<jupyter_start><jupyter_text>DownloadThis notebook will download and extract the images and captions from the COCO Dataset  Setup Check if already downloaded and extracted<jupyter_code>assert len(list((DIR_DATA).glob('COCO/val/*.jpg'))) == 0, 'Everything seems to be downloaded and extracted'<jupyter_output><empty_output><jupyter_text>Imports<jupyter_code>from captioner.download import download_images, download_captions<jupyter_output><empty_output><jupyter_text>Preparations<jupyter_code>DIR_DATA = DIR_DATA / 'COCO'<jupyter_output><empty_output><jupyter_text>Load Data Download and Extract Data<jupyter_code>download_images('train', DIR_DATA)
download_images('val', DIR_DATA)
download_captions(DIR_DATA)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.0975609756097561, 'fraction_numerical': 0.0013550135501355014, 'mean_word_length': 12.436363636363636, 'pattern_counts': {'":': 0, '<': 17, '<?xml version=': 0, '>': 17, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 11, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '4', 'dir': 'jupyter-structured-clean-dedup', 'id': '134628', 'license': 'MIT', 'n_tokens_mistral': 254, 'n_tokens_neox': 247, 'n_words': 45, 'path': 'notebooks/Download.ipynb', 'repo_name': 'svaisakh/captioner', 'size': '738'}