Add

image_dataset.py

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+import os
+import json
+import random
+from datasets import (
+    BuilderConfig,
+    DatasetInfo,
+    DownloadManager,
+    GeneratorBasedBuilder,
+    SplitGenerator,
+    Split,
+    Features,
+    Image,
+    Sequence,
+    Value,
+)
+
+class ImageSubsetConfig(BuilderConfig):
+    """BuilderConfig for small vs. full dataset."""
+    def __init__(self, name, sample_size=None, **kwargs):
+        super().__init__(
+            name=name,
+            version="1.0.0",
+            description=kwargs.get("description", "")
+        )
+        self.sample_size = sample_size
+
+class MyImageDataset(GeneratorBasedBuilder):
+    """A dataset of images with actuated_angle from metadata.json."""
+    BUILDER_CONFIGS = [
+        ImageSubsetConfig(
+            name="full",
+            sample_size=None,
+            description="All images (≈100 GB). Use with streaming=True."
+        ),
+        ImageSubsetConfig(
+            name="small",
+            sample_size=2,
+            description="Random subset of 10 000 images for quick iteration."
+        ),
+    ]
+    DEFAULT_CONFIG_NAME = "smgit all"
+
+    def _info(self):
+        return DatasetInfo(
+            description="Images with a 2-D actuated_angle from metadata.json",
+            features=Features({
+                "image": Image(),                      # the image file
+                "actuated_angle": Sequence(Value("int32")),  # [angle0, angle1]
+            }),
+            supervised_keys=None,
+        )
+
+    def _split_generators(self, dl_manager: DownloadManager):
+        data_dir = dl_manager.manual_dir or os.path.abspath(os.path.dirname(__file__))
+        images_dir = os.path.join(data_dir, "images")
+        meta_path = os.path.join(data_dir, "metadata.json")
+
+        # load your filename → {"0":…, "1":…} mapping
+        with open(meta_path, "r", encoding="utf-8") as f:
+            metadata = json.load(f)
+
+        # sample if in "small" config
+        if self.config.sample_size:
+            all_fnames = list(metadata.keys())
+            random.seed(42)
+            selected = set(random.sample(all_fnames, self.config.sample_size))
+        else:
+            selected = set(metadata.keys())
+
+        return [
+            SplitGenerator(
+                name=Split.TRAIN,
+                gen_kwargs={
+                    "images_dir": images_dir,
+                    "metadata": metadata,
+                    "selected": selected,
+                },
+            ),
+        ]
+
+    def _generate_examples(self, images_dir, metadata, selected):
+        """Yields examples of the form { "image": path, "actuated_angle": [int, int] }"""
+        for idx, fname in enumerate(selected):
+            if fname not in metadata:
+                continue
+            image_path = os.path.join(images_dir, fname)
+            if not os.path.exists(image_path):
+                continue
+            meta = metadata[fname]
+            # extract the two angle values (keys "0" and "1")
+            angles = [ int(meta.get("0", 0)), int(meta.get("1", 0)) ]
+            yield idx, {
+                "image": image_path,
+                "actuated_angle": angles,
+            }

metadata.json

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+{
+    "frame_0a0ab072-9729-4e16-88c5-a3ea9ed959d0_0036.png": {
+        "0": 90,
+        "1": 20
+    },
+    "frame_0a1d5ccc-e1c7-4c66-8fbc-f87080c3f408_0046.png": {
+        "0": 90,
+        "1": 20
+    },
+    "frame_0a1d30e1-d358-4533-a192-75c5c86a2d56_0049.png": {
+        "0": 90,
+        "1": 20
+    },
+    "frame_0a0bf5c3-9ee4-41aa-9298-ccfebdb1b5ea_0029.png": {
+        "0": 90,
+        "1": 20
+    }
+}