# Path: meta_dataset/data/tfds/example_generators.py
# def _image_key(image_id, total_num_examples):
# def _load_and_process_image(image_path = None,
#                             image_bytes = None,
#                             invert_img = False,
#                             bbox=None):
# def generate_aircraft_examples(metadata, paths):
# def generate_cu_birds_examples(metadata, paths):
# def generate_dtd_examples(metadata, paths):
# def generate_fungi_examples(metadata, paths):
# def generate_ilsvrc_2012_examples(metadata, paths):
# def generate_mscoco_examples(metadata, paths, box_scale_ratio=1.2):
# def generate_omniglot_examples(metadata, paths):
# def generate_quickdraw_examples(metadata, paths):
# def generate_traffic_sign_examples(metadata, paths):
# def generate_vgg_flower_examples(metadata, paths):


from meta_dataset.data.tfds import example_generators
import tensorflow_datasets as tfds
    'police car', 'pond', 'pool', 'popsicle', 'postcard', 'potato',
    'power outlet', 'purse', 'rabbit', 'raccoon', 'radio', 'rain', 'rainbow',
    'rake', 'remote control', 'rhinoceros', 'rifle', 'river', 'roller coaster',
    'rollerskates', 'sailboat', 'sandwich', 'saw', 'saxophone', 'school bus',
    'scissors', 'scorpion', 'screwdriver', 'sea turtle', 'see saw', 'shark',
    'sheep', 'shoe', 'shorts', 'shovel', 'sink', 'skateboard', 'skull',
    'skyscraper', 'sleeping bag', 'smiley face', 'snail', 'snake', 'snorkel',
    'snowflake', 'snowman', 'soccer ball', 'sock', 'speedboat', 'spider',
    'spoon', 'spreadsheet', 'square', 'squiggle', 'squirrel', 'stairs', 'star',
    'steak', 'stereo', 'stethoscope', 'stitches', 'stop sign', 'stove',
    'strawberry', 'streetlight', 'string bean', 'submarine', 'suitcase', 'sun',
    'swan', 'sweater', 'swing set', 'sword', 'syringe', 't-shirt', 'table',
    'teapot', 'teddy-bear', 'telephone', 'television', 'tennis racquet',
    'tent', 'tiger', 'toaster', 'toe', 'toilet', 'tooth', 'toothbrush',
    'toothpaste', 'tornado', 'tractor', 'traffic light', 'train', 'tree',
    'triangle', 'trombone', 'truck', 'trumpet', 'umbrella', 'underwear', 'van',
    'vase', 'violin', 'washing machine', 'watermelon', 'waterslide', 'whale',
    'wheel', 'windmill', 'wine bottle', 'wine glass', 'wristwatch', 'yoga',
    'zebra', 'zigzag'
)

BUILDER_CONFIGS = [
    dict(name='aircraft',
         dataset_spec_prefixes={'v1': 'aircraft', 'v2': 'aircraft'},
         filenames={
             'fgvc-aircraft-2013b': ('http://www.robots.ox.ac.uk/~vgg/data/'
                                     'fgvc-aircraft/archives/'
                                     'fgvc-aircraft-2013b.tar.gz'),
         },
         manual_filenames={},

# Path: meta_dataset/data/tfds/example_generators.py
# def _image_key(image_id, total_num_examples):
# def _load_and_process_image(image_path = None,
#                             image_bytes = None,
#                             invert_img = False,
#                             bbox=None):
# def generate_aircraft_examples(metadata, paths):
# def generate_cu_birds_examples(metadata, paths):
# def generate_dtd_examples(metadata, paths):
# def generate_fungi_examples(metadata, paths):
# def generate_ilsvrc_2012_examples(metadata, paths):
# def generate_mscoco_examples(metadata, paths, box_scale_ratio=1.2):
# def generate_omniglot_examples(metadata, paths):
# def generate_quickdraw_examples(metadata, paths):
# def generate_traffic_sign_examples(metadata, paths):
# def generate_vgg_flower_examples(metadata, paths):


# Path: meta_dataset/data/tfds/constants.py
from meta_dataset.data.tfds import example_generators
import tensorflow_datasets as tfds

    'police car', 'pond', 'pool', 'popsicle', 'postcard', 'potato',
    'power outlet', 'purse', 'rabbit', 'raccoon', 'radio', 'rain', 'rainbow',
    'rake', 'remote control', 'rhinoceros', 'rifle', 'river', 'roller coaster',
    'rollerskates', 'sailboat', 'sandwich', 'saw', 'saxophone', 'school bus',
    'scissors', 'scorpion', 'screwdriver', 'sea turtle', 'see saw', 'shark',
    'sheep', 'shoe', 'shorts', 'shovel', 'sink', 'skateboard', 'skull',
    'skyscraper', 'sleeping bag', 'smiley face', 'snail', 'snake', 'snorkel',
    'snowflake', 'snowman', 'soccer ball', 'sock', 'speedboat', 'spider',
    'spoon', 'spreadsheet', 'square', 'squiggle', 'squirrel', 'stairs', 'star',
    'steak', 'stereo', 'stethoscope', 'stitches', 'stop sign', 'stove',
    'strawberry', 'streetlight', 'string bean', 'submarine', 'suitcase', 'sun',
    'swan', 'sweater', 'swing set', 'sword', 'syringe', 't-shirt', 'table',
    'teapot', 'teddy-bear', 'telephone', 'television', 'tennis racquet',
    'tent', 'tiger', 'toaster', 'toe', 'toilet', 'tooth', 'toothbrush',
    'toothpaste', 'tornado', 'tractor', 'traffic light', 'train', 'tree',
    'triangle', 'trombone', 'truck', 'trumpet', 'umbrella', 'underwear', 'van',
    'vase', 'violin', 'washing machine', 'watermelon', 'waterslide', 'whale',
    'wheel', 'windmill', 'wine bottle', 'wine glass', 'wristwatch', 'yoga',
    'zebra', 'zigzag'
)

BUILDER_CONFIGS = [
    dict(name='aircraft',
         dataset_spec_prefixes={'v1': 'aircraft', 'v2': 'aircraft'},
         filenames={
             'fgvc-aircraft-2013b': ('http://www.robots.ox.ac.uk/~vgg/data/'
                                     'fgvc-aircraft/archives/'
                                     'fgvc-aircraft-2013b.tar.gz'),
         },
         manual_filenames={},

         generate_examples_fn=example_generators.generate_aircraft_examples,