2k19 release

Chunk_1.zip

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comma2k19.py

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+import datasets
+import glob
+import os
+import numpy as np
+
+NUM_SHARDS = 10
+_URLS = [
+      f'https://huggingface.co/datasets/commaai/commavq/resolve/main/Chunk_{i}.zip' for i in range(1,NUM_SHARDS+1)
+    ]
+
+_DESCRIPTION = """\
+comma2k19 is a dataset of over 33 hours of commute in California's 280 highway.
+This means 2019 segments, 1 minute long each, on a 20km section of highway driving between California's San Jose and San Francisco.
+comma2k19 is a fully reproducible and scalable dataset.
+The data was collected using comma EONs that has sensors similar to those of any modern smartphone including a road-facing camera, phone GPS, thermometers and 9-axis IMU.
+Additionally, the EON captures raw GNSS measurements and all CAN data sent by the car with a comma grey panda.
+"""
+
+class Comma2k19(datasets.GeneratorBasedBuilder):
+
+  def _info(self):
+    return datasets.DatasetInfo(
+      description=_DESCRIPTION,
+      features=datasets.Features(
+        {"path": datasets.Value("string")}
+      )
+    )
+
+  def _split_generators(self, dl_manager):
+    """Returns SplitGenerators."""
+    dl_manager.download_config.ignore_url_params = True
+    downloaded_files = dl_manager.download(_URLS)
+    local_extracted_archive = dl_manager.extract(downloaded_files) if not dl_manager.is_streaming else None
+    return [
+      datasets.SplitGenerator(
+        name=str(i),
+        gen_kwargs={"local_extracted_archive":local_extracted_archive[i], "files": dl_manager.iter_archive(downloaded_files[i])}
+        ) for i in range(len(downloaded_files))]
+
+  def _generate_examples(self, local_extracted_archive, files):
+    files = glob.glob(local_extracted_archive, recursive=True)
+    for path in files:
+      file_name = os.path.basename(path)
+      yield file_name, {'path': path}
+
+  def _get_examples_iterable_for_split(self, split_generator):
+    for path in split_generator.gen_kwargs['files']:
+      yield path[0], {'path': path[0]}