Create beans.py

beans.py

@@ -0,0 +1,65 @@
+import datasets
+from PIL import Image
+import zipfile
+
+
+class Beans(datasets.GeneratorBasedBuilder):
+    """Bean disease dataset for classification of three classes: Angular Leaf Spot, Bean Rust, and Healthy leaves."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="""The IBeans dataset contains leaf images representing three classes: 
+                1) Healthy leaves, 2) Angular Leaf Spot, and 3) Bean Rust. Images are collected in Uganda for disease 
+                classification in the field.""",
+            features=datasets.Features(
+                {
+                    "image": datasets.Image(),
+                    "label": datasets.ClassLabel(
+                        names=["healthy", "angular_leaf_spot", "bean_rust"]
+                    ),
+                }
+            ),
+            supervised_keys=("image", "label"),
+            license="MIT License",
+            citation="""@misc{makerere2020beans,
+                         author = "{Makerere AI Lab}",
+                         title = "{Bean Disease Dataset}",
+                         year = "2020",
+                         month = "January",
+                         url = "https://github.com/AI-Lab-Makerere/ibean/"}"""
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = {
+            "train": "https://storage.googleapis.com/ibeans/train.zip",
+            "test": "https://storage.googleapis.com/ibeans/test.zip",
+            "validation": "https://storage.googleapis.com/ibeans/validation.zip",
+        }
+        downloaded_files = dl_manager.download(urls)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"zip_path": downloaded_files["train"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"zip_path": downloaded_files["test"]},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                gen_kwargs={"zip_path": downloaded_files["validation"]},
+            ),
+        ]
+
+    def _generate_examples(self, zip_path):
+        with zipfile.ZipFile(zip_path, "r") as archive:
+            for file_name in archive.namelist():
+                if file_name.endswith(".jpg"):
+                    with archive.open(file_name) as file:
+                        image_data = Image.open(file)
+                        label_name = file_name.split("/")[1]
+                        label = self.info.features["label"].str2int(label_name)
+                        yield file_name, {"image": image_data, "label": label}