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import os
import pandas as pd
import datasets
import json
from huggingface_hub import hf_hub_url
_INPUT_CSV = 'captions.txt'
_INPUT_IMAGES = "Images"
_REPO_ID = "shivangibithel/flickr8k"
_JSON_KEYS = ['caption']
class Dataset(datasets.GeneratorBasedBuilder):
VERSION = datasets.Version("1.1.0")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="ALL", version=VERSION, description="all"),
]
def _info(self):
return datasets.DatasetInfo(
features=datasets.Features(
{
"image": datasets.Image(),
"caption": [datasets.Value('string')],
"image_filename": datasets.Value("string"),
}
),
task_templates=[],
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
repo_id = _REPO_ID
data_dir = dl_manager.download_and_extract({
"examples_csv": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=_INPUT_CSV),
"images_dir": hf_hub_url(repo_id=repo_id, repo_type='dataset', filename=f"{_INPUT_IMAGES}.zip")
})
return [datasets.SplitGenerator(name=datasets.Split.ALL, gen_kwargs=data_dir)]
def _generate_examples(self, examples_csv, images_dir):
"""Yields examples."""
df = pd.read_csv(examples_csv, delimiter=',')
for c in _JSON_KEYS:
df[c] = df[c].apply(json.loads)
for r_idx, r in df.iterrows():
r_dict = r.to_dict()
image_path = os.path.join(images_dir, _INPUT_IMAGES, r_dict['image_filename'])
r_dict['image'] = image_path
r_dict['caption'] = r_dict.pop('caption')
yield r_idx, r_dict |