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Datasets:
tanganke
/
sun397

Tasks:
Image Classification
Modalities:
Image
Formats:
parquet
Languages:
English
Size:
10K - 100K
Libraries:
Datasets
Dask
Dataset card Viewer Files Community
1
tanganke commited on
Commit
9c4afd6
·
verified ·
1 Parent(s): 4382ca2

Convert dataset to Parquet (#1)

Browse files

- Convert dataset to Parquet (89559e6d6403b4dfd372f45c1a39899032461cc3)
- Delete data file (0b48c5b9fae94ac9427dd76a9c193748360671b1)
- Delete loading script (ede1f4f69afd491a3d873c0d973b8df49ee68a3b)
- Delete data file (8bdf21369898d909dc6ee2597852e734fa02d76d)

Files changed (38) hide show
  1. README.md +17 -10
  2. data/{test.zip → test-00000-of-00018.parquet} +2 -2
  3. data/{train.zip → test-00001-of-00018.parquet} +2 -2
  4. data/test-00002-of-00018.parquet +3 -0
  5. data/test-00003-of-00018.parquet +3 -0
  6. data/test-00004-of-00018.parquet +3 -0
  7. data/test-00005-of-00018.parquet +3 -0
  8. data/test-00006-of-00018.parquet +3 -0
  9. data/test-00007-of-00018.parquet +3 -0
  10. data/test-00008-of-00018.parquet +3 -0
  11. data/test-00009-of-00018.parquet +3 -0
  12. data/test-00010-of-00018.parquet +3 -0
  13. data/test-00011-of-00018.parquet +3 -0
  14. data/test-00012-of-00018.parquet +3 -0
  15. data/test-00013-of-00018.parquet +3 -0
  16. data/test-00014-of-00018.parquet +3 -0
  17. data/test-00015-of-00018.parquet +3 -0
  18. data/test-00016-of-00018.parquet +3 -0
  19. data/test-00017-of-00018.parquet +3 -0
  20. data/train-00000-of-00018.parquet +3 -0
  21. data/train-00001-of-00018.parquet +3 -0
  22. data/train-00002-of-00018.parquet +3 -0
  23. data/train-00003-of-00018.parquet +3 -0
  24. data/train-00004-of-00018.parquet +3 -0
  25. data/train-00005-of-00018.parquet +3 -0
  26. data/train-00006-of-00018.parquet +3 -0
  27. data/train-00007-of-00018.parquet +3 -0
  28. data/train-00008-of-00018.parquet +3 -0
  29. data/train-00009-of-00018.parquet +3 -0
  30. data/train-00010-of-00018.parquet +3 -0
  31. data/train-00011-of-00018.parquet +3 -0
  32. data/train-00012-of-00018.parquet +3 -0
  33. data/train-00013-of-00018.parquet +3 -0
  34. data/train-00014-of-00018.parquet +3 -0
  35. data/train-00015-of-00018.parquet +3 -0
  36. data/train-00016-of-00018.parquet +3 -0
  37. data/train-00017-of-00018.parquet +3 -0
  38. sun397.py +0 -438
README.md CHANGED
@@ -1,4 +1,10 @@
1
  ---
 
 
 
 
 
 
2
  dataset_info:
3
  features:
4
  - name: image
@@ -406,19 +412,20 @@ dataset_info:
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  '396': youth hostel
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  splits:
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  - name: train
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- num_bytes: 2597332
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  num_examples: 19850
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  - name: test
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- num_bytes: 2557632
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  num_examples: 19850
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- download_size: 14342875038
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- dataset_size: 5154964
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- task_categories:
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- - image-classification
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- language:
419
- - en
420
- size_categories:
421
- - 10K<n<100K
 
422
  ---
423
 
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  ---
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+ language:
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+ - 10K<n<100K
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+ - image-classification
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  dataset_info:
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  features:
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  - name: image
 
412
  '396': youth hostel
413
  splits:
414
  - name: train
415
+ num_bytes: 8834961188.3
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  num_examples: 19850
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  - name: test
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+ num_bytes: 8610045383.95
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  num_examples: 19850
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+ download_size: 14498373101
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+ dataset_size: 17445006572.25
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+ configs:
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+ - config_name: default
424
+ data_files:
425
+ - split: train
426
+ path: data/train-*
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+ - split: test
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+ path: data/test-*
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  ---
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sun397.py DELETED
@@ -1,438 +0,0 @@
1
- import datasets
2
- from datasets.data_files import DataFilesDict
3
- from datasets.packaged_modules.imagefolder.imagefolder import ImageFolder, ImageFolderConfig
4
-
5
- logger = datasets.logging.get_logger(__name__)
6
-
7
-
8
- class SUN397(ImageFolder):
9
- R"""
10
- SUN397 dataset for image classification.
11
- """
12
-
13
- BUILDER_CONFIG_CLASS = ImageFolderConfig
14
- BUILDER_CONFIGS = [
15
- ImageFolderConfig(
16
- name="default",
17
- features=("images", "labels"),
18
- data_files=DataFilesDict({split: f"data/{split}.zip" for split in ["train", "test"]}),
19
- )
20
- ]
21
-
22
- classnames = [
23
- "abbey",
24
- "airplane cabin",
25
- "airport terminal",
26
- "alley",
27
- "amphitheater",
28
- "amusement arcade",
29
- "amusement park",
30
- "anechoic chamber",
31
- "apartment building outdoor",
32
- "apse indoor",
33
- "aquarium",
34
- "aqueduct",
35
- "arch",
36
- "archive",
37
- "arrival gate outdoor",
38
- "art gallery",
39
- "art school",
40
- "art studio",
41
- "assembly line",
42
- "athletic field outdoor",
43
- "atrium public",
44
- "attic",
45
- "auditorium",
46
- "auto factory",
47
- "badlands",
48
- "badminton court indoor",
49
- "baggage claim",
50
- "bakery shop",
51
- "balcony exterior",
52
- "balcony interior",
53
- "ball pit",
54
- "ballroom",
55
- "bamboo forest",
56
- "banquet hall",
57
- "bar",
58
- "barn",
59
- "barndoor",
60
- "baseball field",
61
- "basement",
62
- "basilica",
63
- "basketball court outdoor",
64
- "bathroom",
65
- "batters box",
66
- "bayou",
67
- "bazaar indoor",
68
- "bazaar outdoor",
69
- "beach",
70
- "beauty salon",
71
- "bedroom",
72
- "berth",
73
- "biology laboratory",
74
- "bistro indoor",
75
- "boardwalk",
76
- "boat deck",
77
- "boathouse",
78
- "bookstore",
79
- "booth indoor",
80
- "botanical garden",
81
- "bow window indoor",
82
- "bow window outdoor",
83
- "bowling alley",
84
- "boxing ring",
85
- "brewery indoor",
86
- "bridge",
87
- "building facade",
88
- "bullring",
89
- "burial chamber",
90
- "bus interior",
91
- "butchers shop",
92
- "butte",
93
- "cabin outdoor",
94
- "cafeteria",
95
- "campsite",
96
- "campus",
97
- "canal natural",
98
- "canal urban",
99
- "candy store",
100
- "canyon",
101
- "car interior backseat",
102
- "car interior frontseat",
103
- "carrousel",
104
- "casino indoor",
105
- "castle",
106
- "catacomb",
107
- "cathedral indoor",
108
- "cathedral outdoor",
109
- "cavern indoor",
110
- "cemetery",
111
- "chalet",
112
- "cheese factory",
113
- "chemistry lab",
114
- "chicken coop indoor",
115
- "chicken coop outdoor",
116
- "childs room",
117
- "church indoor",
118
- "church outdoor",
119
- "classroom",
120
- "clean room",
121
- "cliff",
122
- "cloister indoor",
123
- "closet",
124
- "clothing store",
125
- "coast",
126
- "cockpit",
127
- "coffee shop",
128
- "computer room",
129
- "conference center",
130
- "conference room",
131
- "construction site",
132
- "control room",
133
- "control tower outdoor",
134
- "corn field",
135
- "corral",
136
- "corridor",
137
- "cottage garden",
138
- "courthouse",
139
- "courtroom",
140
- "courtyard",
141
- "covered bridge exterior",
142
- "creek",
143
- "crevasse",
144
- "crosswalk",
145
- "cubicle office",
146
- "dam",
147
- "delicatessen",
148
- "dentists office",
149
- "desert sand",
150
- "desert vegetation",
151
- "diner indoor",
152
- "diner outdoor",
153
- "dinette home",
154
- "dinette vehicle",
155
- "dining car",
156
- "dining room",
157
- "discotheque",
158
- "dock",
159
- "doorway outdoor",
160
- "dorm room",
161
- "driveway",
162
- "driving range outdoor",
163
- "drugstore",
164
- "electrical substation",
165
- "elevator door",
166
- "elevator interior",
167
- "elevator shaft",
168
- "engine room",
169
- "escalator indoor",
170
- "excavation",
171
- "factory indoor",
172
- "fairway",
173
- "fastfood restaurant",
174
- "field cultivated",
175
- "field wild",
176
- "fire escape",
177
- "fire station",
178
- "firing range indoor",
179
- "fishpond",
180
- "florist shop indoor",
181
- "food court",
182
- "forest broadleaf",
183
- "forest needleleaf",
184
- "forest path",
185
- "forest road",
186
- "formal garden",
187
- "fountain",
188
- "galley",
189
- "game room",
190
- "garage indoor",
191
- "garbage dump",
192
- "gas station",
193
- "gazebo exterior",
194
- "general store indoor",
195
- "general store outdoor",
196
- "gift shop",
197
- "golf course",
198
- "greenhouse indoor",
199
- "greenhouse outdoor",
200
- "gymnasium indoor",
201
- "hangar indoor",
202
- "hangar outdoor",
203
- "harbor",
204
- "hayfield",
205
- "heliport",
206
- "herb garden",
207
- "highway",
208
- "hill",
209
- "home office",
210
- "hospital",
211
- "hospital room",
212
- "hot spring",
213
- "hot tub outdoor",
214
- "hotel outdoor",
215
- "hotel room",
216
- "house",
217
- "hunting lodge outdoor",
218
- "ice cream parlor",
219
- "ice floe",
220
- "ice shelf",
221
- "ice skating rink indoor",
222
- "ice skating rink outdoor",
223
- "iceberg",
224
- "igloo",
225
- "industrial area",
226
- "inn outdoor",
227
- "islet",
228
- "jacuzzi indoor",
229
- "jail cell",
230
- "jail indoor",
231
- "jewelry shop",
232
- "kasbah",
233
- "kennel indoor",
234
- "kennel outdoor",
235
- "kindergarden classroom",
236
- "kitchen",
237
- "kitchenette",
238
- "labyrinth outdoor",
239
- "lake natural",
240
- "landfill",
241
- "landing deck",
242
- "laundromat",
243
- "lecture room",
244
- "library indoor",
245
- "library outdoor",
246
- "lido deck outdoor",
247
- "lift bridge",
248
- "lighthouse",
249
- "limousine interior",
250
- "living room",
251
- "lobby",
252
- "lock chamber",
253
- "locker room",
254
- "mansion",
255
- "manufactured home",
256
- "market indoor",
257
- "market outdoor",
258
- "marsh",
259
- "martial arts gym",
260
- "mausoleum",
261
- "medina",
262
- "moat water",
263
- "monastery outdoor",
264
- "mosque indoor",
265
- "mosque outdoor",
266
- "motel",
267
- "mountain",
268
- "mountain snowy",
269
- "movie theater indoor",
270
- "museum indoor",
271
- "music store",
272
- "music studio",
273
- "nuclear power plant outdoor",
274
- "nursery",
275
- "oast house",
276
- "observatory outdoor",
277
- "ocean",
278
- "office",
279
- "office building",
280
- "oil refinery outdoor",
281
- "oilrig",
282
- "operating room",
283
- "orchard",
284
- "outhouse outdoor",
285
- "pagoda",
286
- "palace",
287
- "pantry",
288
- "park",
289
- "parking garage indoor",
290
- "parking garage outdoor",
291
- "parking lot",
292
- "parlor",
293
- "pasture",
294
- "patio",
295
- "pavilion",
296
- "pharmacy",
297
- "phone booth",
298
- "physics laboratory",
299
- "picnic area",
300
- "pilothouse indoor",
301
- "planetarium outdoor",
302
- "playground",
303
- "playroom",
304
- "plaza",
305
- "podium indoor",
306
- "podium outdoor",
307
- "pond",
308
- "poolroom establishment",
309
- "poolroom home",
310
- "power plant outdoor",
311
- "promenade deck",
312
- "pub indoor",
313
- "pulpit",
314
- "putting green",
315
- "racecourse",
316
- "raceway",
317
- "raft",
318
- "railroad track",
319
- "rainforest",
320
- "reception",
321
- "recreation room",
322
- "residential neighborhood",
323
- "restaurant",
324
- "restaurant kitchen",
325
- "restaurant patio",
326
- "rice paddy",
327
- "riding arena",
328
- "river",
329
- "rock arch",
330
- "rope bridge",
331
- "ruin",
332
- "runway",
333
- "sandbar",
334
- "sandbox",
335
- "sauna",
336
- "schoolhouse",
337
- "sea cliff",
338
- "server room",
339
- "shed",
340
- "shoe shop",
341
- "shopfront",
342
- "shopping mall indoor",
343
- "shower",
344
- "skatepark",
345
- "ski lodge",
346
- "ski resort",
347
- "ski slope",
348
- "sky",
349
- "skyscraper",
350
- "slum",
351
- "snowfield",
352
- "squash court",
353
- "stable",
354
- "stadium baseball",
355
- "stadium football",
356
- "stage indoor",
357
- "staircase",
358
- "street",
359
- "subway interior",
360
- "subway station platform",
361
- "supermarket",
362
- "sushi bar",
363
- "swamp",
364
- "swimming pool indoor",
365
- "swimming pool outdoor",
366
- "synagogue indoor",
367
- "synagogue outdoor",
368
- "television studio",
369
- "temple east asia",
370
- "temple south asia",
371
- "tennis court indoor",
372
- "tennis court outdoor",
373
- "tent outdoor",
374
- "theater indoor procenium",
375
- "theater indoor seats",
376
- "thriftshop",
377
- "throne room",
378
- "ticket booth",
379
- "toll plaza",
380
- "topiary garden",
381
- "tower",
382
- "toyshop",
383
- "track outdoor",
384
- "train railway",
385
- "train station platform",
386
- "tree farm",
387
- "tree house",
388
- "trench",
389
- "underwater coral reef",
390
- "utility room",
391
- "valley",
392
- "van interior",
393
- "vegetable garden",
394
- "veranda",
395
- "veterinarians office",
396
- "viaduct",
397
- "videostore",
398
- "village",
399
- "vineyard",
400
- "volcano",
401
- "volleyball court indoor",
402
- "volleyball court outdoor",
403
- "waiting room",
404
- "warehouse indoor",
405
- "water tower",
406
- "waterfall block",
407
- "waterfall fan",
408
- "waterfall plunge",
409
- "watering hole",
410
- "wave",
411
- "wet bar",
412
- "wheat field",
413
- "wind farm",
414
- "windmill",
415
- "wine cellar barrel storage",
416
- "wine cellar bottle storage",
417
- "wrestling ring indoor",
418
- "yard",
419
- "youth hostel",
420
- ]
421
-
422
- clip_templates = [
423
- lambda c: f"a photo of a {c}.",
424
- lambda c: f"a photo of the {c}.",
425
- ]
426
-
427
- def _info(self):
428
- return datasets.DatasetInfo(
429
- description="SUN397 dataset for image classification.",
430
- features=datasets.Features(
431
- {
432
- "image": datasets.Image(),
433
- "label": datasets.ClassLabel(names=self.classnames),
434
- }
435
- ),
436
- supervised_keys=("image", "label"),
437
- task_templates=[datasets.ImageClassification(image_column="image", label_column="label")],
438
- )