'dirname': 'file_path'
})
video_info = video_info[~video_info['strain'].isin(bad_labels)]
fnames = root_dir + '/' + video_info['file_path'] + '/' + video_info[
'basename'].str.replace('.hdf5', '_featuresN.hdf5')
is_valid = [os.path.exists(x) for x in fnames.values]
video_info = video_info[is_valid]
fnames = [Path(x) for e, x in zip(is_valid, fnames.values) if e]
return video_info, fnames
#%%
if __name__ == '__main__':
p = 'osx' if sys.platform == 'darwin' else 'centos_oxford'
root = _root_dirs[p]
emb_sets = ['angles']
set_type = 'CeNDRAgg'
root_dir = root + 'screenings/Serena_WT_Screening/Results'
video_info, fnames = get_video_info_from_csv_agg(root_dir)
for emb_set in emb_sets:
save_file = root + 'experiments/classify_strains/{}_{}.hdf5'.format(
set_type, emb_set)
calculate_embeddings(video_info, fnames, emb_set, save_file)
fnames = root_dir + '/' + video_info['file_path'] + '/' + video_info[
'basename'].str.replace('.hdf5', '_featuresN.hdf5')
is_valid = [os.path.exists(x) for x in fnames.values]
video_info = video_info[is_valid]
fnames = [Path(x) for e, x in zip(is_valid, fnames.values) if e]
return video_info, fnames
#%%
if __name__ == '__main__':
p = 'osx' if sys.platform == 'darwin' else 'centos_oxford'
root = _root_dirs[p]
set_type = 'CeNDR'
emb_set = 'AE2DWithSkels32_emb32_20180620'
root_dir = root + 'experiments/autoencoders/embeddings/CeNDR_ROIs_embeddings/20180620_173601_AE2DWithSkels32_skel-1-1_adam_lr0.001_batch16'
video_info, fnames = get_video_info_from_files(root_dir,
f_ext='_embeddings.hdf5')
save_file = root + 'experiments/classify_strains/{}_{}.hdf5'.format(
set_type, emb_set)
calculate_embeddings(video_info,
fnames,
emb_set,
save_file,
col_label='roi_index',
embeddings_field='/embeddings')