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import io
import datasets
from PIL import Image
class DemoImages:
_instance = None
def __new__(cls, *args, **kwargs):
if not cls._instance:
cls._instance = super(DemoImages, cls).__new__(cls, *args, **kwargs)
return cls._instance
def __init__(self, url="Riksarkivet/test_images_demo", cache_dir="./helper/examples/.cache_images"):
if not hasattr(self, "images_datasets"):
self.images_datasets = datasets.load_dataset(url, cache_dir=cache_dir, split="train")
self.example_df = self.images_datasets.to_pandas()
self.examples_list = self.convert_bytes_to_images()
def convert_bytes_to_images(self):
examples_list = []
# For each row in the dataframe
for index, row in self.example_df.iterrows():
image_bytes = row["image"]["bytes"]
image = Image.open(io.BytesIO(image_bytes))
# Set the path to save the image
path_to_image = f"./helper/examples/images/image_{index}.jpg"
# Save the image
image.save(path_to_image)
# Get the description
description = row["text"]
# Append to the examples list
examples_list.append([description, path_to_image])
return examples_list
if __name__ == "__main__":
# test = DemoImages(cache_dir=".cache_images")
# print(test.examples_list)
images_datasets = datasets.load_dataset("Riksarkivet/test_images_demo", cache_dir="./helper/examples/.cache_images")
print(images_datasets["train"]["image"][0])
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