Zaid commited on
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84bfecc
1 Parent(s): af89340

Upload NewDataset.py with huggingface_hub

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Files changed (1) hide show
  1. NewDataset.py +11 -8
NewDataset.py CHANGED
@@ -6,7 +6,7 @@ import zipfile
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  class NewDataset(datasets.GeneratorBasedBuilder):
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  def _info(self):
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- return datasets.DatasetInfo(features=datasets.Features({'image':datasets.Image(),'label':datasets.Value('string')}))
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  def extract_all(self, dir):
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  zip_files = glob(dir+'/**/**.zip', recursive=True)
@@ -25,9 +25,14 @@ class NewDataset(datasets.GeneratorBasedBuilder):
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  def _split_generators(self, dl_manager):
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  url = [os.path.abspath(os.path.expanduser(dl_manager.manual_dir))]
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  downloaded_files = dl_manager.download_and_extract(url)
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- return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepaths':{'inputs':sorted(glob(downloaded_files[0]+'/data/**.png')),'targets1':sorted(glob(downloaded_files[0]+'/data/**.txt')),} })]
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  def read_image(self, filepath):
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  if filepath.endswith('.jpg') or filepath.endswith('.png'):
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  raw_data = {'bytes':[filepath]}
@@ -39,13 +44,11 @@ class NewDataset(datasets.GeneratorBasedBuilder):
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  _id = 0
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  for i,filepath in enumerate(filepaths['inputs']):
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  df = self.read_image(filepath)
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- dfs = [df]
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- dfs.append(self.read_image(filepaths['targets1'][i]))
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- df = pd.concat(dfs, axis = 1)
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- if len(df.columns) != 2:
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  continue
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- df.columns = ['image', 'label']
 
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  for _, record in df.iterrows():
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- yield str(_id), {'image':record['image'],'label':record['label']}
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  _id += 1
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  class NewDataset(datasets.GeneratorBasedBuilder):
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  def _info(self):
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+ return datasets.DatasetInfo(features=datasets.Features({'image':datasets.Image(),'label': datasets.features.ClassLabel(names=['dogs', 'cats'])}))
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  def extract_all(self, dir):
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  zip_files = glob(dir+'/**/**.zip', recursive=True)
 
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  def _split_generators(self, dl_manager):
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  url = [os.path.abspath(os.path.expanduser(dl_manager.manual_dir))]
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  downloaded_files = dl_manager.download_and_extract(url)
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+ return [datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={'filepaths':{'inputs':sorted(glob(downloaded_files[0]+'/data/**/**.png')),} })]
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+ def get_label_from_path(self, labels, label):
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+ for l in labels:
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+ if l == label:
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+ return label
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+
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  def read_image(self, filepath):
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  if filepath.endswith('.jpg') or filepath.endswith('.png'):
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  raw_data = {'bytes':[filepath]}
 
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  _id = 0
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  for i,filepath in enumerate(filepaths['inputs']):
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  df = self.read_image(filepath)
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+ if len(df.columns) != 1:
 
 
 
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  continue
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+ df.columns = ['image']
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+ label = self.get_label_from_path(['dogs', 'cats'], filepath.split('/')[-2])
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  for _, record in df.iterrows():
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+ yield str(_id), {'image':record['image'],'label':str(label)}
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  _id += 1
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