Datasets:
Tasks:
Image Classification
Modalities:
Image
Formats:
parquet
Languages:
English
Size:
10K - 100K
ArXiv:
Convert dataset to Parquet
#1
by
tanganke
- opened
- README.md +38 -17
- data/{contrast.zip → contrast-00000-of-00001.parquet} +2 -2
- data/{gaussian_noise.zip → gaussian_noise-00000-of-00001.parquet} +2 -2
- data/{impulse_noise.zip → impulse_noise-00000-of-00001.parquet} +2 -2
- data/{jpeg_compression.zip → jpeg_compression-00000-of-00001.parquet} +2 -2
- data/motion_blur-00000-of-00001.parquet +3 -0
- data/motion_blur.zip +0 -3
- data/pixelate-00000-of-00001.parquet +3 -0
- data/pixelate.zip +0 -3
- data/spatter-00000-of-00001.parquet +3 -0
- data/spatter.zip +0 -3
- data/test-00000-of-00001.parquet +3 -0
- data/test.zip +0 -3
- data/train-00000-of-00001.parquet +3 -0
- data/train.zip +0 -3
- eurosat.py +0 -58
README.md
CHANGED
@@ -1,4 +1,10 @@
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---
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dataset_info:
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features:
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- name: image
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@@ -19,40 +25,55 @@ dataset_info:
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'9': lake or sea
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splits:
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- name: train
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num_bytes:
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num_examples: 21600
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- name: test
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-
num_bytes:
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num_examples: 2700
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- name: contrast
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-
num_bytes:
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num_examples: 2700
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- name: gaussian_noise
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num_bytes:
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num_examples: 2700
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- name: impulse_noise
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num_bytes:
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num_examples: 2700
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- name: jpeg_compression
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-
num_bytes:
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num_examples: 2700
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- name: motion_blur
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-
num_bytes:
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num_examples: 2700
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- name: pixelate
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-
num_bytes:
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num_examples: 2700
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- name: spatter
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num_bytes:
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num_examples: 2700
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download_size:
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dataset_size:
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-
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-
-
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---
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---
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language:
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- en
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size_categories:
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- 10K<n<100K
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task_categories:
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- image-classification
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dataset_info:
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features:
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- name: image
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'9': lake or sea
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splits:
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- name: train
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num_bytes: 70654720.8
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num_examples: 21600
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- name: test
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num_bytes: 8626053.5
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num_examples: 2700
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- name: contrast
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num_bytes: 2577694.4
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num_examples: 2700
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- name: gaussian_noise
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num_bytes: 4344552.8
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num_examples: 2700
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- name: impulse_noise
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num_bytes: 4551961.4
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num_examples: 2700
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- name: jpeg_compression
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num_bytes: 2879624.6
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num_examples: 2700
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- name: motion_blur
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num_bytes: 2881150.1
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num_examples: 2700
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- name: pixelate
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num_bytes: 2114682.2
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num_examples: 2700
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- name: spatter
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num_bytes: 4174215.2
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num_examples: 2700
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download_size: 98645265
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dataset_size: 102804655.0
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: test
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path: data/test-*
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- split: contrast
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path: data/contrast-*
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- split: gaussian_noise
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path: data/gaussian_noise-*
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- split: impulse_noise
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path: data/impulse_noise-*
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- split: jpeg_compression
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path: data/jpeg_compression-*
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- split: motion_blur
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path: data/motion_blur-*
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- split: pixelate
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path: data/pixelate-*
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- split: spatter
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path: data/spatter-*
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---
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data/{contrast.zip → contrast-00000-of-00001.parquet}
RENAMED
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:248543ce5fb9ffcfae41af7579240d55d195f93900b2d6f70c1679147bd1c957
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size 1414683
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data/{gaussian_noise.zip → gaussian_noise-00000-of-00001.parquet}
RENAMED
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:0012b4457effae36ec9ef14874faff8c4b182e08dad16ab691bee071250c532d
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size 3379572
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data/{impulse_noise.zip → impulse_noise-00000-of-00001.parquet}
RENAMED
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:96b6850aee61193386597cf11a2b5cc98b7f70308b67007f35fcefe3b717d6e5
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size 3602617
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data/{jpeg_compression.zip → jpeg_compression-00000-of-00001.parquet}
RENAMED
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version https://git-lfs.github.com/spec/v1
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oid sha256:
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size
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version https://git-lfs.github.com/spec/v1
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size 1827382
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data/motion_blur-00000-of-00001.parquet
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:925da9da5a5fe5a61d1d6de62c3276feeaa58676e9b48ab372237694d2251c8b
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size 1771787
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data/motion_blur.zip
DELETED
@@ -1,3 +0,0 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:d27fbf4e4f8f123febeb915df4ee65ec67917c4141174413274c4f1e022bb9b9
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size 3465104
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data/pixelate-00000-of-00001.parquet
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:59c7758bb0369ad9cf717e083ff33c92783f638432170b415b18a5be3062d5ae
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size 765724
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data/pixelate.zip
DELETED
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version https://git-lfs.github.com/spec/v1
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oid sha256:271334e75cce92eef9a1bd5498cab4ac7031dcb3a38fce61d8871a2831394ada
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size 2503369
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data/spatter-00000-of-00001.parquet
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:fe490a7564bdd93276baa46f8271df0e963d7810f9506187fb56d57e3f5827b9
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size 3215883
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data/spatter.zip
DELETED
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version https://git-lfs.github.com/spec/v1
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oid sha256:01ca43ad933878014bd283eccfb0d8731c08306aa86acc48120e5c4effd710c2
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size 4767237
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data/test-00000-of-00001.parquet
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:815d6c3b86d277dbc3164961936ba47ea0f4b4bafd59059fe93f7cd473cd5044
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size 9134700
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data/test.zip
DELETED
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version https://git-lfs.github.com/spec/v1
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oid sha256:16a5ca861583acb87c8b5b5ceeb5dae0b4f712d865bd0368070870f5a168e873
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size 9634576
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data/train-00000-of-00001.parquet
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:27f28503c24d6fd64432c25825de0621853d3b04e2881be78748555289902656
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size 73532917
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data/train.zip
DELETED
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version https://git-lfs.github.com/spec/v1
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oid sha256:ece9c02ec765c2a916f779d5777d85876258e47a0d9363af444cd6c42182f506
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size 77655061
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eurosat.py
DELETED
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import datasets
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from datasets.data_files import DataFilesDict
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from datasets.packaged_modules.imagefolder.imagefolder import ImageFolder, ImageFolderConfig
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logger = datasets.logging.get_logger(__name__)
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class EuroSAT(ImageFolder):
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R"""
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EuroSAT dataset for image classification.
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"""
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BUILDER_CONFIG_CLASS = ImageFolderConfig
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BUILDER_CONFIGS = [
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ImageFolderConfig(
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name="default",
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features=("images", "labels"),
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data_files=DataFilesDict(
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{
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split: f"data/{split}.zip"
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for split in ["train", "test"]
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+ ["contrast", "gaussian_noise", "impulse_noise", "jpeg_compression", "motion_blur", "pixelate", "spatter"]
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}
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),
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)
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]
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classnames = [
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"annual crop land",
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"forest",
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"brushland or shrubland",
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"highway or road",
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"industrial buildings or commercial buildings",
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"pasture land",
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"permanent crop land",
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"residential buildings or homes or apartments",
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"river",
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"lake or sea",
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]
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clip_templates = [
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lambda c: f"a centered satellite photo of {c}.",
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lambda c: f"a centered satellite photo of a {c}.",
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lambda c: f"a centered satellite photo of the {c}.",
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]
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def _info(self):
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return datasets.DatasetInfo(
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description="EuroSAT dataset for image classification.",
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features=datasets.Features(
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{
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"image": datasets.Image(),
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"label": datasets.ClassLabel(names=self.classnames),
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}
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),
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supervised_keys=("image", "label"),
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task_templates=[datasets.ImageClassification(image_column="image", label_column="label")],
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)
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