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hub / github.com/NVIDIA/semantic-segmentation / __init__

Method __init__

datasets/mapillary.py:49–83  ·  view source on GitHub ↗
(self, mode, quality='semantic', joint_transform_list=None,
                 img_transform=None, label_transform=None, eval_folder=None)

Source from the content-addressed store, hash-verified

47 color_mapping = []
48
49 def __init__(self, mode, quality='semantic', joint_transform_list=None,
50 img_transform=None, label_transform=None, eval_folder=None):
51
52 super(Loader, self).__init__(quality=quality,
53 mode=mode,
54 joint_transform_list=joint_transform_list,
55 img_transform=img_transform,
56 label_transform=label_transform)
57
58 root = cfg.DATASET.MAPILLARY_DIR
59 config_fn = os.path.join(root, 'config.json')
60 self.fill_colormap_and_names(config_fn)
61
62 ######################################################################
63 # Assemble image lists
64 ######################################################################
65 if mode == 'folder':
66 self.all_imgs = make_dataset_folder(eval_folder)
67 else:
68 splits = {'train': 'training',
69 'val': 'validation',
70 'test': 'testing'}
71 split_name = splits[mode]
72 img_ext = 'jpg'
73 mask_ext = 'png'
74 img_root = os.path.join(root, split_name, 'images')
75 mask_root = os.path.join(root, split_name, 'labels')
76 self.all_imgs = self.find_images(img_root, mask_root, img_ext,
77 mask_ext)
78 logx.msg('all imgs {}'.format(len(self.all_imgs)))
79 self.centroids = uniform.build_centroids(self.all_imgs,
80 self.num_classes,
81 self.train,
82 cv=cfg.DATASET.CV)
83 self.build_epoch()
84
85 def fill_colormap_and_names(self, config_fn):
86 """

Callers

nothing calls this directly

Calls 4

make_dataset_folderFunction · 0.90
find_imagesMethod · 0.80
build_epochMethod · 0.80

Tested by

no test coverage detected