data/raw/README.md

How the data got here:

1. Downloading the DocLayNet_core.zip dataset using the wget.
2. Uploaded the downloaded DocLayNet_core.zip file to Hugging Face space.
3. Loading a dataset (chainyo/rvl-cdip-invoice) using the load_dataset function from the Hugging Face library.
4. Extracting and saving each image from the train portion of the loaded dataset into the RVL-CDIP-invoice directory.
5. Compressing the RVL-CDIP-invoice directory into a zip file (RVL-CDIP-invoice.zip) using the zip command.
6. Uploading the zip file to Hugging Face space.

# # !wget https://codait-cos-dax.s3.us.cloud-object-storage.appdomain.cloud/dax-doclaynet/1.0.0/DocLayNet_core.zip -O DocLayNet_core.zip
# upload_to_huggingface_space(
#     space_name = HUGGINGFACE_SPACE_NAME,
#     private = True,
#     path_or_fileobj = './DocLayNet_core.zip',
#     path_in_repo = 'data/raw/DocLayNet_core.zip')
# 
# 
# invoices = load_dataset('chainyo/rvl-cdip-invoice')
# # can also be found at: https://huggingface.co/datasets/aharley/rvl_cdip
# os.mkdir('./RVL-CDIP-invoice')
# for index, invoice in enumerate(tqdm(invoices['train'])):
#   invoice['image'].save(f'./RVL-CDIP-invoice/{index}.png', format="png")
# 
# !ls ./RVL-CDIP-invoice -1 | wc -l
# !zip -r RVL-CDIP-invoice.zip ./RVL-CDIP-invoice
# 
# upload_to_huggingface_space(
#     space_name = HUGGINGFACE_SPACE_NAME,
#     private = True,
#     path_or_fileobj = './RVL-CDIP-invoice.zip',
#     path_in_repo = f'data/raw/RVL-CDIP-invoice.zip')