GIS
Datasets
All datasets matching “GIS”geospatialPACE-Water-QualityWHU-Building-Dataset
WHU Building Dataset
The WHU Building Dataset is a widely-used benchmark for building extraction from high-resolution aerial imagery. It contains aerial images at 0.3m resolution with pixel-level binary building masks.
Dataset Description
Property
Value
Resolution
0.3m ground sampling distance
Tile Size
512 x 512 pixels
Channels
3 (RGB)
Classes
2 (Background=0, Building=255)
Format
PNG
Splits
Split
Images
Masks… See the full description on the dataset page: https://huggingface.co/datasets/giswqs/WHU-Building-Dataset.dataset_gise_full_v1cqadupstack-gis
CQADupstackGisRetrieval
An MTEB dataset
Massive Text Embedding Benchmark
CQADupStack: A Benchmark Data Set for Community Question-Answering Research
Task category
t2t
Domains
Written, Non-fiction
Reference
http://nlp.cis.unimelb.edu.au/resources/cqadupstack/
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_tasks(["CQADupstackGisRetrieval"])
evaluator =… See the full description on the dataset page: https://huggingface.co/datasets/mteb/cqadupstack-gis.gist1m
GIST1M Vector Search Dataset
1 million 960-dimensional vectors from the GIST descriptor dataset.
Dataset Details
Vectors: 1,000,000
Dimensions: 960
Queries: 1,000
Source: ANN Benchmarks
Shard Configurations
Config
Shards
Vectors/Shard
.indices
.vectors
shard_3
3
333,333
651MB
1.2GB
shard_5
5
200,000
391MB
732MB
shard_7
7
142,857
279MB
523MB
shard_10
10
100,000
195MB
366MB
DiskANN Parameters
R: 64, L: 100, Distance: L2… See the full description on the dataset page: https://huggingface.co/datasets/maknee/gist1m.