__sets[name] = (lambda split=split, year=year: pascal_voc(
split, year, use_diff=True))
# # Set up coco_2014_<split>
# for year in ['2014']:
# for split in ['train', 'val', 'minival', 'valminusminival', 'trainval']:
# name = 'coco_{}_{}'.format(year, split)
# __sets[name] = (lambda split=split, year=year: coco(split, year))
#
# # Set up coco_2015_<split>
# for year in ['2015']:
# for split in ['test', 'test-dev']:
# name = 'coco_{}_{}'.format(year, split)
# __sets[name] = (lambda split=split, year=year: coco(split, year))
for split in ['train', 'val', 'test']:
name = 'visual_genome_{}'.format(split)
__sets[name] = (lambda split=split: visual_genome(split, use_diff=True))
def get_imdb(name):
"""Get an imdb (image database) by name."""
if name not in __sets:
raise KeyError('Unknown dataset: {}'.format(name))
return __sets[name]()
def list_imdbs():
"""List all registered imdbs."""
return list(__sets.keys())
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
"""Factory method for easily getting imdbs by name."""
__sets = {}
from datasets.visual_genome import visual_genome
import numpy as np
# Set up visual_genome_<split> using rpn mode
for version in ['1.0', '1.2']:
for split in ['train', 'val', 'test']:
name = 'vg_{}_{}'.format(version, split)
__sets[name] = (
lambda split=split, version=version: visual_genome(split, version))
def get_imdb(name):
"""Get an imdb (image database) by name."""
if not __sets.has_key(name):
raise KeyError('Unknown dataset: {}'.format(name))
return __sets[name]()
def list_imdbs():
"""List all registered imdbs."""
return __sets.keys()
# --------------------------------------------------------
# Fast R-CNN
# Copyright (c) 2015 Microsoft
# Licensed under The MIT License [see LICENSE for details]
# Written by Ross Girshick
# --------------------------------------------------------
"""Factory method for easily getting imdbs by name."""
__sets = {}
from datasets.visual_genome import visual_genome
import numpy as np
# Set up visual_genome_<split> using rpn mode
for version in ['1.0','1.2']:
for split in ['train', 'val', 'test']:
name = 'vg_{}_{}'.format(version, split)
__sets[name] = (lambda split=split, version=version: visual_genome(split,version))
def get_imdb(name):
"""Get an imdb (image database) by name."""
if not __sets.has_key(name):
raise KeyError('Unknown dataset: {}'.format(name))
return __sets[name]()
def list_imdbs():
"""List all registered imdbs."""
return __sets.keys()
for categories in categories_lists:
for split in ['train','val']:
train_dir = './data/visual_genome/' + categories + '_train'
val_dir = './data/visual_genome/' + categories + '_val'
train_list, val_list = vg_instance.train_val_splitting(0.7, eval(categories))
if not os.path.exists(train_dir):
os.system('mkdir ' + train_dir)
for f in train_list:
os.system('cp ' + vg_path + '/images/' + str(f) + '.jpg ' + train_dir)
if not os.path.exists(val_dir):
os.system('mkdir ' + val_dir)
for f in val_list:
os.system('cp ' + vg_path + '/images/' + str(f) + '.jpg ' + val_dir)
name = 'visual_genome_{}_{}'.format(categories,split)
__sets[name] = (lambda split=split, categories=categories: visual_genome(categories, eval(categories), split))
def get_imdb(name):
"""Get an imdb (image database) by name."""
if name not in __sets:
raise KeyError('Unknown dataset: {}'.format(name))
return __sets[name]()
def list_imdbs():
"""List all registered imdbs."""
return list(__sets.keys())
name = 'coco_{}_{}'.format(year, split)
__sets[name] = (lambda split=split, year=year: coco(split, year))
# Set up coco_2015_<split>
for year in ['2015']:
for split in ['test', 'test-dev']:
name = 'coco_{}_{}'.format(year, split)
__sets[name] = (lambda split=split, year=year: coco(split, year))
# Set up ade_<split>_5
for split in ['train', 'val', 'mval', 'mtest']:
name = 'ade_{}_5'.format(split)
__sets[name] = (lambda split=split: ade(split))
# Set up vg_<split>_5,10
for split in ['train', 'val', 'test']:
name = 'visual_genome_{}_5'.format(split)
__sets[name] = (lambda split=split: visual_genome(split))
def get_imdb(name):
"""Get an imdb (image database) by name."""
if name not in __sets:
raise KeyError('Unknown dataset: {}'.format(name))
return __sets[name]()
def list_imdbs():
"""List all registered imdbs."""
return list(__sets.keys())