lukasbraach commited on
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upd: new try

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Files changed (2) hide show
  1. README.md +0 -39
  2. rwth_phoenix_weather_2014.py +2 -4
README.md CHANGED
@@ -1,42 +1,3 @@
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- ---
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- dataset_info:
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- - config_name: multisigner
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- features:
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- - name: tokens
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- sequence: string
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- - name: frames
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- sequence: image
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- splits:
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- - name: train
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- num_bytes: 35090699166
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- num_examples: 5672
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- - name: validation
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- num_bytes: 3294861848
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- num_examples: 540
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- - name: test
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- num_bytes: 3935889563
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- num_examples: 629
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- download_size: 43042303939
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- dataset_size: 42321450577
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- - config_name: signerindependent
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- features:
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- - name: tokens
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- sequence: string
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- - name: frames
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- sequence: image
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- splits:
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- - name: train
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- num_bytes: 26933878872
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- num_examples: 4376
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- - name: validation
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- num_bytes: 720567494
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- num_examples: 111
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- - name: test
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- num_bytes: 1175795394
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- num_examples: 180
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- download_size: 29320607031
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- dataset_size: 28830241760
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- ---
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  # RWTH-Weather-Phoenix 2014
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  This archive contains two sets of the RWTH-Weather-Phoenix 2014 corpus
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  # RWTH-Weather-Phoenix 2014
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  This archive contains two sets of the RWTH-Weather-Phoenix 2014 corpus
rwth_phoenix_weather_2014.py CHANGED
@@ -79,12 +79,10 @@ class RWTHPhoenixWeather2014(datasets.GeneratorBasedBuilder):
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  def _info(self):
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  features_dict = {
 
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  "transcription": datasets.Value("string"),
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  }
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- if self.config.name != "pre-training":
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- features_dict["frames"] = datasets.Sequence(feature=datasets.Image())
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-
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  return datasets.DatasetInfo(
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  description=_DESCRIPTION + self.config.description,
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  features=datasets.Features(features_dict),
@@ -97,7 +95,6 @@ class RWTHPhoenixWeather2014(datasets.GeneratorBasedBuilder):
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  def _split_generators(self, dl_manager: datasets.DownloadManager):
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  dfs = {}
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- split_frames = {}
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  file_ids = {}
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  dataDirMapper = {
@@ -139,6 +136,7 @@ class RWTHPhoenixWeather2014(datasets.GeneratorBasedBuilder):
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  entry = df[df["id"] == idx]
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  result = {
 
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  "transcription": entry["annotation"],
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  }
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  def _info(self):
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  features_dict = {
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+ "id": datasets.Value("string"),
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  "transcription": datasets.Value("string"),
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  }
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  return datasets.DatasetInfo(
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  description=_DESCRIPTION + self.config.description,
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  features=datasets.Features(features_dict),
 
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  def _split_generators(self, dl_manager: datasets.DownloadManager):
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  dfs = {}
 
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  file_ids = {}
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  dataDirMapper = {
 
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  entry = df[df["id"] == idx]
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  result = {
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+ "id": idx,
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  "transcription": entry["annotation"],
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  }
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