Upload NewDataset.py with huggingface_hub

NewDataset.py

@@ -6,7 +6,7 @@ import zipfile
 
 class NewDataset(datasets.GeneratorBasedBuilder):
 	def _info(self):
-		return datasets.DatasetInfo(features=datasets.Features({'path':datasets.Value('string'),'image':datasets.Image(),'label': datasets.features.ClassLabel(names=['cat', 'dog\n'])}))
+		return datasets.DatasetInfo(features=datasets.Features({'image':datasets.Image(),'text':datasets.Value('string')}))
 
 	def extract_all(self, dir):
 		zip_files = glob(dir+'/**/**.zip', recursive=True)
@@ -30,7 +30,7 @@ class NewDataset(datasets.GeneratorBasedBuilder):
 
 	def read_image(self, filepath):
 		if filepath.endswith('.jpg') or filepath.endswith('.png'):
-			raw_data = {'filepath':[filepath], 'bytes':[filepath]}
+			raw_data = {'bytes':[filepath]}
 		else:
 			raw_data = {'text':[open(filepath).read()]}
 		return pd.DataFrame(raw_data)
@@ -42,10 +42,10 @@ class NewDataset(datasets.GeneratorBasedBuilder):
 			dfs = [df] 
 			dfs.append(self.read_image(filepaths['targets1'][i]))
 			df = pd.concat(dfs, axis = 1)
-			if len(df.columns) != 3:
+			if len(df.columns) != 2:
 				continue
-			df.columns = ['path', 'image', 'text']
+			df.columns = ['image', 'text']
 			for _, record in df.iterrows():
-				yield str(_id), {'path':record['path'],'image':record['image'],'label':str(record['text'])}
+				yield str(_id), {'image':record['image'],'text':record['text']}
 				_id += 1