Create SkinDisease.py

SkinDisease.py

@@ -0,0 +1,101 @@
+# coding=utf-8
+import os
+from dataclasses import dataclass
+
+import datasets
+from datasets.tasks import ImageClassification
+
+_HOMEPAGE = "TODO"
+
+_CITATION = """\
+TODO
+"""
+
+_DESCRIPTION = """\
+TODO
+"""
+
+_URL = "https://huggingface.co/datasets/HugsVision/Skin-Disease/resolve/main/skin-disease-datasaet.zip"
+
+@dataclass
+class CustomConfig(datasets.BuilderConfig):
+    name: str = None
+    version: datasets.Version = None
+    description: str = None
+    schema: str = None
+    subset_id: str = None
+    
+class SkinDisease(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("1.0.0")
+
+    BUILDER_CONFIGS = [
+        CustomConfig(
+            name="default",
+            version=VERSION,
+            description="Skin Disease datasets.",
+            schema="default",
+            subset_id="default",
+        ),
+    ]
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=datasets.Features(
+                {
+                    "image_file_path": datasets.Value("string"),
+                    "image": datasets.Image(),
+                    "labels": datasets.features.ClassLabel(names=["BA-cellulitis","BA-impetigo","FU-athlete-foot","FU-nail-fungus","FU-ringworm","PA-cutaneous-larva-migrans","VI-chickenpox","VI-shingles"]),
+                }
+            ),
+            supervised_keys=("image", "labels"),
+            homepage=_HOMEPAGE,
+            citation=_CITATION,
+            task_templates=[ImageClassification(image_column="image", label_column="labels")],
+        )
+
+    def _split_generators(self, dl_manager):
+
+        data_dir = dl_manager.download_and_extract(_URL)
+        
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={
+                    "data_dir": os.path.join(data_dir, "train"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={
+                    "data_dir": os.path.join(data_dir, "validation"),
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={
+                    "data_dir": os.path.join(data_dir, "test"),
+                },
+            ),
+        ]
+
+    def _generate_examples(self, data_dir):
+
+        idx = 0
+
+        for class_name in os.listdir(data_dir):
+            
+            class_name_path = os.path.join(data_dir, class_name)
+            
+            for file_name in os.listdir(class_name_path):
+                
+                file_path = os.path.join(class_name_path, file_name)
+
+                idx += 1
+
+                yield idx, {
+                    "image_file_path": file_path,
+                    "image": file_path,
+                    "labels": class_name,
+                }