| |
|
|
| import os |
|
|
| import h5py |
| import numpy as np |
| import PIL.Image as Image |
|
|
| script_dir = os.path.dirname(__file__) |
| datafile_path = os.path.join(script_dir, "../raw/LLD-logo.hdf5") |
|
|
| with h5py.File(datafile_path, "r") as throwaway: |
| samples_count: int = len(throwaway["data"]) |
|
|
|
|
| def gen_samples( |
| labels: list[str] = ["data", "meta_data/names"], datafile_path: str = datafile_path |
| ): |
|
|
| |
| with h5py.File(datafile_path, "r") as hdf5_file: |
| count = len(hdf5_file["data"]) |
|
|
| i = 0 |
| while i < count: |
| result = {} |
|
|
| if "data" in labels: |
| shape = hdf5_file["shapes"][i] |
| images = hdf5_file["data"][i][:, : shape[1], : shape[2]] |
|
|
| result["data"] = images.astype(np.uint8) |
|
|
| for label in [l for l in labels if l != "data"]: |
| result[label] = hdf5_file[label][i] |
|
|
| yield result |
|
|
| i += 1 |
|
|
|
|
| if __name__ == "__main__": |
| sample = next(gen_samples()) |
| name = sample["meta_data/names"] |
| images = sample["data"] |
|
|
| print(name) |
|
|
| image_pil = Image.fromarray(images[2]) |
| image_pil.show() |
|
|
