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dummy.py

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+import os
+import pandas as pd 
+import datasets
+from glob import glob
+import zipfile
+
+class dummy(datasets.GeneratorBasedBuilder):
+	def _info(self):
+		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)
+		for file in zip_files:
+			with zipfile.ZipFile(file) as item:
+				item.extractall('/'.join(file.split('/')[:-1])) 
+
+
+	def get_all_files(self, dir):
+		files = []
+		valid_file_ext = ['txt', 'csv', 'tsv', 'xlsx', 'xls', 'xml', 'json', 'jsonl', 'html', 'wav', 'mp3', 'jpg', 'png']
+		for ext in valid_file_ext:
+			files += glob(f"{dir}/**/**.{ext}", recursive = True)
+		return files
+
+	def _split_generators(self, dl_manager):
+		url = [os.path.abspath(os.path.expanduser(dl_manager.manual_dir))]
+		downloaded_files = dl_manager.download_and_extract(url)
+		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')),} })]
+
+
+	def read_image(self, filepath):
+		if filepath.endswith('.jpg') or filepath.endswith('.png'):
+			raw_data = {'bytes':[filepath]}
+		else:
+			raw_data = {'text':[open(filepath).read()]}
+		return pd.DataFrame(raw_data)
+
+	def _generate_examples(self, filepaths):
+		_id = 0
+		for i,filepath in enumerate(filepaths['inputs']):
+			df = self.read_image(filepath)
+			dfs = [df] 
+			dfs.append(self.read_image(filepaths['targets1'][i]))
+			df = pd.concat(dfs, axis = 1)
+			if len(df.columns) != 2:
+				continue
+			df.columns = ['image', 'text']
+			for _, record in df.iterrows():
+				yield str(_id), {'image':record['image'],'text':record['text']}
+				_id += 1 
+