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import os |
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import pandas as pd |
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import datasets |
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from glob import glob |
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import zipfile |
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class dummy(datasets.GeneratorBasedBuilder): |
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def _info(self): |
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return datasets.DatasetInfo(features=datasets.Features({'image':datasets.Image(),'text':datasets.Value('string')})) |
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def extract_all(self, dir): |
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zip_files = glob(dir+'/**/**.zip', recursive=True) |
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for file in zip_files: |
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with zipfile.ZipFile(file) as item: |
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item.extractall('/'.join(file.split('/')[:-1])) |
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def get_all_files(self, dir): |
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files = [] |
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valid_file_ext = ['txt', 'csv', 'tsv', 'xlsx', 'xls', 'xml', 'json', 'jsonl', 'html', 'wav', 'mp3', 'jpg', 'png'] |
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for ext in valid_file_ext: |
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files += glob(f"{dir}/**/**.{ext}", recursive = True) |
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return files |
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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]} |
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else: |
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raw_data = {'text':[open(filepath).read()]} |
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return pd.DataFrame(raw_data) |
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def _generate_examples(self, filepaths): |
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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', 'text'] |
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for _, record in df.iterrows(): |
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yield str(_id), {'image':record['image'],'text':record['text']} |
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_id += 1 |
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