Spaces:
Running
on
T4
Running
on
T4
| 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]) | |