You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Thanks for the code. Just a few notes in case anyone else runs into the same problems. I needed to add a statement to clear the session when I was using mclahe to loop through thousands of 3D images on a CPU. Otherwise, memory usage expands and code slows to a crawl. Also, the default kernel size is 1/8 of data dimensions. For a 3D image with one dimension less than 8, I got an error. I needed to change kernel size to ceiling of 1/8 image dims. These fixes are shown below.
for i, full_path in enumerate(full_paths):
os.makedirs(paths_new[i], exist_ok = True)
print(i)
img_arr, meta_data = load(full_path)
dims = np.shape(img_arr)
img_arr_eq = mc.mclahe(img_arr, kernel_size = [int(np.ceil(dims[0]/8)), int(np.ceil(dims[1]/8)), int(np.ceil(dims[2]/8))])
save(img_arr_eq, full_paths_new[i], meta_data)
tf.keras.backend.clear_session()
The text was updated successfully, but these errors were encountered:
Thanks for the code. Just a few notes in case anyone else runs into the same problems. I needed to add a statement to clear the session when I was using mclahe to loop through thousands of 3D images on a CPU. Otherwise, memory usage expands and code slows to a crawl. Also, the default kernel size is 1/8 of data dimensions. For a 3D image with one dimension less than 8, I got an error. I needed to change kernel size to ceiling of 1/8 image dims. These fixes are shown below.
The text was updated successfully, but these errors were encountered: