Datasets:
Commit
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732a8b6
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Parent(s):
06e7bf3
clean loading script
Browse files- dataset_infos.json +1 -1
- yalt_ai_tabular_dataset.py +4 -13
dataset_infos.json
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{"default": {"description": "TODO", "citation": " @dataset{clerice_thibault_2022_6827706,\n author = {Cl\u00e9rice, Thibault},\n title = {YALTAi: Tabular Dataset},\n month = jul,\n year = 2022,\n publisher = {Zenodo},\n version = {1.0.0},\n doi = {10.5281/zenodo.6827706},\n url = {https://doi.org/10.5281/zenodo.6827706}\n}\n", "homepage": "https://doi.org/10.5281/zenodo.6827706", "license": "Creative Commons Attribution 4.0 International", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "objects": {"feature": {"label": {"num_classes": 4, "names": ["Header", "Col", "Marginal", "text"], "id": null, "_type": "ClassLabel"}, "bbox": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": 4, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "yalt_ai_tabular_dataset", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 60704, "num_examples": 196, "dataset_name": "yalt_ai_tabular_dataset"}, "validation": {"name": "validation", "num_bytes": 7537, "num_examples": 22, "dataset_name": "yalt_ai_tabular_dataset"}, "test": {"name": "test", "num_bytes": 47159, "num_examples": 135, "dataset_name": "yalt_ai_tabular_dataset"}}, "download_checksums": {"https://zenodo.org/record/6827706/files/yaltai-table.zip?download=1": {"num_bytes": 376190064, "checksum": "5b312faf097939302fb98ab0a8b35c007962d88978ea9dc28d2f560b89dc0657"}}, "download_size": 376190064, "post_processing_size": null, "dataset_size": 115400, "size_in_bytes": 376305464}, "YOLO": {"description": "
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{"default": {"description": "TODO", "citation": " @dataset{clerice_thibault_2022_6827706,\n author = {Cl\u00e9rice, Thibault},\n title = {YALTAi: Tabular Dataset},\n month = jul,\n year = 2022,\n publisher = {Zenodo},\n version = {1.0.0},\n doi = {10.5281/zenodo.6827706},\n url = {https://doi.org/10.5281/zenodo.6827706}\n}\n", "homepage": "https://doi.org/10.5281/zenodo.6827706", "license": "Creative Commons Attribution 4.0 International", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "objects": {"feature": {"label": {"num_classes": 4, "names": ["Header", "Col", "Marginal", "text"], "id": null, "_type": "ClassLabel"}, "bbox": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": 4, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "yalt_ai_tabular_dataset", "config_name": "default", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 60704, "num_examples": 196, "dataset_name": "yalt_ai_tabular_dataset"}, "validation": {"name": "validation", "num_bytes": 7537, "num_examples": 22, "dataset_name": "yalt_ai_tabular_dataset"}, "test": {"name": "test", "num_bytes": 47159, "num_examples": 135, "dataset_name": "yalt_ai_tabular_dataset"}}, "download_checksums": {"https://zenodo.org/record/6827706/files/yaltai-table.zip?download=1": {"num_bytes": 376190064, "checksum": "5b312faf097939302fb98ab0a8b35c007962d88978ea9dc28d2f560b89dc0657"}}, "download_size": 376190064, "post_processing_size": null, "dataset_size": 115400, "size_in_bytes": 376305464}, "YOLO": {"description": "Yalt AI Tabular Dataset", "citation": " @dataset{clerice_thibault_2022_6827706,\n author = {Cl\u00e9rice, Thibault},\n title = {YALTAi: Tabular Dataset},\n month = jul,\n year = 2022,\n publisher = {Zenodo},\n version = {1.0.0},\n doi = {10.5281/zenodo.6827706},\n url = {https://doi.org/10.5281/zenodo.6827706}\n}\n", "homepage": "https://doi.org/10.5281/zenodo.6827706", "license": "Creative Commons Attribution 4.0 International", "features": {"image": {"decode": true, "id": null, "_type": "Image"}, "objects": {"feature": {"label": {"num_classes": 4, "names": ["Header", "Col", "Marginal", "text"], "id": null, "_type": "ClassLabel"}, "bbox": {"feature": {"dtype": "int32", "id": null, "_type": "Value"}, "length": 4, "id": null, "_type": "Sequence"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "yalt_ai_tabular_dataset", "config_name": "YOLO", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 60704, "num_examples": 196, "dataset_name": "yalt_ai_tabular_dataset"}, "validation": {"name": "validation", "num_bytes": 7537, "num_examples": 22, "dataset_name": "yalt_ai_tabular_dataset"}, "test": {"name": "test", "num_bytes": 47159, "num_examples": 135, "dataset_name": "yalt_ai_tabular_dataset"}}, "download_checksums": {"https://zenodo.org/record/6827706/files/yaltai-table.zip?download=1": {"num_bytes": 376190064, "checksum": "5b312faf097939302fb98ab0a8b35c007962d88978ea9dc28d2f560b89dc0657"}}, "download_size": 376190064, "post_processing_size": null, "dataset_size": 115400, "size_in_bytes": 376305464}, "COCO": {"description": "Yalt AI Tabular Dataset", "citation": " @dataset{clerice_thibault_2022_6827706,\n author = {Cl\u00e9rice, Thibault},\n title = {YALTAi: Tabular Dataset},\n month = jul,\n year = 2022,\n publisher = {Zenodo},\n version = {1.0.0},\n doi = {10.5281/zenodo.6827706},\n url = {https://doi.org/10.5281/zenodo.6827706}\n}\n", "homepage": "https://doi.org/10.5281/zenodo.6827706", "license": "Creative Commons Attribution 4.0 International", "features": {"image_id": {"dtype": "int64", "id": null, "_type": "Value"}, "image": {"decode": true, "id": null, "_type": "Image"}, "width": {"dtype": "int32", "id": null, "_type": "Value"}, "height": {"dtype": "int32", "id": null, "_type": "Value"}, "objects": [{"category_id": {"num_classes": 4, "names": ["Header", "Col", "Marginal", "text"], "id": null, "_type": "ClassLabel"}, "image_id": {"dtype": "string", "id": null, "_type": "Value"}, "id": {"dtype": "int64", "id": null, "_type": "Value"}, "area": {"dtype": "int64", "id": null, "_type": "Value"}, "bbox": {"feature": {"dtype": "float32", "id": null, "_type": "Value"}, "length": 4, "id": null, "_type": "Sequence"}, "segmentation": [[{"dtype": "float32", "id": null, "_type": "Value"}]], "iscrowd": {"dtype": "bool", "id": null, "_type": "Value"}}]}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "yalt_ai_tabular_dataset", "config_name": "COCO", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 87171, "num_examples": 196, "dataset_name": "yalt_ai_tabular_dataset"}, "validation": {"name": "validation", "num_bytes": 11225, "num_examples": 22, "dataset_name": "yalt_ai_tabular_dataset"}, "test": {"name": "test", "num_bytes": 71491, "num_examples": 135, "dataset_name": "yalt_ai_tabular_dataset"}}, "download_checksums": {"https://zenodo.org/record/6827706/files/yaltai-table.zip?download=1": {"num_bytes": 376190064, "checksum": "5b312faf097939302fb98ab0a8b35c007962d88978ea9dc28d2f560b89dc0657"}}, "download_size": 376190064, "post_processing_size": null, "dataset_size": 169887, "size_in_bytes": 376359951}}
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yalt_ai_tabular_dataset.py
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# Copyright
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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import os
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from glob import glob
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from re import L
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import datasets
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from PIL import Image
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}
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"""
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_DESCRIPTION = """
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_HOMEPAGE = "https://doi.org/10.5281/zenodo.6827706"
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"image": datasets.Image(),
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"width": datasets.Value("int32"),
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"height": datasets.Value("int32"),
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# "url": datasets.Value("string"),
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}
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)
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object_dict = {
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if self.config.name == "YOLO":
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features = datasets.Features(
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{
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# "image_id": datasets.Value("int32"),
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"image": datasets.Image(),
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"objects": datasets.Sequence(
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{
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):
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image_id = idx
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annotations = []
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image = Image.open(image_path) #
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w, h = image.size
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with open(label_path, "r") as f:
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lines = f.readlines()
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for line in lines:
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line = line.strip().split()
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category_id = line[
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0
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] # int(line[0]) + 1 # you start with annotation id with '1'
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x_center = float(line[1])
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y_center = float(line[2])
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width = float(line[3])
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image_id,
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category_id,
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image_id,
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# segmentation=opt.box2seg,
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)
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annotations.append(annotation)
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# annotation_id += 1
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# image_id += 1 # if you finished annotation work, updates the image id.
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example = {
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"image_id": image_id,
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"image": image,
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# Copyright 2022 The HuggingFace Datasets Authors and the current dataset script contributor.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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import os
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from glob import glob
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import datasets
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from PIL import Image
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}
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"""
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_DESCRIPTION = """Yalt AI Tabular Dataset"""
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_HOMEPAGE = "https://doi.org/10.5281/zenodo.6827706"
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"image": datasets.Image(),
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"width": datasets.Value("int32"),
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"height": datasets.Value("int32"),
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}
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)
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object_dict = {
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if self.config.name == "YOLO":
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features = datasets.Features(
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{
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"image": datasets.Image(),
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"objects": datasets.Sequence(
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{
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):
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image_id = idx
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annotations = []
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image = Image.open(image_path) # Possibly conver to RGB?
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w, h = image.size
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with open(label_path, "r") as f:
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lines = f.readlines()
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for line in lines:
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line = line.strip().split()
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category_id = line[0]
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x_center = float(line[1])
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y_center = float(line[2])
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width = float(line[3])
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image_id,
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category_id,
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image_id,
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)
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annotations.append(annotation)
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example = {
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"image_id": image_id,
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"image": image,
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