refactor

README.md

@@ -44,6 +44,6 @@ dataset_info:
   - name: train
     num_bytes: 578234
     num_examples: 3068
-  download_size: 330399200
+  download_size: 330476983
   dataset_size: 578234
 ---

amazonian_fish_classifier_data.py

@@ -13,8 +13,9 @@
 # limitations under the License.
 """TODO."""
 
+
 import os
-from pathlib import Path
+import pandas as pd
 import datasets
 
 _CITATION = """TODO"""
@@ -24,13 +25,14 @@ _DESCRIPTION = """\
 TODO
 """
 
-_HOMEPAGE = "https://doi.org/10.25573/data.17314730.v1" 
+_HOMEPAGE = "https://doi.org/10.25573/data.17314730.v1"
 
 _LICENSE = "CC BY 4.0"
 
 
 _URLS = {
     "images": "https://smithsonian.figshare.com/ndownloader/files/31975544",
+    "labels": "https://smithsonian.figshare.com/ndownloader/files/31975646",
 }
 
 
@@ -93,19 +95,22 @@ class AmazonianFish(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         images = dl_manager.download_and_extract(_URLS["images"])
+        labels = dl_manager.download(_URLS["labels"])
+        df = pd.read_csv(labels)
+        labels = df.to_dict(orient="records")
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
                     "images": os.path.join(images, "training_images"),
+                    "labels": labels,
                 },
             ),
         ]
 
-    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}
+    def _generate_examples(self, images, labels):
+        for id_, example in enumerate(labels):
+            yield id_, {
+                "image": os.path.join(images, example["Genus"], example["Image_name"]),
+                "label": example["Genus"],
+            }