Create dataset.py

dataset.py

@@ -0,0 +1,47 @@
+import numpy as np
+import datasets
+
+class BreastMNIST(datasets.GeneratorBasedBuilder):
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            features=datasets.Features({
+                "image": datasets.Array3D(shape=(28, 28, 1), dtype="uint8"),  # Adjust shape if necessary
+                "label": datasets.ClassLabel(names=["benign", "malignant"])   # Adjust based on your labels
+            }),
+            description="BreastMNIST dataset containing medical imaging data",
+            supervised_keys=("image", "label"),
+        )
+
+    def _split_generators(self, dl_manager):
+        # Provide the URL for downloading your dataset
+        downloaded_file = dl_manager.download_and_extract({
+            "dataset": "https://huggingface.co/datasets/sanaa13/breastmnist1/raw/main/breastmnist.npz"
+        })
+        return [
+            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file["dataset"], "split": "train"}),
+            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_file["dataset"], "split": "val"}),
+            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_file["dataset"], "split": "test"}),
+        ]
+
+    def _generate_examples(self, filepath, split):
+        # Load the .npz file
+        data = np.load(filepath)
+
+        if split == "train":
+            images = data['train_images']
+            labels = data['train_labels']
+        elif split == "val":
+            images = data['val_images']
+            labels = data['val_labels']
+        elif split == "test":
+            images = data['test_images']
+            labels = data['test_labels']
+
+        # Yield examples in index: {image, label} format
+        for idx, (image, label) in enumerate(zip(images, labels)):
+            yield idx, {
+                "image": image,
+                "label": int(label),
+            }