Datasets:
image
imagewidth (px) 247
257
| category
stringclasses 44
values | img_id
stringlengths 25
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desert | jonathan-roberts1/NWPU-RESISC45/train/8682 |
|
chaparral | jonathan-roberts1/NWPU-RESISC45/train/4689 |
|
cloud | jonathan-roberts1/NWPU-RESISC45/train/6807 |
|
intersection | jonathan-roberts1/NWPU-RESISC45/train/13698 |
|
commercial area | jonathan-roberts1/NWPU-RESISC45/train/7165 |
|
mountain | jonathan-roberts1/NWPU-RESISC45/train/17693 |
|
basketball court | jonathan-roberts1/NWPU-RESISC45/train/2424 |
|
stadium | jonathan-roberts1/NWPU-RESISC45/train/27833 |
|
bridge | jonathan-roberts1/NWPU-RESISC45/train/3983 |
|
meadow | jonathan-roberts1/NWPU-RESISC45/train/15948 |
|
residential | jonathan-roberts1/NWPU-RESISC45/train/16588 |
|
ground track field | jonathan-roberts1/NWPU-RESISC45/train/11291 |
|
thermal power station | jonathan-roberts1/NWPU-RESISC45/train/30401 |
|
snowberg | jonathan-roberts1/NWPU-RESISC45/train/26393 |
|
intersection | jonathan-roberts1/NWPU-RESISC45/train/13600 |
|
thermal power station | jonathan-roberts1/NWPU-RESISC45/train/30477 |
|
golf course | jonathan-roberts1/NWPU-RESISC45/train/11085 |
|
church | jonathan-roberts1/NWPU-RESISC45/train/5339 |
|
stadium | jonathan-roberts1/NWPU-RESISC45/train/27450 |
|
storage tanks | jonathan-roberts1/NWPU-RESISC45/train/28329 |
|
commercial area | jonathan-roberts1/NWPU-RESISC45/train/7024 |
|
commercial area | jonathan-roberts1/NWPU-RESISC45/train/7201 |
|
harbor | jonathan-roberts1/NWPU-RESISC45/train/12570 |
|
ship | jonathan-roberts1/NWPU-RESISC45/train/25405 |
|
forest | jonathan-roberts1/NWPU-RESISC45/train/9520 |
|
parking lot | jonathan-roberts1/NWPU-RESISC45/train/20279 |
|
buildings | torchgeo/ucmerced/train/430 |
|
river | jonathan-roberts1/NWPU-RESISC45/train/23073 |
|
storage tanks | jonathan-roberts1/NWPU-RESISC45/train/28032 |
|
chaparral | torchgeo/ucmerced/train/538 |
|
sea ice | jonathan-roberts1/NWPU-RESISC45/train/24704 |
|
residential | jonathan-roberts1/NWPU-RESISC45/train/8107 |
|
freeway | torchgeo/ucmerced/train/865 |
|
airplane | jonathan-roberts1/NWPU-RESISC45/train/203 |
|
circular farmland | jonathan-roberts1/NWPU-RESISC45/train/5909 |
|
overpass | jonathan-roberts1/NWPU-RESISC45/train/18476 |
|
church | jonathan-roberts1/NWPU-RESISC45/train/4986 |
|
snowberg | jonathan-roberts1/NWPU-RESISC45/train/26327 |
|
sea ice | jonathan-roberts1/NWPU-RESISC45/train/24978 |
|
industrial area | jonathan-roberts1/NWPU-RESISC45/train/13038 |
|
railway station | jonathan-roberts1/NWPU-RESISC45/train/21667 |
|
residential | jonathan-roberts1/NWPU-RESISC45/train/17165 |
|
church | jonathan-roberts1/NWPU-RESISC45/train/4990 |
|
railway station | jonathan-roberts1/NWPU-RESISC45/train/21521 |
|
basketball court | jonathan-roberts1/NWPU-RESISC45/train/2539 |
|
basketball court | jonathan-roberts1/NWPU-RESISC45/train/2519 |
|
wetland | jonathan-roberts1/NWPU-RESISC45/train/31187 |
|
commercial area | jonathan-roberts1/NWPU-RESISC45/train/7580 |
|
sea ice | jonathan-roberts1/NWPU-RESISC45/train/25091 |
|
sea ice | jonathan-roberts1/NWPU-RESISC45/train/25043 |
|
residential | torchgeo/ucmerced/train/659 |
|
island | jonathan-roberts1/NWPU-RESISC45/train/14155 |
|
residential | jonathan-roberts1/NWPU-RESISC45/train/27200 |
|
baseball diamond | jonathan-roberts1/NWPU-RESISC45/train/1622 |
|
golf course | jonathan-roberts1/NWPU-RESISC45/train/11127 |
|
freeway | jonathan-roberts1/NWPU-RESISC45/train/10436 |
|
commercial area | jonathan-roberts1/NWPU-RESISC45/train/7594 |
|
airport | jonathan-roberts1/NWPU-RESISC45/train/815 |
|
airplane | jonathan-roberts1/NWPU-RESISC45/train/114 |
|
freeway | jonathan-roberts1/NWPU-RESISC45/train/10056 |
|
river | jonathan-roberts1/NWPU-RESISC45/train/22937 |
|
overpass | jonathan-roberts1/NWPU-RESISC45/train/18414 |
|
thermal power station | jonathan-roberts1/NWPU-RESISC45/train/30655 |
|
commercial area | jonathan-roberts1/NWPU-RESISC45/train/7690 |
|
circular farmland | jonathan-roberts1/NWPU-RESISC45/train/5802 |
|
ground track field | jonathan-roberts1/NWPU-RESISC45/train/11254 |
|
tennis court | torchgeo/ucmerced/train/2043 |
|
roundabout | jonathan-roberts1/NWPU-RESISC45/train/23647 |
|
sea ice | jonathan-roberts1/NWPU-RESISC45/train/25182 |
|
thermal power station | jonathan-roberts1/NWPU-RESISC45/train/30301 |
|
palace | jonathan-roberts1/NWPU-RESISC45/train/19045 |
|
forest | jonathan-roberts1/NWPU-RESISC45/train/9526 |
|
intersection | jonathan-roberts1/NWPU-RESISC45/train/13770 |
|
palace | jonathan-roberts1/NWPU-RESISC45/train/18907 |
|
cloud | jonathan-roberts1/NWPU-RESISC45/train/6685 |
|
lake | jonathan-roberts1/NWPU-RESISC45/train/14776 |
|
harbor | jonathan-roberts1/NWPU-RESISC45/train/12261 |
|
meadow | jonathan-roberts1/NWPU-RESISC45/train/15770 |
|
island | jonathan-roberts1/NWPU-RESISC45/train/14154 |
|
sea ice | jonathan-roberts1/NWPU-RESISC45/train/25147 |
|
roundabout | jonathan-roberts1/NWPU-RESISC45/train/23526 |
|
residential | torchgeo/ucmerced/train/1253 |
|
residential | jonathan-roberts1/NWPU-RESISC45/train/27041 |
|
beach | torchgeo/ucmerced/train/397 |
|
tennis court | jonathan-roberts1/NWPU-RESISC45/train/29035 |
|
church | jonathan-roberts1/NWPU-RESISC45/train/5155 |
|
roundabout | jonathan-roberts1/NWPU-RESISC45/train/23551 |
|
airplane | jonathan-roberts1/NWPU-RESISC45/train/246 |
|
mountain | jonathan-roberts1/NWPU-RESISC45/train/18048 |
|
airplane | jonathan-roberts1/NWPU-RESISC45/train/548 |
|
thermal power station | jonathan-roberts1/NWPU-RESISC45/train/30122 |
|
sea ice | jonathan-roberts1/NWPU-RESISC45/train/25014 |
|
storage tanks | jonathan-roberts1/NWPU-RESISC45/train/28616 |
|
residential | jonathan-roberts1/NWPU-RESISC45/train/16763 |
|
circular farmland | jonathan-roberts1/NWPU-RESISC45/train/5678 |
|
golf course | torchgeo/ucmerced/train/935 |
|
harbor | jonathan-roberts1/NWPU-RESISC45/train/11939 |
|
bridge | jonathan-roberts1/NWPU-RESISC45/train/4148 |
|
residential | jonathan-roberts1/NWPU-RESISC45/train/16454 |
|
ship | jonathan-roberts1/NWPU-RESISC45/train/25199 |
Dataset Card for Merged Remote Landscapes dataset
Dataset summary
This is a merged version of following datasets:
from datasets import load_dataset
dataset = load_dataset('EmbeddingStudio/merged_remote_landscapes_v1')
Categories
This is a union of categories from original datasets: agricultural, airplane, airport, baseball diamond, basketball court, beach, bridge, buildings, chaparral, church, circular farmland, cloud, commercial area, desert, forest, freeway, golf course, ground track field, harbor, industrial area, intersection, island, lake, meadow, mountain, overpass, palace, parking lot, railway, railway station, rectangular farmland, residential, river, roundabout, runway, sea ice, ship, snowberg, stadium, storage tanks, tennis court, terrace, thermal power station, wetland
Warning: Synonymous and ambiguous categories were combined (see "Merge method").
Motivation
EmbeddingStudio is the open-source framework, that allows you transform a joint "Embedding Model + Vector DB" into a full-cycle search engine: collect clickstream -> improve search experience-> adapt embedding model and repeat out of the box.
In the development of EmbeddingStudio the scientific approach is a backbone. On the early stage of the development we can't collect real clickstream data, so to do experiments and choose the best way to improve embedding model we had to use synthetic or emulated data. And the first step is to use the most transparent datasets and the easiest domain.
P.S. this dataset is tagged to be used for the image classification task, but in fact we use it for the metric learning task. And we do another step to emulate clickstream.
We provide this dataset on HuggingFace, so anyone can reproduce our results.
Check our repositories to get more details:
- EmbeddingStudio Framework (coming soon at 22.12.2023)
- Experiments (coming soon)
Merge method
For this type of dataset it's all simple:
- Remove duplicates.
- Resolve synonymous and ambiguous categories with using a simple map (CATEGORIES_MAPPING).
CATEGORIES_MAPPING = {
"dense residential": "residential",
"medium residential": "residential",
"mobile home park": "residential",
"sparse residential": "residential",
"storage tank": "storage tanks",
"storage tanks": "storage tanks",
}
All details and code base of merging algorithm will be provided in our experiments repository. If you have any suggestion or you find some mistakes, we will be happy to fix it, so our experimental data will have better quality.
Contact info
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