
1839,
1851,
1872,
1901,
1913,
1923,
1924,
1935,
1936,
1982,
2010,
2036,
2040,
2104,
2147,
2234,
2245,
2247,
2255,
2256,
2264,
2286,
2298,
2303,
2314,
2320,
2321,
2327,
2375
] |
train-00332-of-01000.parquet | Kampung Kolam Pendang | 27 | [
1574,
1577,
1589,
1600,
1614
] |
train-00748-of-01000.parquet | Taman Golf Heights Seremban | 27 | [
3278,
3293,
3302
] |
train-00309-of-01000.parquet | Kampung Bukit Semanggol Simpang Ampat Semanggol | 117 | [
3772,
3786,
3801,
3876,
3877,
3901,
3902
] |
train-00588-of-01000.parquet | Plaza Hang Tuah Melaka | 16 | [
1637,
1638,
1663,
1673,
1678,
1691,
1700,
1714,
1724,
1728,
1739,
1749,
1760,
1774,
1779,
1782,
1783,
1805,
1810
] |
train-00267-of-01000.parquet | Jalan Teluk Gadong Kuala Lumpur | 9 | [
743,
779,
780
] |
train-00318-of-01000.parquet | Kampung Gandai Ayer Hitam | 53 | [
2866,
2875
] |
train-00236-of-01000.parquet | Jalan Salung 33/26 Shah Alam | 6 | [
332,
336
] |
train-00204-of-01000.parquet | Jalan Jerantut 26/128 Shah Alam | 67 | [
3340,
3348,
3355
] |
train-00282-of-01000.parquet | Kabong Kabong | 0 | [
1,
20,
27,
29,
56,
61,
67,
95,
116,
123,
143,
172,
190,
218,
220,
234,
238,
251,
275,
303
] |
train-00484-of-01000.parquet | Lorong Muntahah (1 - 3C) Kota Kinabalu | 31 | [
1105,
1115
] |
train-00100-of-01000.parquet | Empangan Timah Tassoh JPS Kangar | 3 | [
57,
72,
102,
126
] |
train-00406-of-01000.parquet | Kampung Wak Musa Pekan Nenas | 66 | [
2359
] |
train-00702-of-01000.parquet | Taman Bukit Mewah Semenyih | 1 | [
464,
524,
525,
533,
546,
552,
612,
709,
776,
973
] |
train-00944-of-01000.parquet | Taman Tas Mahkota Kuantan | 9 | [
2675,
2688,
2718,
2725,
2746,
2747,
2788,
2796,
2807,
2811,
2824,
2854
] |
train-00297-of-01000.parquet | Kampung Baru Senggarang | 2 | [
36,
40,
45,
56,
62
] |
train-00657-of-01000.parquet | Sungai Punai Pontian | 10 | [
821,
823,
837
] |
train-00379-of-01000.parquet | Kampung Seri Merlow Lubok China | 82 | [
3039,
3042,
3054
] |
train-00167-of-01000.parquet | Jalan Betek Pelabuhan Klang | 11 | [
504,
513,
517,
522,
528
] |
train-00331-of-01000.parquet | Kampung Klau Kechil Raub | 49 | [
2242,
2243,
2246,
2255,
2256
] |
train-00394-of-01000.parquet | Kampung Tanjong Baru Kuala Berang | 53 | [
1597
] |
train-00752-of-01000.parquet | Taman Harmoni Impian Sungai Pelek | 9 | [
790,
792
] |
train-00383-of-01000.parquet | Kampung Stenggang Bau | 109 | [
3349,
3354,
3384,
3415
] |
train-00303-of-01000.parquet | Kampung Bendang Sera Serdang | 52 | [
1288,
1292
] |
train-00296-of-01000.parquet | Kampung Baru Seberang Kuala Lumpur | 56 | [
3522,
3552,
3598,
3616,
3621
] |
train-00380-of-01000.parquet | Kampung Serting Tengah Batu Kikir | 44 | [
1680,
1691,
1700,
1745
] |
train-00175-of-01000.parquet | Jalan Cantek Johor Bahru | 16 | [
964,
984,
986,
991,
992,
998
] |
train-00355-of-01000.parquet | Kampung Padang Ulu Takir Kuala Terengganu | 36 | [
1751,
1753
] |
train-00162-of-01000.parquet | Jalan Bedok Kuala Lumpur | 77 | [
3136,
3141,
3149,
3152,
3158,
3164,
3166
] |
train-00531-of-01000.parquet | Paka | 4 | [
235,
236,
241,
249,
257,
266,
297,
305,
307,
319,
327,
349,
390,
411,
425,
436,
438,
441,
442,
463,
491,
517,
521,
525,
529,
542,
568,
598,
602,
608,
630,
637,
654,
659,
663,
681,
719,
721,
737,
749,
768,
769,
784,
795,
799,
849,
851,
877,
888
] |
train-00367-of-01000.parquet | Kampung Petaseh Kuala Klawang | 3 | [
56,
68,
72
] |
train-00210-of-01000.parquet | Jalan Kekwa Serendah | 48 | [
3349,
3477,
3480,
3489,
3501
] |
train-00089-of-01000.parquet | Dataran Pahlawan Melaka | 0 | [
0,
2,
12,
18,
34,
53,
57,
62,
71,
82,
85,
89,
92,
110,
116,
121,
127,
137,
147,
151,
159,
164,
207,
226,
250,
251,
279,
286,
290,
291,
297,
306,
314,
318,
319,
331
] |
train-00785-of-01000.parquet | Taman King Dom Kuching | 45 | [
2555,
2559,
2560,
2568,
2570
] |
train-00588-of-01000.parquet | Pokok Asam Simpang Ampat | 32 | [
3491,
3498,
3503
] |
train-00957-of-01000.parquet | Taman Villa Mutiara Jerantut | 21 | [
2617,
2618,
2631,
2642,
2646,
2653
] |
train-00228-of-01000.parquet | Jalan Pulau Ketam (U10/61A - U10/62D) Shah Alam | 8 | [
316,
319,
329
] |
train-00275-of-01000.parquet | Jalan wangsa Delima 1A Kuala Lumpur | 45 | [
1787,
1808,
1828,
1838,
1846
] |
train-00079-of-01000.parquet | Changkat Kampar Kuala Kangsar | 26 | [
3156,
3174
] |
train-00396-of-01000.parquet | Kampung Tebing Tinggi Segamat | 43 | [
3215,
3219,
3222
] |
train-00573-of-01000.parquet | Persiaran Jelutong Kuala Lumpur | 16 | [
2152,
2166,
2196,
2197,
2238,
2258
] |
train-00163-of-01000.parquet | Jalan Belalang Enam 20/7F Shah Alam | 8 | [
180,
189,
190,
191
] |
train-00806-of-01000.parquet | Taman Manggis Bukit Mertajam | 20 | [
4037
] |
train-00756-of-01000.parquet | Taman Idaman Kuantan | 18 | [
1550,
1564,
1575,
1580,
1586,
1648
] |
train-00082-of-01000.parquet | Cherating Kuantan | 1 | [
695,
740,
752,
825,
869,
895,
920,
941,
1004,
1009,
1051,
1085,
1185,
1192,
1194,
1216,
1224,
1228,
1286,
1291,
1348
] |
train-00576-of-01000.parquet | Persiaran Saujana Shah Alam | 7 | [
675,
690,
728,
734,
752,
763,
779
] |
train-00318-of-01000.parquet | Kampung Gading Galuh Pulai Chondong | 4 | [
93,
111
] |
train-00344-of-01000.parquet | Kampung Manikavasagam Pulau Carey | 25 | [
723,
724,
726,
747,
750,
758,
762
] |
train-00993-of-01000.parquet | Vistaria Residensi Kuala Lumpur | 15 | [
3363,
3366,
3385,
3398,
3478,
3481,
3556,
3614,
3736
] |
train-00808-of-01000.parquet | Taman Mas Ria Muar | 35 | [
2868,
2874,
2876,
2888
] |
train-00959-of-01000.parquet | Taman Warisan Kuala Krai | 4 | [
1220,
1228,
1277,
1286
] |
train-00157-of-01000.parquet | Jalan Balakong Jaya (23, 23A, 23B, 24) Seri Kembangan | 3 | [
157
] |
train-00041-of-01000.parquet | Batu Balai Damak | 71 | [
3930,
3970
] |
train-00740-of-01000.parquet | Taman Duranta Seremban | 5 | [
157,
182,
199,
207,
219,
221
] |
train-00263-of-01000.parquet | Jalan Taming Sari Melaka | 10 | [
1233,
1267,
1287,
1290,
1299,
1331,
1354,
1373,
1380,
1392,
1436,
1490,
1497,
1527,
1531,
1543,
1566,
1585,
1596,
1598,
1637,
1641,
1645,
1648
] |
train-00823-of-01000.parquet | Taman Molek Gemas | 31 | [
3300,
3306,
3314,
3320
] |
train-00001-of-01000.parquet | Alor Malai Alor Setar | 4 | [
341,
345,
346,
351,
364,
400,
410,
420,
430,
534,
540,
591,
613,
631,
653,
662,
694,
704,
712,
729,
733,
776,
788,
795,
813,
817,
824,
886,
936,
955
] |
train-00417-of-01000.parquet | Kementerian Kewangan Sabah Kota Kinabalu | 10 | [
1406,
1418,
1437,
1467,
1476,
1505
] |
train-00168-of-01000.parquet | Jalan Bringin Kluang | 15 | [
973,
976,
993
] |
train-00375-of-01000.parquet | Kampung Seberang Kodiang | 29 | [
831,
833
] |
train-00154-of-01000.parquet | Jalan Ayer Molek Kuala Lumpur | 56 | [
3249,
3253,
3259
] |
train-00299-of-01000.parquet | Kampung Batu 26 Tanjong Tualang | 78 | [
1590,
1593
] |
train-00424-of-01000.parquet | Klang - Peti Surat 95 Klang | 33 | [
3923,
3929,
3930
] |
train-00658-of-01000.parquet | Sungai Sumun - Peti Surat Sungai Sumun | 43 | [
3963,
3965,
3967
] |
train-00473-of-01000.parquet | Lorong Bunga Kenanga Kecil Kota Kinabalu | 42 | [
1884
] |
train-00773-of-01000.parquet | Taman Johor Jaya Johor Bahru | 11 | [
2098,
2099,
2103,
2110,
2146,
2155,
2158,
2191,
2194,
2236,
2266,
2290,
2362,
2370,
2412,
2417,
2418,
2428,
2439,
2457,
2467,
2473,
2514,
2579,
2719
] |
train-00332-of-01000.parquet | Kampung Kolam Kedai Menanti Melor | 20 | [] |
train-00572-of-01000.parquet | Persiaran Geleri Kepayang Ipoh | 27 | [
2657
] |
train-00723-of-01000.parquet | Taman Danau Kota Kuala Lumpur | 4 | [
614,
621,
656,
659,
663,
684,
693,
719,
733,
749,
791,
834,
846,
861,
920,
929,
932,
948,
951,
962,
973,
1021,
1045,
1082,
1088,
1100,
1101,
1107,
1217,
1235,
1244
] |
train-00342-of-01000.parquet | Kampung Lubok Gong Rantau Panjang | 10 | [
302,
318,
326
] |
train-00343-of-01000.parquet | Kampung Mak Chik Alor Setar | 24 | [
868,
870
] |
train-00380-of-01000.parquet | Kampung Seterus Sauk | 62 | [
2225,
2228
] |
train-00892-of-01000.parquet | Taman Sentosa Gemas | 18 | [
1205,
1252,
1302,
1320
] |
End of preview.
Google Image Malaysia Location Dedup
Original dataset https://huggingface.co/datasets/malaysia-ai/crawl-google-image-malaysia-location
Source code at https://github.com/mesolitica/malaysian-dataset/tree/master/vlm/dedup-malaysia-location
Dedup 50% similar
dedup-0.5.jsonl, total deduped 227937 images,
{'filename': 'train-00812-of-01000.parquet',
'keyword': 'Taman Megah Jaya Ayer Tawar',
'no': 16,
'selected_indices': [2556, 2559, 2575, 2577, 2586, 2587, 2595]}
Dedup 60% similar
dedup-0.6.jsonl, total deduped 487301 images,
{'filename': 'train-00404-of-01000.parquet',
'keyword': 'Kampung Tok Wan Nik Padang Besar',
'no': 92,
'selected_indices': [2100, 2102, 2103, 2104]}
filenameis the parquet file from the original repository.selected_indicesis the index of dataframe of that filename.
Embedding
We convert to embedding using https://huggingface.co/google/siglip-base-patch16-512, we use MosaicML for faster indexing,
from streaming import MDSWriter
from streaming.base.format.mds.encodings import Encoding, _encodings
from streaming import LocalDataset
import streaming
import numpy as np
from tqdm import tqdm
class Float32(Encoding):
def encode(self, obj) -> bytes:
return obj.tobytes()
def decode(self, data: bytes):
return np.frombuffer(data, np.float32)
_encodings['float32'] = Float32
dataset = LocalDataset('embedding')
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