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# hello fellow human, this script is used to save kspace data to disk
# You may ask why? Well, as it turns out having h5py read the entire .h5 file
# and then just accessing the kspace data as numpy array takes around 50 seconds for a single file
# and that's just too slow for me. So I'm going to save the kspace data to disk as numpy arrays
import h5py
import huggingface_hub as hfh
import numpy as np
# datasets
# osbm/fastmri-prostate
# osbm/fastmri-brain
# osbm/fastmri-knee
# files in the dataset
# prostate
# - training_T2_1/file_prostate_AXT2_0002.h5
# - training_T2_1/file_prostate_AXT2_0015.h5
# brain
# - multicoil_train/file_brain_AXFLAIR_200_6002442.h5
# - multicoil_train/file_brain_AXFLAIR_200_6002487.h5
# knee
# - singlecoil_train/file1000015.h5
# - multicoil_train/file1000015.h5
# Download files
file_paths = {
"prostate1": hfh.hf_hub_download(
repo_id="osbm/fastmri-prostate",
filename="training_T2_1/file_prostate_AXT2_0002.h5",
repo_type="dataset",
cache_dir="./data"
),
"prostate2": hfh.hf_hub_download(
repo_id="osbm/fastmri-prostate",
filename="training_T2_1/file_prostate_AXT2_0015.h5",
repo_type="dataset",
cache_dir="./data"
),
"brain1": hfh.hf_hub_download(
repo_id="osbm/fastmri-brain",
filename="multicoil_train/file_brain_AXFLAIR_200_6002442.h5",
repo_type="dataset",
cache_dir="./data"
),
"brain2": hfh.hf_hub_download(
repo_id="osbm/fastmri-brain",
filename="multicoil_train/file_brain_AXFLAIR_200_6002487.h5",
repo_type="dataset",
cache_dir="./data"
),
"knee1": hfh.hf_hub_download(
repo_id="osbm/fastmri-knee",
filename="singlecoil_train/file1000015.h5",
repo_type="dataset",
cache_dir="./data"
),
"knee2": hfh.hf_hub_download(
repo_id="osbm/fastmri-knee",
filename="multicoil_train/file1000015.h5",
repo_type="dataset",
cache_dir="./data"
)
}
for key, file_path in file_paths.items():
print(f"{key}: {file_path}")
file = h5py.File(file_path, "r")
kspace = file["kspace"][()]
print(kspace.shape)
if key.startswith("prostate"):
kspace = kspace[0, :, :, :] + kspace[1, :, :, :]
print(kspace.shape)
np.save(f"./data/{key}_kspace.npy", kspace) |