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fixations.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:0c794f6a901bc1a4b780601696a68a68a5032e2b506078cce83a805aa6e02114
+size 9112539

nm_marmoset_data.py

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+import os	
+import zipfile	
+from datasets import DatasetInfo, GeneratorBasedBuilder, SplitGenerator, Split, Features, Value, BuilderConfig
+import shutil
+
+class MarmosetConfig(BuilderConfig):
+    def __init__(self, unzip_path=None, **kwargs):
+        super().__init__(**kwargs)
+        self.unzip_path = unzip_path
+        
+class MarmosetData(GeneratorBasedBuilder):		
+    BUILDER_CONFIG_CLASS = MarmosetConfig  # 🔑 Tell HF to use your custom config
+
+    BUILDER_CONFIGS = [
+        MarmosetConfig(
+            name="nm_marmoset_data",
+            description="Marmoset data unpacker",
+        )
+    ]
+    def _info(self):
+        return DatasetInfo(
+            description="Unpacks Marmoset natural movie dataset.",
+            features=Features({
+                "data_dir": Value("string"),  # optional metadata
+            }),
+        )
+
+    def _split_generators(self, dl_manager):
+        # Download & extract the needed files
+        path = 'https://huggingface.co/datasets/m-vys/nm_marmoset_data/resolve/main'
+        unzip_path = getattr(self.config, 'unzip_path')
+        urls = {
+            "stas": os.path.join(path, "stas.zip"),
+            "responses": os.path.join(path, "responses.zip"),
+            "fixations": os.path.join(path, "fixations.zip"),
+            "stimuli_padded": os.path.join(path, "stimuli_padded.zip"),
+            "stimuli_padded_4": os.path.join(path, "stimuli_padded_4.zip")
+        }
+
+        local_paths = {
+            name: dl_manager.download_and_extract(url)
+            for name, url in urls.items()
+        }
+        print('local_paths', local_paths)
+        for name, path in local_paths.items():
+            src = os.path.join(path, name)
+            dst = os.path.join(unzip_path, name)
+            print(f'moving {src} to {dst}')
+            shutil.move(src, dst)
+       
+        return [SplitGenerator(name=Split.TRAIN, gen_kwargs={"local_paths": local_paths})]	
+    def _generate_examples(self, local_paths):	
+        #Return a dictionary matching the features	
+        print(" Running _generate_examples with data_dir:", local_paths)	
+        yield 0, {"data_dir": local_paths}	
+
+

responses.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:c47d31636322553849582e2d2087c970c6d7e59aa06f0377463e727c00b8159f
+size 91470833

stas.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:3b412f467d1f5d129c07c1a53431b187d1f73e5290789051ba7fc8e1f314624e
+size 2419225057

stimuli_padded.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5c8745be674d9e9e69251cbe08047c2103820736bb336bf5bf4083d19eb795aa
+size 9760517215

stimuli_padded_4.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:26fcf40d6459f57a5abf49d20265f639417023e6383ab87eca907559c59b5eb5
+size 3085930933