|
--- |
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dataset_info: |
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features: |
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- name: image |
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dtype: image |
|
- name: domain |
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dtype: string |
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- name: category |
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dtype: string |
|
- name: 'y' |
|
dtype: |
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class_label: |
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names: |
|
0: aircraft_carrier |
|
1: airplane |
|
2: alarm_clock |
|
3: ambulance |
|
4: angel |
|
5: animal_migration |
|
6: ant |
|
7: anvil |
|
8: apple |
|
9: arm |
|
10: asparagus |
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11: axe |
|
12: backpack |
|
13: banana |
|
14: bandage |
|
15: barn |
|
16: baseball |
|
17: baseball_bat |
|
18: basket |
|
19: basketball |
|
20: bat |
|
21: bathtub |
|
22: beach |
|
23: bear |
|
24: beard |
|
25: bed |
|
26: bee |
|
27: belt |
|
28: bench |
|
29: bicycle |
|
30: binoculars |
|
31: bird |
|
32: birthday_cake |
|
33: blackberry |
|
34: blueberry |
|
35: book |
|
36: boomerang |
|
37: bottlecap |
|
38: bowtie |
|
39: bracelet |
|
40: brain |
|
41: bread |
|
42: bridge |
|
43: broccoli |
|
44: broom |
|
45: bucket |
|
46: bulldozer |
|
47: bus |
|
48: bush |
|
49: butterfly |
|
50: cactus |
|
51: cake |
|
52: calculator |
|
53: calendar |
|
54: camel |
|
55: camera |
|
56: camouflage |
|
57: campfire |
|
58: candle |
|
59: cannon |
|
60: canoe |
|
61: car |
|
62: carrot |
|
63: castle |
|
64: cat |
|
65: ceiling_fan |
|
66: cello |
|
67: cell_phone |
|
68: chair |
|
69: chandelier |
|
70: church |
|
71: circle |
|
72: clarinet |
|
73: clock |
|
74: cloud |
|
75: coffee_cup |
|
76: compass |
|
77: computer |
|
78: cookie |
|
79: cooler |
|
80: couch |
|
81: cow |
|
82: crab |
|
83: crayon |
|
84: crocodile |
|
85: crown |
|
86: cruise_ship |
|
87: cup |
|
88: diamond |
|
89: dishwasher |
|
90: diving_board |
|
91: dog |
|
92: dolphin |
|
93: donut |
|
94: door |
|
95: dragon |
|
96: dresser |
|
97: drill |
|
98: drums |
|
99: duck |
|
100: dumbbell |
|
101: ear |
|
102: elbow |
|
103: elephant |
|
104: envelope |
|
105: eraser |
|
106: eye |
|
107: eyeglasses |
|
108: face |
|
109: fan |
|
110: feather |
|
111: fence |
|
112: finger |
|
113: fire_hydrant |
|
114: fireplace |
|
115: firetruck |
|
116: fish |
|
117: flamingo |
|
118: flashlight |
|
119: flip_flops |
|
120: floor_lamp |
|
121: flower |
|
122: flying_saucer |
|
123: foot |
|
124: fork |
|
125: frog |
|
126: frying_pan |
|
127: garden |
|
128: garden_hose |
|
129: giraffe |
|
130: goatee |
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131: golf_club |
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132: grapes |
|
133: grass |
|
134: guitar |
|
135: hamburger |
|
136: hammer |
|
137: hand |
|
138: harp |
|
139: hat |
|
140: headphones |
|
141: hedgehog |
|
142: helicopter |
|
143: helmet |
|
144: hexagon |
|
145: hockey_puck |
|
146: hockey_stick |
|
147: horse |
|
148: hospital |
|
149: hot_air_balloon |
|
150: hot_dog |
|
151: hot_tub |
|
152: hourglass |
|
153: house |
|
154: house_plant |
|
155: hurricane |
|
156: ice_cream |
|
157: jacket |
|
158: jail |
|
159: kangaroo |
|
160: key |
|
161: keyboard |
|
162: knee |
|
163: knife |
|
164: ladder |
|
165: lantern |
|
166: laptop |
|
167: leaf |
|
168: leg |
|
169: light_bulb |
|
170: lighter |
|
171: lighthouse |
|
172: lightning |
|
173: line |
|
174: lion |
|
175: lipstick |
|
176: lobster |
|
177: lollipop |
|
178: mailbox |
|
179: map |
|
180: marker |
|
181: matches |
|
182: megaphone |
|
183: mermaid |
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184: microphone |
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185: microwave |
|
186: monkey |
|
187: moon |
|
188: mosquito |
|
189: motorbike |
|
190: mountain |
|
191: mouse |
|
192: moustache |
|
193: mouth |
|
194: mug |
|
195: mushroom |
|
196: nail |
|
197: necklace |
|
198: nose |
|
199: ocean |
|
200: octagon |
|
201: octopus |
|
202: onion |
|
203: oven |
|
204: owl |
|
205: paintbrush |
|
206: paint_can |
|
207: palm_tree |
|
208: panda |
|
209: pants |
|
210: paper_clip |
|
211: parachute |
|
212: parrot |
|
213: passport |
|
214: peanut |
|
215: pear |
|
216: peas |
|
217: pencil |
|
218: penguin |
|
219: piano |
|
220: pickup_truck |
|
221: picture_frame |
|
222: pig |
|
223: pillow |
|
224: pineapple |
|
225: pizza |
|
226: pliers |
|
227: police_car |
|
228: pond |
|
229: pool |
|
230: popsicle |
|
231: postcard |
|
232: potato |
|
233: power_outlet |
|
234: purse |
|
235: rabbit |
|
236: raccoon |
|
237: radio |
|
238: rain |
|
239: rainbow |
|
240: rake |
|
241: remote_control |
|
242: rhinoceros |
|
243: rifle |
|
244: river |
|
245: roller_coaster |
|
246: rollerskates |
|
247: sailboat |
|
248: sandwich |
|
249: saw |
|
250: saxophone |
|
251: school_bus |
|
252: scissors |
|
253: scorpion |
|
254: screwdriver |
|
255: sea_turtle |
|
256: see_saw |
|
257: shark |
|
258: sheep |
|
259: shoe |
|
260: shorts |
|
261: shovel |
|
262: sink |
|
263: skateboard |
|
264: skull |
|
265: skyscraper |
|
266: sleeping_bag |
|
267: smiley_face |
|
268: snail |
|
269: snake |
|
270: snorkel |
|
271: snowflake |
|
272: snowman |
|
273: soccer_ball |
|
274: sock |
|
275: speedboat |
|
276: spider |
|
277: spoon |
|
278: spreadsheet |
|
279: square |
|
280: squiggle |
|
281: squirrel |
|
282: stairs |
|
283: star |
|
284: steak |
|
285: stereo |
|
286: stethoscope |
|
287: stitches |
|
288: stop_sign |
|
289: stove |
|
290: strawberry |
|
291: streetlight |
|
292: string_bean |
|
293: submarine |
|
294: suitcase |
|
295: sun |
|
296: swan |
|
297: sweater |
|
298: swing_set |
|
299: sword |
|
300: syringe |
|
301: table |
|
302: teapot |
|
303: teddy-bear |
|
304: telephone |
|
305: television |
|
306: tennis_racquet |
|
307: tent |
|
308: The_Eiffel_Tower |
|
309: The_Great_Wall_of_China |
|
310: The_Mona_Lisa |
|
311: tiger |
|
312: toaster |
|
313: toe |
|
314: toilet |
|
315: tooth |
|
316: toothbrush |
|
317: toothpaste |
|
318: tornado |
|
319: tractor |
|
320: traffic_light |
|
321: train |
|
322: tree |
|
323: triangle |
|
324: trombone |
|
325: truck |
|
326: trumpet |
|
327: t-shirt |
|
328: umbrella |
|
329: underwear |
|
330: van |
|
331: vase |
|
332: violin |
|
333: washing_machine |
|
334: watermelon |
|
335: waterslide |
|
336: whale |
|
337: wheel |
|
338: windmill |
|
339: wine_bottle |
|
340: wine_glass |
|
341: wristwatch |
|
342: yoga |
|
343: zebra |
|
344: zigzag |
|
- name: image_path |
|
dtype: string |
|
splits: |
|
- name: train |
|
num_bytes: 1104174711.3600001 |
|
num_examples: 409832 |
|
- name: test |
|
num_bytes: 474182438.589 |
|
num_examples: 176743 |
|
download_size: 18524149098 |
|
dataset_size: 1578357149.9490001 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: train |
|
path: data/train-* |
|
- split: test |
|
path: data/test-* |
|
task_categories: |
|
- image-classification |
|
- zero-shot-image-classification |
|
task_ids: |
|
- multi-class-image-classification |
|
- multi-class-classification |
|
language: |
|
- en |
|
pretty_name: DomainNet |
|
license: other |
|
size_categories: |
|
- 100K<n<1M |
|
--- |
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|
|
Data downloaded from [WILDS](https://wilds.stanford.edu/) ([Download](https://wilds.stanford.edu/downloads), [paper](https://arxiv.org/abs/1812.01754), [project](https://ai.bu.edu/M3SDA/)). |
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This dataset contains some copyrighted material whose use has not been specifically authorized by the copyright owners. In an effort to advance scientific research, we make this material available for academic research. We believe this constitutes a fair use of any such copyrighted material as provided for in section 107 of the US Copyright Law. In accordance with Title 17 U.S.C. Section 107, the material on this site is distributed without profit for non-commercial research and educational purposes. For more information on fair use please click [here](https://www.law.cornell.edu/uscode/text/17/107). If you wish to use copyrighted material on this site or in our dataset for purposes of your own that go beyond non-commercial research and academic purposes, you must obtain permission directly from the copyright owner. (adapted from the [official DomainNet website](https://ai.bu.edu/M3SDA/#refs)) |
