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imagenet_tool.py
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imagenet_tool.py
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import numpy as np
from os import listdir
from os.path import isfile, join
from scipy.io import loadmat
meta_clsloc_file = "meta_clsloc.mat"
synsets = loadmat(meta_clsloc_file)["synsets"][0]
synsets_imagenet_sorted = sorted([(int(s[0]), str(s[1][0])) for s in synsets[:1000]],
key=lambda v:v[1])
corr = {}
for j in range(1000):
corr[synsets_imagenet_sorted[j][0]] = j
corr_inv = {}
for j in range(1,1001):
corr_inv[corr[j]] = j
def depthfirstsearch(id, out=None):
if out == None:
out = []
if type(id) == int:
pass
else:
id = next(int(s[0]) for s in synsets if s[1][0] == id)
out.append(id)
children = synsets[id-1][5][0]
for c in children:
depthfirstsearch(int(c), out)
return out
def synset_to_dfs_ids(synset):
ids = [x for x in depthfirstsearch(synset) if x <= 1000]
ids = [corr[x] for x in ids]
return ids
def synset_to_id(synset):
a = next((i for (i,s) in synsets if s == synset), None)
return a
def id_to_synset(id):
return str(synsets[corr[id]][1][0])