Create arabic-digits.py

arabic-digits.py

@@ -0,0 +1,67 @@
+import io
+from tqdm import tqdm
+from PIL import Image
+from zipfile import ZipFile
+import datasets
+
+
+class ArabicDigits(datasets.GeneratorBasedBuilder):
+    """Arabic Handwritten Digits Dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="""Arabic Handwritten Digits Dataset, composed of images of Arabic digits handwritten 
+                           by participants. This dataset is structured for use in machine learning tasks such 
+                           as digit classification.""",
+            features=datasets.Features(
+                {
+                    "image": datasets.Image(),
+                    "label": datasets.ClassLabel(names=[str(i) for i in range(10)])
+                }
+            ),
+            supervised_keys=("image", "label"),
+            homepage="https://github.com/mloey/Arabic-Handwritten-Digits-Dataset",
+            citation="""@inproceedings{el2016cnn,
+                        title={CNN for handwritten arabic digits recognition based on LeNet-5},
+                        author={El-Sawy, Ahmed and Hazem, EL-Bakry and Loey, Mohamed},
+                        booktitle={International conference on advanced intelligent systems and informatics},
+                        pages={566--575},
+                        year={2016},
+                        organization={Springer}
+                        }""",
+            license="odbl"
+        )
+
+    def _split_generators(self, dl_manager):
+        urls = {
+            "train": "https://github.com/mloey/Arabic-Handwritten-Digits-Dataset/raw/master/Train%20Images.zip",
+            "test": "https://github.com/mloey/Arabic-Handwritten-Digits-Dataset/raw/master/Test%20Images.zip"
+        }
+        downloaded_files = dl_manager.download(urls)
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"archive_path": downloaded_files["train"], "split": "train"},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"archive_path": downloaded_files["test"], "split": "test"},
+            )
+        ]
+
+    def _generate_examples(self, archive_path, split):
+        """Generate examples from the ZIP archives of images and labels."""
+        with ZipFile(archive_path, "r") as archive:
+            for entry in tqdm(archive.infolist(), desc=f"Processing {split} set"):
+                if entry.filename.endswith(".png"):
+                    content = archive.read(entry)
+                    image = Image.open(io.BytesIO(content))
+                    label = int(entry.filename.split("_")[-1][:-4])  # Extract label from filename
+
+                    yield entry.filename, {
+                        "image": image,
+                        "label": label
+                    }