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
def personcoarse(INPUT_SIZE, dataaug_args):
nb_classes = 6 + 1
#person: head, torso, upper/lower arms and legs
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_coarse_parts/labels_orig/'
segments_dir = '/storage/cfmata/deeplab/crf_rnn/crfasrnn_keras/data/person_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 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 voc2012(INPUT_SIZE, dataaug_args):
nb_classes = 20 + 1
train_data = 'lst/voc2012_train.txt'
val_data = 'lst/voc2012_val.txt'
image_dir = 'data/pascal_voc12/images_orig/'
label_dir = 'data/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 horsecoarse_small(INPUT_SIZE, dataaug_args, batch_size):
nb_classes = 5 + 1
#horse: head, tail, torso, upper legs, lower legs
train_data = 'lst/horsecoarse_train_small.txt'
val_data = 'lst/horsecoarse_test_small.txt'
image_dir = '/om2/user/cfmata/voc12/train/VOCdevkit/VOC2012/JPEGImages/'
label_dir = 'data/horse_coarse_parts/labels_orig/'
segments_dir = 'data/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