Upload PM25Vision.py with huggingface_hub

PM25Vision.py

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+import os
+import csv
+import datasets
+import zipfile
+
+
+class PM25Vision(datasets.GeneratorBasedBuilder):
+    def _info(self):
+        return datasets.DatasetInfo(
+            description="PM25Vision: Street-level imagery with PM2.5 annotations",
+            features=datasets.Features(
+                {
+                    "image_id": datasets.Value("int64"),
+                    "station_id": datasets.Value("int64"),
+                    "captured_at": datasets.Value("string"),
+                    "camera_angle": datasets.Value("float64"),
+                    "longitude": datasets.Value("float64"),
+                    "latitude": datasets.Value("float64"),
+                    "quality_score": datasets.Value("float64"),
+                    "downloaded_at": datasets.Value("string"),
+                    "pm25": datasets.Value("float64"),
+                    "image": datasets.Image(),  
+                    "quality": datasets.Value("string"),
+                    "pm25_bin": datasets.Value("string"),
+                }
+            ),
+            supervised_keys=None,
+        )
+
+    def _split_generators(self, dl_manager):
+
+        train_path = dl_manager.download("train.zip")
+        test_path = dl_manager.download("test.zip")
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                gen_kwargs={"archive_path": train_path},
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"archive_path": test_path},
+            ),
+        ]
+
+    def _generate_examples(self, archive_path):
+
+        if self.config.streaming:
+            # Streaming
+            with zipfile.ZipFile(archive_path, "r") as z:
+                # find metadata.csv
+                meta_name = None
+                for name in z.namelist():
+                    if name.endswith("metadata.csv"):
+                        meta_name = name
+                        break
+                if meta_name is None:
+                    raise FileNotFoundError("metadata.csv not found in archive")
+
+                with z.open(meta_name) as f:
+                    reader = csv.DictReader(line.decode("utf-8") for line in f)
+                    for i, row in enumerate(reader):
+                        img_name = f"images/{row['filename']}"
+                        if img_name in z.namelist():
+                            img_bytes = z.read(img_name)
+                            row["image"] = {"bytes": img_bytes, "path": row["filename"]}
+                            yield i, row
+        else:
+            # default
+            base_dir = datasets.filesystems.extract_archive(archive_path)
+            metadata_file = os.path.join(base_dir, "metadata.csv")
+            images_dir = os.path.join(base_dir, "images")
+
+            with open(metadata_file, encoding="utf-8") as f:
+                reader = csv.DictReader(f)
+                for i, row in enumerate(reader):
+                    image_path = os.path.join(images_dir, row["filename"])
+                    row["image"] = image_path
+                    yield i, row