def voc2012dbg(INPUT_SIZE,dataaug_args):
nb_classes = 20 + 1
train_data = 'lst/voc2012_train_dbg.txt'
val_data = 'lst/voc2012_val_dbg.txt'
image_dir = '/storage/gby/datasets/pascal_voc12/images_orig/'
label_dir = '/storage/gby/datasets/pascal_voc12/labels_orig/'
segments_dir = ''
ds = split_from_list(train_data, val_data, image_dir, label_dir, INPUT_SIZE, nb_classes, dataaug_args)
ds.segments_dir = segments_dir
ds.train_list = train_data
ds.test_list = val_data
ds.datagen_train = generate_arrays_from_file(train_data, image_dir, label_dir, INPUT_SIZE, nb_classes, dataaug_args)
ds.datagen_test = generate_arrays_from_file(val_data, image_dir, label_dir, INPUT_SIZE, nb_classes, None)
return ds
def personfine(INPUT_SIZE, dataaug_args):
nb_classes = 24+1
train_data = 'lst/personcoarse_train.txt'
val_data = 'lst/personcoarse_test.txt'
#image_dir = "/storage/gby/datasets/horse_coarse_parts/images_orig/"
image_dir = '/storage/gby/datasets/pascal_voc12/images_orig/'
label_dir = '/storage/gby/datasets/person_fine_parts/labels_orig/'
segments_dir = ''
ds = split_from_list(train_data, val_data, image_dir, label_dir, INPUT_SIZE, nb_classes, dataaug_args)
ds.segments_dir = segments_dir
ds.train_list = train_data
ds.test_list = val_data
ds.datagen_train = generate_arrays_from_file(train_data, image_dir, label_dir, INPUT_SIZE,nb_classes, dataaug_args)
ds.datagen_test = generate_arrays_from_file(val_data, image_dir, label_dir, INPUT_SIZE, nb_classes, None)
return ds
def horsecoarsedbg(INPUT_SIZE,dataaug_args):
nb_classes = 5+1
#horse: head, tail, torso, upper legs, lower legs
train_data = 'lst/horsecoarse_train_dbg.txt'
val_data = 'lst/horsecoarse_test_dbg.txt'
#image_dir = "/storage/gby/datasets/horse_coarse_parts/images_orig/"
image_dir = '/storage/gby/datasets/pascal_voc12/images_orig/'
label_dir = '/storage/gby/datasets/horse_coarse_parts/labels_orig/'
segments_dir = '/storage/gby/datasets/horse_coarse_parts/sp_seg/'
ds = split_from_list(train_data, val_data, image_dir, label_dir, INPUT_SIZE, nb_classes, dataaug_args)
ds.segments_dir = segments_dir
ds.train_list = train_data
ds.test_list = val_data
ds.datagen_train = generate_arrays_from_file(train_data, image_dir, label_dir, INPUT_SIZE,nb_classes, dataaug_args)
ds.datagen_test = generate_arrays_from_file(val_data, image_dir, label_dir, INPUT_SIZE, nb_classes, None)
return ds
def streets(INPUT_SIZE, dataaug_args):
nb_classes = 11+1
train_data = 'lst/streets_train.txt' # to fix
val_data = 'lst/streets_val.txt' # to fix
image_dir = '/storage/gby/datasets/streets/all_imgs/'
label_dir = '/storage/gby/datasets/streets/all_labels/'
segments_dir = ''
#train_rate = 0.85
#allow_randomness = False
#ds = split_train_test(image_dir,label_dir, train_rate, allow_randomness, INPUT_SIZE, nb_classes)
ds = split_from_list(train_data, val_data, image_dir, label_dir, INPUT_SIZE, nb_classes, dataaug_args)
ds.segments_dir = segments_dir
ds.train_list = train_data
ds.test_list = val_data
ds.datagen_train = generate_arrays_from_file(train_data, image_dir, label_dir, INPUT_SIZE, nb_classes, dataaug_args)
ds.datagen_test = generate_arrays_from_file(val_data, image_dir, label_dir, INPUT_SIZE, nb_classes, None)
return ds