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import click
from app.utils import click_utils
from app.settings import app_cfg
from os.path import join
from subprocess import call
@click.command('')
# @click.option('-i', '--input', 'opt_dir_in', required=True,
# help='Path to input image glob directory')
# @click.option('-r', '--recursive', 'opt_recursive', is_flag=True)
@click.pass_context
def cli(ctx):
"""
"""
# app_cfg.MODELZOO_CFG
import gensim
# from nltk.corpus import wordnet as wn
# synsets = wordnet.synsets("fir_tree")
# synonyms = [ lemma.name() for lemma in synsets[0].lemmas() ]
imagenet = Imagenet()
sentence = "The quick brown fox jumps over the lazy dog"
tokens = gensim.utils.simple_preprocess(sentence)
class Imagenet:
def __init__():
tokens = {}
with open(app_cfg.FP_IMAGENET_WORDS, "r") as fp:
for line in fp.readlines():
wordnet_id, word_list = line.split('\t')
words = [word.trim() for word in word_list.split(',')]
for word in words:
tokens[word] = wordnet_id
self.tokens = tokens
def get_wordnet_ids_for_words(tokens):
# for token in tokens:
# if token in tokens:
pass
def images_from_wordnet_id(wordnet_id):
"""
Given a Wordnet ID, download images for this class
"""
call([
"python",
join(app_cfg.DIR_APP, "../ImageNet-Datasets-Downloader/downloader.py"),
'-data_root', app_cfg.FP_IMAGENET,
'-use_class_list', 'True',
'-class_list', wordnet_id,
'-images_per_class', app_cfg.IMAGENET_IMAGES_PER_CLASS
])
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