Module vipy.data.oxford_flowers_102
Expand source code Browse git
import os
import vipy.downloader
import vipy.dataset
from vipy.util import remkdir
from vipy.image import ImageCategory
import scipy.io
IMAGE_URL = 'https://www.robots.ox.ac.uk/~vgg/data/flowers/102/102flowers.tgz'
ANNO_URL = 'https://www.robots.ox.ac.uk/~vgg/data/flowers/102/imagelabels.mat'
SHA1 = None
class Flowers102(vipy.dataset.Dataset):
"""Project: https://www.robots.ox.ac.uk/~vgg/data/flowers/102"""
def __init__(self, datadir):
# Download (if not cached)
self._datadir = remkdir(datadir)
if not os.path.exists(os.path.join(self._datadir, '102flowers.tgz')):
vipy.downloader.download_and_unpack(IMAGE_URL, self._datadir, sha1=None)
# Read cached JSON
jsonfile = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'oxford_flowers_102.json')
if not os.path.exists(jsonfile):
self._cache_annotations(jsonfile)
self._json = vipy.util.readjson(jsonfile)
# Create dataset
imlist = [vipy.image.ImageCategory(filename=f, category=self._json['labelindex_to_category'][self._json['imageindex_to_labelindex'][k]]) for (k,f) in enumerate(sorted(vipy.util.findimages(self._datadir)))]
super().__init__(imlist, id='flowers102')
def _cache_annotations(self, outjson='oxford_flowers_102.json'):
if not os.path.exists(os.path.join(self._datadir, 'imagelabels.mat')):
vipy.downloader.download(ANNO_URL, os.path.join(self._datadir, 'imagelabels.mat'), sha1=None)
# Thanks to: https://gist.githubusercontent.com/JosephKJ/94c7728ed1a8e0cd87fe6a029769cde1/raw/403325f5110cb0f3099734c5edb9f457539c77e9/Oxford-102_Flower_dataset_labels.txt
category = ['pink primrose',
'hard-leaved pocket orchid',
'canterbury bells',
'sweet pea',
'english marigold',
'tiger lily',
'moon orchid',
'bird of paradise',
'monkshood',
'globe thistle',
'snapdragon',
"colt's foot",
'king protea',
'spear thistle',
'yellow iris',
'globe-flower',
'purple coneflower',
'peruvian lily',
'balloon flower',
'giant white arum lily',
'fire lily',
'pincushion flower',
'fritillary',
'red ginger',
'grape hyacinth',
'corn poppy',
'prince of wales feathers',
'stemless gentian',
'artichoke',
'sweet william',
'carnation',
'garden phlox',
'love in the mist',
'mexican aster',
'alpine sea holly',
'ruby-lipped cattleya',
'cape flower',
'great masterwort',
'siam tulip',
'lenten rose',
'barbeton daisy',
'daffodil',
'sword lily',
'poinsettia',
'bolero deep blue',
'wallflower',
'marigold',
'buttercup',
'oxeye daisy',
'common dandelion',
'petunia',
'wild pansy',
'primula',
'sunflower',
'pelargonium',
'bishop of llandaff',
'gaura',
'geranium',
'orange dahlia',
'pink-yellow dahlia?',
'cautleya spicata',
'japanese anemone',
'black-eyed susan',
'silverbush',
'californian poppy',
'osteospermum',
'spring crocus',
'bearded iris',
'windflower',
'tree poppy',
'gazania',
'azalea',
'water lily',
'rose',
'thorn apple',
'morning glory',
'passion flower',
'lotus',
'toad lily',
'anthurium',
'frangipani',
'clematis',
'hibiscus',
'columbine',
'desert-rose',
'tree mallow',
'magnolia',
'cyclamen ',
'watercress',
'canna lily',
'hippeastrum ',
'bee balm',
'ball moss',
'foxglove',
'bougainvillea',
'camellia',
'mallow',
'mexican petunia',
'bromelia',
'blanket flower',
'trumpet creeper',
'blackberry lily', '102']
labelindex_to_category = {str(k):c for (k,c) in enumerate(category, start=1)} # one-indexed
# Import, cache and reuse JSON
import scipy.io
mat = scipy.io.loadmat(os.path.join(self._datadir, 'imagelabels.mat'))
imageindex_to_labelindex = [str(c) for c in mat['labels'][0]]
return vipy.util.writejson({'imageindex_to_labelindex': imageindex_to_labelindex, 'labelindex_to_category':labelindex_to_category}, outjson)
Classes
class Flowers102 (datadir)
-
Expand source code Browse git
class Flowers102(vipy.dataset.Dataset): """Project: https://www.robots.ox.ac.uk/~vgg/data/flowers/102""" def __init__(self, datadir): # Download (if not cached) self._datadir = remkdir(datadir) if not os.path.exists(os.path.join(self._datadir, '102flowers.tgz')): vipy.downloader.download_and_unpack(IMAGE_URL, self._datadir, sha1=None) # Read cached JSON jsonfile = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'oxford_flowers_102.json') if not os.path.exists(jsonfile): self._cache_annotations(jsonfile) self._json = vipy.util.readjson(jsonfile) # Create dataset imlist = [vipy.image.ImageCategory(filename=f, category=self._json['labelindex_to_category'][self._json['imageindex_to_labelindex'][k]]) for (k,f) in enumerate(sorted(vipy.util.findimages(self._datadir)))] super().__init__(imlist, id='flowers102') def _cache_annotations(self, outjson='oxford_flowers_102.json'): if not os.path.exists(os.path.join(self._datadir, 'imagelabels.mat')): vipy.downloader.download(ANNO_URL, os.path.join(self._datadir, 'imagelabels.mat'), sha1=None) # Thanks to: https://gist.githubusercontent.com/JosephKJ/94c7728ed1a8e0cd87fe6a029769cde1/raw/403325f5110cb0f3099734c5edb9f457539c77e9/Oxford-102_Flower_dataset_labels.txt category = ['pink primrose', 'hard-leaved pocket orchid', 'canterbury bells', 'sweet pea', 'english marigold', 'tiger lily', 'moon orchid', 'bird of paradise', 'monkshood', 'globe thistle', 'snapdragon', "colt's foot", 'king protea', 'spear thistle', 'yellow iris', 'globe-flower', 'purple coneflower', 'peruvian lily', 'balloon flower', 'giant white arum lily', 'fire lily', 'pincushion flower', 'fritillary', 'red ginger', 'grape hyacinth', 'corn poppy', 'prince of wales feathers', 'stemless gentian', 'artichoke', 'sweet william', 'carnation', 'garden phlox', 'love in the mist', 'mexican aster', 'alpine sea holly', 'ruby-lipped cattleya', 'cape flower', 'great masterwort', 'siam tulip', 'lenten rose', 'barbeton daisy', 'daffodil', 'sword lily', 'poinsettia', 'bolero deep blue', 'wallflower', 'marigold', 'buttercup', 'oxeye daisy', 'common dandelion', 'petunia', 'wild pansy', 'primula', 'sunflower', 'pelargonium', 'bishop of llandaff', 'gaura', 'geranium', 'orange dahlia', 'pink-yellow dahlia?', 'cautleya spicata', 'japanese anemone', 'black-eyed susan', 'silverbush', 'californian poppy', 'osteospermum', 'spring crocus', 'bearded iris', 'windflower', 'tree poppy', 'gazania', 'azalea', 'water lily', 'rose', 'thorn apple', 'morning glory', 'passion flower', 'lotus', 'toad lily', 'anthurium', 'frangipani', 'clematis', 'hibiscus', 'columbine', 'desert-rose', 'tree mallow', 'magnolia', 'cyclamen ', 'watercress', 'canna lily', 'hippeastrum ', 'bee balm', 'ball moss', 'foxglove', 'bougainvillea', 'camellia', 'mallow', 'mexican petunia', 'bromelia', 'blanket flower', 'trumpet creeper', 'blackberry lily', '102'] labelindex_to_category = {str(k):c for (k,c) in enumerate(category, start=1)} # one-indexed # Import, cache and reuse JSON import scipy.io mat = scipy.io.loadmat(os.path.join(self._datadir, 'imagelabels.mat')) imageindex_to_labelindex = [str(c) for c in mat['labels'][0]] return vipy.util.writejson({'imageindex_to_labelindex': imageindex_to_labelindex, 'labelindex_to_category':labelindex_to_category}, outjson)
Ancestors
Inherited members
Dataset
:archive
categories
chunk
class_to_index
classes
classlist
clone
count
countby
density
duration_in_seconds
filter
flatten
id
index_to_class
inverse_frequency_weight
istype
jsondir
label_to_index
list
load
map
merge
minibatch
multilabel_inverse_frequency_weight
num_categories
num_classes
num_labels
percentage
replace
save
set
shuffle
shuffler
sort
split
split_by_videoid
synonym
take
take_per_category
takefilter
takelist
takeone
to_torch
to_torch_tensordir
tohtml
tojsondir
tolist
video_duration_in_seconds
video_montage
zip