a2a558fc6c1e4b4308e130c77c31816564de7c3a,chainercv/datasets/ade20k/ade20k_semantic_segmentation_dataset.py,ADE20KSemanticSegmentationDataset,__init__,#ADE20KSemanticSegmentationDataset#Any#Any#,44

Before Change

        self.label_paths = sorted(glob.glob(os.path.join(label_dir, "*.png")))

        self.add_getter("img", lambda i: read_image(self.img_paths[i]))
        self.add_getter("iabel", lambda i: read_image(
            self.label_paths[i], dtype=np.int32, color=False)[0])

    def __len__(self):
        return len(self.img_paths)

After Change

        ":math:`[0, \//class - 1]`"
    

    def __init__(self, data_dir="auto", split="train"):
        super(ADE20KSemanticSegmentationDataset, self).__init__()

        if data_dir is "auto":
            data_dir = get_ade20k(root, url)

        if split == "train" or split == "val":
            img_dir = os.path.join(
                data_dir, "ADEChallengeData2016", "images",
                "training" if split == "train" else "validation")
            label_dir = os.path.join(
                data_dir, "ADEChallengeData2016", "annotations",
                "training" if split == "train" else "validation")
        else:
            raise ValueError(
                "Please give \"split\" argument with either \"train\" or "
                "\"val\".")

        self.img_paths = sorted(glob.glob(os.path.join(img_dir, "*.jpg")))
        self.label_paths = sorted(glob.glob(os.path.join(label_dir, "*.png")))

        self.add_getter("img", self._get_image)
        self.add_getter("label", self._get_label)

    def __len__(self):
        return len(self.img_paths)

Instances