Upload pm25vision.py with huggingface_hub

pm25vision.py

@@ -1,6 +1,7 @@
 import os
 import csv
 import datasets
+import zipfile
 
 
 class PM25Vision(datasets.GeneratorBasedBuilder):
@@ -18,7 +19,7 @@ class PM25Vision(datasets.GeneratorBasedBuilder):
                     "quality_score": datasets.Value("float64"),
                     "downloaded_at": datasets.Value("string"),
                     "pm25": datasets.Value("float64"),
-                    "image": datasets.Image(),   # 图片字段
+                    "image": datasets.Image(),  
                     "quality": datasets.Value("string"),
                     "pm25_bin": datasets.Value("string"),
                 }
@@ -27,29 +28,52 @@ class PM25Vision(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        # unzip
-        train_path = dl_manager.download_and_extract("train.zip")
-        test_path = dl_manager.download_and_extract("test.zip")
+
+        train_path = dl_manager.download("train.zip")
+        test_path = dl_manager.download("test.zip")
 
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
-                gen_kwargs={"base_dir": train_path},
+                gen_kwargs={"archive_path": train_path},
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
-                gen_kwargs={"base_dir": test_path},
+                gen_kwargs={"archive_path": test_path},
             ),
         ]
 
-    def _generate_examples(self, base_dir):
-        # structure: base_dir/metadata.csv + base_dir/images/*
-        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
+    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