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-rw-r--r--cli/app/commands/process/fetch.py47
1 files changed, 42 insertions, 5 deletions
diff --git a/cli/app/commands/process/fetch.py b/cli/app/commands/process/fetch.py
index a558d94..5b6c102 100644
--- a/cli/app/commands/process/fetch.py
+++ b/cli/app/commands/process/fetch.py
@@ -3,6 +3,9 @@ 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')
@@ -10,11 +13,45 @@ from app.settings import app_cfg
@click.pass_context
def cli(ctx):
"""
- Converts directory of images to BigGAN* vectors
"""
- # ------------------------------------------------
- # imports
-
# app_cfg.MODELZOO_CFG
- pass
+ 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
+ ])