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"""Graptoloidea Specimens dataset.""" |
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import os |
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import random |
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from typing import List |
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import datasets |
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import pandas as pd |
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import numpy as np |
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import csv |
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import logging |
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from PIL import Image |
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import ast |
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_CITATION = """\ |
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111 |
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""" |
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_DESCRIPTION = """\ |
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[Your dataset description here...] |
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""" |
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_HOMEPAGE = "https://zenodo.org/records/6194943" |
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_license = "111" |
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class GraptoloideaSpecimensDataset(datasets.GeneratorBasedBuilder): |
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_URL = "https://raw.githubusercontent.com/LeoZhangzaolin/photos/main/Final_GS_with_Images.csv" |
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def _info(self): |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=datasets.Features( |
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{ |
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"Suborder": datasets.Value("string"), |
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"Infraorder": datasets.Value("string"), |
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"Family (Subfamily)": datasets.Value("string"), |
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"Genus": datasets.Value("string"), |
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"Tagged Species Name": datasets.Value("string"), |
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"Image": datasets.Value("string"), |
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"Stage": datasets.Value("string"), |
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"Mean Age Value": datasets.Value("float64"), |
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"Locality (Longitude, Latitude, Horizon)": datasets.Value("string"), |
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"Reference (Specimens Firstly Published)": datasets.Value("string"), |
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} |
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), |
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supervised_keys=None, |
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homepage=_HOMEPAGE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: |
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downloaded_file = dl_manager.download_and_extract(self._URL) |
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df = pd.read_csv(downloaded_file) |
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df = df.sample(frac=1).reset_index(drop=True) |
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train_size = int(0.7 * len(df)) |
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test_size = int(0.15 * len(df)) |
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train_df = df[:train_size] |
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test_df = df[train_size:train_size + test_size] |
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validation_df = df[train_size + test_size:] |
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train_file = '/tmp/train_split.csv' |
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test_file = '/tmp/test_split.csv' |
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validation_file = '/tmp/validation_split.csv' |
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train_df.to_csv(train_file, index=False) |
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test_df.to_csv(test_file, index=False) |
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validation_df.to_csv(validation_file, index=False) |
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return [ |
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": train_file}), |
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": test_file}), |
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": validation_file}), |
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] |
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def _generate_examples(self, filepath): |
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"""This function returns the examples from the CSV file.""" |
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logging.info("generating examples from = %s", filepath) |
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with open(filepath, encoding='utf-8') as f: |
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reader = csv.DictReader(f) |
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key = 0 |
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for row in reader: |
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key += 1 |
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suborder = row['Suborder'].strip() |
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infraorder = row['Infraorder'].strip() |
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family_subfamily = row['Family (Subfamily)'].strip() |
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genus = row['Genus'].strip() |
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species_name = row['tagged species name'].strip() |
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image = row['image'].strip() |
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stage = row['Stage'].strip() |
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mean_age = row['mean age value'] |
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locality = row['Locality (Longitude, Latitude, Horizon)'].strip() |
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reference = row['Reference (specimens firstly published)'].strip() |
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yield key, { |
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"Suborder": suborder, |
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"Infraorder": infraorder, |
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"Family (Subfamily)": family_subfamily, |
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"Genus": genus, |
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"Tagged Species Name": species_name, |
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"Image": image, |
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"Stage": stage, |
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"Mean Age Value": mean_age, |
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"Locality (Longitude, Latitude, Horizon)": locality, |
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"Reference (Specimens Firstly Published)": reference, |
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} |
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