feat(opendataset): add dataloader for the CityscapesGTFine dataset

docs/source/reference/api/opendataset.rst

@@ -24,6 +24,7 @@ tensorbay.opendataset
    CCPD
    CCPDGreen
    CIHP
+   CityscapesGTFine
    COCO2017
    COVIDChestXRay
    COVID_CT

tensorbay/opendataset/Cityscapes/__init__.py

@@ -0,0 +1,11 @@
+#!/usr/bin/env python3
+#
+# Copyright 2021 Graviti. Licensed under MIT License.
+#
+# pylint: disable=invalid-name
+
+"""Dataloader of the CityscapesGTFine dataset."""
+
+from tensorbay.opendataset.Cityscapes.loader import CityscapesGTFine
+
+__all__ = ["CityscapesGTFine"]

tensorbay/opendataset/Cityscapes/catalog.json

@@ -0,0 +1,56 @@
+{
+    "SEMANTIC_MASK": {
+        "categories": [
+            { "name": "void", "categoryId": 0 },
+            { "name": "flat", "categoryId": 1 },
+            { "name": "construction", "categoryId": 2 },
+            { "name": "object", "categoryId": 3 },
+            { "name": "nature", "categoryId": 4 },
+            { "name": "sky", "categoryId": 5 },
+            { "name": "human", "categoryId": 6 },
+            { "name": "vehicle", "categoryId": 7 }
+        ]
+    },
+    "INSTANCE_MASK": {
+        "categories": [{ "name": "Background", "categoryId": 0 }]
+    },
+    "POLYGON": {
+        "categories": [
+            { "name": "unlabeled" },
+            { "name": "ego vehicle" },
+            { "name": "rectification border" },
+            { "name": "out of roi" },
+            { "name": "static" },
+            { "name": "dynamic" },
+            { "name": "ground" },
+            { "name": "road" },
+            { "name": "sidewalk" },
+            { "name": "parking" },
+            { "name": "rail track" },
+            { "name": "building" },
+            { "name": "wall" },
+            { "name": "fence" },
+            { "name": "guard rail" },
+            { "name": "bridge" },
+            { "name": "tunnel" },
+            { "name": "pole" },
+            { "name": "polegroup" },
+            { "name": "traffic light" },
+            { "name": "traffic sign" },
+            { "name": "vegetation" },
+            { "name": "terrain" },
+            { "name": "sky" },
+            { "name": "person" },
+            { "name": "rider" },
+            { "name": "car" },
+            { "name": "truck" },
+            { "name": "bus" },
+            { "name": "caravan" },
+            { "name": "trailer" },
+            { "name": "train" },
+            { "name": "motorcycle" },
+            { "name": "bicycle" },
+            { "name": "license plate" }
+        ]
+    }
+}

tensorbay/opendataset/Cityscapes/loader.py

@@ -0,0 +1,107 @@
+#!/usr/bin/env python3
+#
+# Copyright 2021 Graviti. Licensed under MIT License.
+#
+# pylint: disable=invalid-name
+
+"""Dataloader of the CityscapesGTFine dataset."""
+
+import json
+import os
+from glob import glob
+from typing import List
+
+from tensorbay.dataset import Data, Dataset
+from tensorbay.label import InstanceMask, LabeledPolygon, SemanticMask
+
+DATASET_NAME = "CityscapesGTFine"
+_SEGMENT_NAMES = {"test", "train", "val"}
+
+
+def CityscapesGTFine(path: str) -> Dataset:
+    """`CityscapesGTFine <https://www.cityscapes-dataset.com/>`_ dataset.
+
+    The file structure should be like::
+
+        <path>
+            leftImg8bit/
+                test/
+                    berlin/
+                        berlin_000000_000019_leftImg8bit.png
+                        ...
+                    ...
+                train/
+                    aachen/
+                        aachen_000000_000019_leftImg8bit.png
+                        ...
+                    ...
+                val/
+                    frankfurt/
+                        frankfurt_000000_000019_leftImg8bit.png
+                        ...
+                    ...
+                ...
+            gtFine/
+                test/
+                    berlin/
+                        berlin_000000_000019_gtFine_instanceIds.png
+                        berlin_000000_000019_gtFine_labelIds.png
+                        berlin_000000_000019_gtFine_polygons.json
+                        ...
+                    ...
+                train/
+                    aachen/
+                        aachen_000000_000019_gtFine_instanceIds.png
+                        aachen_000000_000019_gtFine_labelIds.png
+                        aachen_000000_000019_gtFine_polygons.json
+                        ...
+                    ...
+                val/
+                    frankfurt/
+                        frankfurt_000000_000019_gtFine_instanceIds.png
+                        frankfurt_000000_000019_gtFine_labelIds.png
+                        frankfurt_000000_000019_gtFine_polygons.json
+                        ...
+                    ...
+            ...
+
+    Arguments:
+        path: The root directory of the dataset.
+
+    Returns:
+        Loaded :class:`~tensorbay.dataset.dataset.Dataset` instance.
+
+    """
+    root_path = os.path.join(os.path.abspath(os.path.expanduser(path)))
+
+    dataset = Dataset(DATASET_NAME)
+    dataset.load_catalog(os.path.join(os.path.dirname(__file__), "catalog.json"))
+
+    for segment_name in _SEGMENT_NAMES:
+        segment = dataset.create_segment(segment_name)
+        for image_path in glob(os.path.join(root_path, "leftImg8bit", segment_name, "*", "*.png")):
+            city = image_path.split("_", 1)[0]
+            image_prefix = image_path.rsplit("_", 1)[0]
+            label_dir = os.path.join(root_path, "gtFine", segment_name, city)
+            data = Data(image_path)
+            # get semantic mask and instance mask
+            label = data.label
+            label.semantic_mask = SemanticMask(
+                os.path.join(label_dir, f"{image_prefix}_gtFine_labelIds.png")
+            )
+            label.instance_mask = InstanceMask(
+                os.path.join(label_dir, f"{image_prefix}_gtFine_instanceIds.png")
+            )
+            # get polygons
+            polygons: List[LabeledPolygon] = []
+            with open(
+                os.path.join(label_dir, f"{image_prefix}_gtFine_polygons.json"),
+                encoding="utf-8",
+            ) as fp:
+                objects = json.load(fp)["objects"]
+            for obj in objects:
+                polygons.append(LabeledPolygon(obj["polygon"], category=obj["label"]))
+            label.polygon = polygons
+
+            segment.append(data)
+    return dataset

tensorbay/opendataset/__init__.py

@@ -17,6 +17,7 @@
 from tensorbay.opendataset.CarConnection import CarConnection
 from tensorbay.opendataset.CCPD import CCPD, CCPDGreen
 from tensorbay.opendataset.CIHP import CIHP
+from tensorbay.opendataset.Cityscapes import CityscapesGTFine
 from tensorbay.opendataset.COCO2017 import COCO2017
 from tensorbay.opendataset.CoinImage import CoinImage
 from tensorbay.opendataset.CompCars import CompCars
@@ -80,6 +81,7 @@
     "CCPD",
     "CCPDGreen",
     "CIHP",
+    "CityscapesGTFine",
     "COCO2017",
     "CoinImage",
     "COVIDChestXRay",