Datasets:
Tasks:
Image Classification
Sub-tasks:
multi-class-image-classification
Languages:
English
Size:
1K<n<10K
Tags:
biology
License:
fix tipo in dataset
Browse files- README.md +12 -11
- bird-species-dataset.py +13 -10
README.md
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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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dtype: image
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- name: test
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num_bytes: 123269
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num_examples: 2625
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download_size:
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dataset_size: 4474183
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language:
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- en
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license: cc0-1.0
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size_categories:
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- 1K<n<10K
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task_categories:
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- image-classification
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pretty_name: Bird Species
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tags:
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- biology
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---
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# Dataset Card for "Bird Species"
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---
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language:
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- en
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license: cc0-1.0
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size_categories:
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- 1K<n<10K
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task_categories:
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- image-classification
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pretty_name: Bird Species
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tags:
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- biology
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dataset_info:
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config_name: bird_species_dataset
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features:
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- name: image
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dtype: image
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- name: test
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num_bytes: 123269
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num_examples: 2625
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download_size: 4474183
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dataset_size: 4474183
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---
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# Dataset Card for "Bird Species"
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bird-species-dataset.py
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import os
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import datasets
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from datasets import SplitGenerator, Split, ImageClassification
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from kaggle.api.kaggle_api_extended import KaggleApi
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_CITATION = """\
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@TECHREPORT{gpiosenka/100-bird-species,
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_DATA_DIR = 'data/'
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def _CLASSES() -> list[str]:
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# reads from bird_labels.txt, line by line
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with open("birds_labels.txt") as f:
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return f.read().splitlines()
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class
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-
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def _info(self):
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_NAMES = _CLASSES()
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@@ -48,6 +57,7 @@ class BirdSpeciesDatasetDataset(datasets.GeneratorBasedBuilder):
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data_dir = _DATA_DIR
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# Downloading the dataset
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if not os.path.exists(data_dir):
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kaggle_api = KaggleApi()
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kaggle_api.authenticate()
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kaggle_api.dataset_download_files('gpiosenka/100-bird-species', path=data_dir, unzip=True)
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}
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yield idx, record
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idx += 1
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-
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# To use the dataset:
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# from datasets import load_dataset
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# dataset = load_dataset('path/to/birds.py')
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import os
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import datasets
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from datasets import SplitGenerator, Split, ImageClassification
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_CITATION = """\
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@TECHREPORT{gpiosenka/100-bird-species,
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_DATA_DIR = 'data/'
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_VERSION = "0.1.0"
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def _CLASSES() -> list[str]:
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# reads from bird_labels.txt, line by line
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with open("birds_labels.txt") as f:
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return f.read().splitlines()
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class BirdSpeciesDataset(datasets.GeneratorBasedBuilder):
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"""DatasetBuilder for bird_species_dataset dataset."""
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name="bird_species_dataset",
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version=datasets.Version(_VERSION),
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description=_DESCRIPTION,
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)
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]
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def _info(self):
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_NAMES = _CLASSES()
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data_dir = _DATA_DIR
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# Downloading the dataset
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if not os.path.exists(data_dir):
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from kaggle.api.kaggle_api_extended import KaggleApi
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kaggle_api = KaggleApi()
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kaggle_api.authenticate()
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kaggle_api.dataset_download_files('gpiosenka/100-bird-species', path=data_dir, unzip=True)
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}
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yield idx, record
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idx += 1
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