draft

README.md

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+---
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: label
+    dtype:
+      class_label:
+        names:
+          '0': Ancistrus
+          '1': Apistogramma
+          '2': Astyanax
+          '3': Bario
+          '4': Bryconops
+          '5': Bujurquina
+          '6': Bunocephalus
+          '7': Characidium
+          '8': Charax
+          '9': Copella
+          '10': Corydoras
+          '11': Creagrutus
+          '12': Curimata
+          '13': Doras
+          '14': Erythrinus
+          '15': Gasteropelecus
+          '16': Gymnotus
+          '17': Hemigrammus
+          '18': Hyphessobrycon
+          '19': Knodus
+          '20': Moenkhausia
+          '21': Otocinclus
+          '22': Oxyropsis
+          '23': Phenacogaster
+          '24': Pimelodella
+          '25': Prochilodus
+          '26': Pygocentrus
+          '27': Pyrrhulina
+          '28': Rineloricaria
+          '29': Sorubim
+          '30': Tatia
+          '31': Tetragonopterus
+          '32': Tyttocharax
+  splits:
+  - name: train
+    num_bytes: 578234
+    num_examples: 3068
+  download_size: 330399200
+  dataset_size: 578234
+---

amazonian_fish_classifier.py

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+# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""TODO."""
+
+
+import os
+from pathlib import Path
+import pandas as pd
+import datasets
+
+_CITATION = """TODO"""
+
+
+_DESCRIPTION = """\
+TODO
+"""
+
+_HOMEPAGE = "https://doi.org/10.25573/data.17314730.v1"
+
+_LICENSE = "CC BY 4.0"
+
+
+_URLS = {
+    "images": "https://smithsonian.figshare.com/ndownloader/files/31975544",
+}
+
+
+class AmazonianFish(datasets.GeneratorBasedBuilder):
+    """TODO"""
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+        features = datasets.Features(
+            {
+                "image": datasets.Image(),
+                "label": datasets.ClassLabel(
+                    names=[
+                        "Ancistrus",
+                        "Apistogramma",
+                        "Astyanax",
+                        "Bario",
+                        "Bryconops",
+                        "Bujurquina",
+                        "Bunocephalus",
+                        "Characidium",
+                        "Charax",
+                        "Copella",
+                        "Corydoras",
+                        "Creagrutus",
+                        "Curimata",
+                        "Doras",
+                        "Erythrinus",
+                        "Gasteropelecus",
+                        "Gymnotus",
+                        "Hemigrammus",
+                        "Hyphessobrycon",
+                        "Knodus",
+                        "Moenkhausia",
+                        "Otocinclus",
+                        "Oxyropsis",
+                        "Phenacogaster",
+                        "Pimelodella",
+                        "Prochilodus",
+                        "Pygocentrus",
+                        "Pyrrhulina",
+                        "Rineloricaria",
+                        "Sorubim",
+                        "Tatia",
+                        "Tetragonopterus",
+                        "Tyttocharax",
+                    ]
+                ),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            homepage=_HOMEPAGE,
+            license=_LICENSE,
+            citation=_CITATION,
+        )
+
+    def _split_generators(self, dl_manager):
+        images = dl_manager.download_and_extract(_URLS["images"])
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "images": os.path.join(images,"training_images"),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, images):
+        id_ = 0
+        for example in Path(images).rglob("*.jpg"):
+            if example.name.startswith("._"):
+                continue
+            id_ += 1
+            yield id_, {"image": str(example), "label": example.parent.name}