s2_download_data.py

import requests
from PIL import Image
from IPython.display import display
import huggingface_hub
from huggingface_hub import list_datasets
from huggingface_hub import HfApi

# You can use your own uploaded images and captions. 
# You will be responsible for the legal use of images that 
#  you are going to use.

url1='http://farm3.staticflickr.com/2519/4126738647_cc436c111b_z.jpg'
cap1='A motorcycle sits parked across from a herd of livestock'

url2='http://farm3.staticflickr.com/2046/2003879022_1b4b466d1d_z.jpg'
cap2='Motorcycle on platform to be worked on in garage'

url3='https://i.natgeofe.com/n/548467d8-c5f1-4551-9f58-6817a8d2c45e/NationalGeographic_2572187_3x2.jpg'
cap3='a cat laying down stretched out near a laptop'

img1 = {
  'flickr_url': url1,
  'caption': cap1,
  'image_path' : './shared_data/motorcycle_1.jpg'
}

img2 = {
    'flickr_url': url2,
    'caption': cap2,
    'image_path' : './shared_data/motorcycle_2.jpg'
}

img3 = {
    'flickr_url' : url3,
    'caption': cap3,
    'image_path' : './shared_data/cat_1.jpg'
}

def download_images():
    # download images
    imgs = [img1, img2, img3]
    for img in imgs:
        data = requests.get(img['flickr_url']).content
        with open(img['image_path'], 'wb') as f:
            f.write(data)

    for img in [img1, img2, img3]:
        image = Image.open(img['image_path'])
        caption = img['caption']
        display(image)
        print(caption)
        
def load_data_from_huggingface(hf_dataset_name):
        
    api = HfApi()

    #list models from huggingface

    #models = list(api.list_models())

    #list datasets from huggingface

    #datasets = list(api.list_datasets())


    return api.list_datasets(search=hf_dataset_name)