Datasets:
Stavros Niafas
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edit readme
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README.md
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@@ -36,10 +36,10 @@ dataset_info:
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1: '1'
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splits:
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- name: train
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num_bytes:
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num_examples: 1200
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download_size: 39731200
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dataset_size:
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---
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## Dataset Summary
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1: '1'
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splits:
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- name: train
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num_bytes: 192150
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num_examples: 1200
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download_size: 39731200
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dataset_size: 192150
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---
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## Dataset Summary
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dof.py
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# limitations under the License.
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"""The depth-of-field dataset"""
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import
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import datasets
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from datasets.tasks import ImageClassification
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@@ -62,22 +61,21 @@ class DoF(datasets.GeneratorBasedBuilder):
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)
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def _split_generators(self, dl_manager):
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-
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"images": dl_manager.
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},
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)
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]
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def _generate_examples(self, images):
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"""Generate images and labels for splits."""
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for file_path
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-
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label = file_path.split("/")[0]
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yield file_path, {
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"image": {"path": file_path, "
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"label": label,
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}
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# limitations under the License.
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"""The depth-of-field dataset"""
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from PIL import Image
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import datasets
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from datasets.tasks import ImageClassification
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)
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def _split_generators(self, dl_manager):
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images_path = dl_manager.download_and_extract(_URL)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"images": dl_manager.iter_files(images_path),
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},
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)
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]
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def _generate_examples(self, images):
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"""Generate images and labels for splits."""
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for file_path in images:
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label = file_path.split("/")[-2:][0]
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yield file_path, {
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"image": {"path": file_path, "image": Image.open(file_path)},
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"label": label,
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}
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