Dataset meta file for some formats (Cityscapes, ImageNet Txt, Pascal VOC and WiderFace)

CHANGELOG.md

@@ -12,8 +12,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   (<https://github.com/openvinotoolkit/datumaro/pull/537>)
 - Datumaro can now be installed on Windows on Python 3.9
   (<https://github.com/openvinotoolkit/datumaro/pull/547>)
-- Import for SYNTHIA dataset format.
+- Import for SYNTHIA dataset format
   (<https://github.com/openvinotoolkit/datumaro/pull/532>)
+- Support for Accuracy Checker dataset meta files in formats
+  (<https://github.com/openvinotoolkit/datumaro/pull/553>)
 
 ### Changed
 - The following formats can now be detected unambiguously:

datumaro/components/converter.py

@@ -13,6 +13,7 @@
 from datumaro.components.dataset import DatasetPatch
 from datumaro.components.extractor import DatasetItem
 from datumaro.components.media import Image
+from datumaro.util.meta_file_util import save_meta_file
 from datumaro.util.os_util import rmtree
 from datumaro.util.scope import on_error_do, scoped
 
@@ -28,6 +29,8 @@ def build_cmdline_parser(cls, **kwargs):
         parser.add_argument('--image-ext', default=None,
             help="Image extension (default: keep or use format default%s)" % \
                 (' ' + cls.DEFAULT_IMAGE_EXT if cls.DEFAULT_IMAGE_EXT else ''))
+        parser.add_argument('--save-dataset-meta', action='store_true',
+            help="Save dataset meta file (default: %(default)s)")
 
         return parser
 
@@ -70,7 +73,7 @@ def apply(self):
         raise NotImplementedError("Should be implemented in a subclass")
 
     def __init__(self, extractor, save_dir, save_images=False,
-            image_ext=None, default_image_ext=None):
+            image_ext=None, default_image_ext=None, save_dataset_meta=False):
         default_image_ext = default_image_ext or self.DEFAULT_IMAGE_EXT
         assert default_image_ext
         self._default_image_ext = default_image_ext
@@ -81,6 +84,8 @@ def __init__(self, extractor, save_dir, save_images=False,
         self._extractor = extractor
         self._save_dir = save_dir
 
+        self._save_dataset_meta = save_dataset_meta
+
         # TODO: refactor this variable.
         # Can be used by a subclass to store the current patch info
         if isinstance(extractor, DatasetPatch.DatasetPatchWrapper):
@@ -144,3 +149,6 @@ def _save_point_cloud(self, item=None, path=None, *,
         if item.point_cloud and osp.isfile(item.point_cloud):
             if item.point_cloud != path:
                 shutil.copyfile(item.point_cloud, path)
+
+    def _save_meta_file(self, path):
+        save_meta_file(path, self._extractor.categories())

datumaro/plugins/cityscapes_format.py

@@ -20,6 +20,9 @@
 from datumaro.util.annotation_util import make_label_id_mapping
 from datumaro.util.image import find_images, load_image, save_image
 from datumaro.util.mask_tools import generate_colormap, paint_mask
+from datumaro.util.meta_file_util import (
+    has_meta_file, is_meta_file, parse_meta_file,
+)
 
 CityscapesLabelMap = OrderedDict([
     ('unlabeled', (0, 0, 0)),
@@ -172,11 +175,15 @@ def __init__(self, path, subset=None):
 
     def _load_categories(self, path):
         label_map = None
-        label_map_path = osp.join(path, CityscapesPath.LABELMAP_FILE)
-        if osp.isfile(label_map_path):
-            label_map = parse_label_map(label_map_path)
+        if has_meta_file(path):
+            label_map = parse_meta_file(path)
         else:
-            label_map = CityscapesLabelMap
+            label_map_path = osp.join(path, CityscapesPath.LABELMAP_FILE)
+            if osp.isfile(label_map_path):
+                label_map = parse_label_map(label_map_path)
+            else:
+                label_map = CityscapesLabelMap
+
         self._labels = [label for label in label_map]
         return make_cityscapes_categories(label_map)
 
@@ -335,11 +342,15 @@ def apply(self):
         self.save_label_map()
 
     def save_label_map(self):
-        path = osp.join(self._save_dir, CityscapesPath.LABELMAP_FILE)
-        labels = self._extractor.categories()[AnnotationType.label]
-        if len(self._label_map) > len(labels):
-            self._label_map.pop('background')
-        write_label_map(path, self._label_map)
+        if self._save_dataset_meta:
+            self._save_meta_file(self._save_dir)
+        else:
+            labels = self._extractor.categories()[AnnotationType.label]
+            if len(self._label_map) > len(labels):
+                self._label_map.pop('background')
+
+            path = osp.join(self._save_dir, CityscapesPath.LABELMAP_FILE)
+            write_label_map(path, self._label_map)
 
     def _load_categories(self, label_map_source):
         if label_map_source == LabelmapType.cityscapes.name:
@@ -370,7 +381,10 @@ def _load_categories(self, label_map_source):
                 sorted(label_map_source.items(), key=lambda e: e[0]))
 
         elif isinstance(label_map_source, str) and osp.isfile(label_map_source):
-            label_map = parse_label_map(label_map_source)
+            if is_meta_file(label_map_source):
+                label_map = parse_meta_file(label_map_source)
+            else:
+                label_map = parse_label_map(label_map_source)
 
         else:
             raise Exception("Wrong labelmap specified, "

datumaro/plugins/imagenet_txt_format.py

@@ -15,6 +15,7 @@
 from datumaro.components.errors import DatasetImportError
 from datumaro.components.extractor import DatasetItem, Importer, SourceExtractor
 from datumaro.components.format_detection import FormatDetectionContext
+from datumaro.util.meta_file_util import has_meta_file, parse_meta_file
 
 
 class ImagenetTxtPath:
@@ -57,9 +58,10 @@ def __init__(self, path: str, *,
             subset = osp.splitext(osp.basename(path))[0]
         super().__init__(subset=subset)
 
+        root_dir = osp.dirname(path)
         if not image_dir:
             image_dir = ImagenetTxtPath.IMAGE_DIR
-        self.image_dir = osp.join(osp.dirname(path), image_dir)
+        self.image_dir = osp.join(root_dir, image_dir)
 
         self._generate_labels = False
 
@@ -70,8 +72,11 @@ def __init__(self, path: str, *,
                 labels = ()
                 self._generate_labels = True
             elif labels_source == _LabelsSource.file:
-                labels = self._parse_labels(
-                    osp.join(osp.dirname(path), labels_file))
+                if has_meta_file(root_dir):
+                    labels = list(parse_meta_file(root_dir).keys())
+                else:
+                    labels = self._parse_labels(
+                        osp.join(root_dir, labels_file))
             else:
                 assert False, "Unhandled labels source %s" % labels_source
         else:
@@ -200,9 +205,12 @@ def apply(self):
             with open(annotation_file, 'w', encoding='utf-8') as f:
                 f.write(annotation)
 
-        labels_file = osp.join(subset_dir, ImagenetTxtPath.LABELS_FILE)
-        with open(labels_file, 'w', encoding='utf-8') as f:
-            f.writelines(l.name + '\n'
-                for l in extractor.categories().get(
-                    AnnotationType.label, LabelCategories())
-            )
+        if self._save_dataset_meta:
+            self._save_meta_file(subset_dir)
+        else:
+            labels_file = osp.join(subset_dir, ImagenetTxtPath.LABELS_FILE)
+            with open(labels_file, 'w', encoding='utf-8') as f:
+                f.writelines(l.name + '\n'
+                    for l in extractor.categories().get(
+                        AnnotationType.label, LabelCategories())
+                )

datumaro/plugins/voc_format/converter.py

@@ -22,10 +22,11 @@
 from datumaro.util.annotation_util import make_label_id_mapping
 from datumaro.util.image import save_image
 from datumaro.util.mask_tools import paint_mask, remap_mask
+from datumaro.util.meta_file_util import has_meta_file
 
 from .format import (
     VocInstColormap, VocPath, VocTask, make_voc_categories, make_voc_label_map,
-    parse_label_map, write_label_map,
+    parse_label_map, parse_meta_file, write_label_map, write_meta_file,
 )
 
 
@@ -530,8 +531,11 @@ def save_segm(self, path, mask, colormap=None):
         save_image(path, mask, create_dir=True)
 
     def save_label_map(self):
-        path = osp.join(self._save_dir, VocPath.LABELMAP_FILE)
-        write_label_map(path, self._label_map)
+        if self._save_dataset_meta:
+            write_meta_file(self._save_dir, self._label_map)
+        else:
+            path = osp.join(self._save_dir, VocPath.LABELMAP_FILE)
+            write_label_map(path, self._label_map)
 
     def _load_categories(self, label_map_source):
         if label_map_source == LabelmapType.voc.name:
@@ -562,7 +566,10 @@ def _load_categories(self, label_map_source):
                 sorted(label_map_source.items(), key=lambda e: e[0]))
 
         elif isinstance(label_map_source, str) and osp.isfile(label_map_source):
-            label_map = parse_label_map(label_map_source)
+            if has_meta_file(label_map_source):
+                label_map = parse_meta_file(label_map_source)
+            else:
+                label_map = parse_label_map(label_map_source)
 
         else:
             raise Exception("Wrong labelmap specified: '%s', "

datumaro/plugins/voc_format/extractor.py

@@ -15,9 +15,11 @@
 from datumaro.components.media import Image
 from datumaro.util.image import find_images
 from datumaro.util.mask_tools import invert_colormap, lazy_mask
+from datumaro.util.meta_file_util import has_meta_file
 
 from .format import (
     VocInstColormap, VocPath, VocTask, make_voc_categories, parse_label_map,
+    parse_meta_file,
 )
 
 _inverse_inst_colormap = invert_colormap(VocInstColormap)
@@ -48,12 +50,15 @@ def _get_label_id(self, label):
         assert label_id is not None, label
         return label_id
 
-    @staticmethod
-    def _load_categories(dataset_path):
+    def _load_categories(self, dataset_path):
         label_map = None
-        label_map_path = osp.join(dataset_path, VocPath.LABELMAP_FILE)
-        if osp.isfile(label_map_path):
-            label_map = parse_label_map(label_map_path)
+        if has_meta_file(dataset_path):
+            label_map = parse_meta_file(dataset_path)
+        else:
+            label_map_path = osp.join(dataset_path, VocPath.LABELMAP_FILE)
+            if osp.isfile(label_map_path):
+                label_map = parse_label_map(label_map_path)
+
         return make_voc_categories(label_map)
 
     def _load_subset_list(self, subset_path):

datumaro/plugins/voc_format/format.py

@@ -5,12 +5,16 @@
 from collections import OrderedDict
 from enum import Enum, auto
 from itertools import chain
+import json
+import os.path as osp
 
 import numpy as np
 
 from datumaro.components.annotation import (
     AnnotationType, LabelCategories, MaskCategories,
 )
+from datumaro.util import find
+from datumaro.util.meta_file_util import get_meta_file
 
 
 class VocTask(Enum):
@@ -157,6 +161,33 @@ def parse_label_map(path):
             label_map[name] = [color, parts, actions]
     return label_map
 
+def parse_meta_file(path):
+    meta_file = path
+    if osp.isdir(path):
+        meta_file = get_meta_file(path)
+
+    with open(meta_file) as f:
+        dataset_meta = json.load(f)
+
+    label_map = OrderedDict()
+    parts = dataset_meta.get('parts', {})
+    actions = dataset_meta.get('actions', {})
+
+    for i, label in enumerate(dataset_meta.get('labels', [])):
+        label_map[label] = [None, parts.get(str(i), []), actions.get(str(i), [])]
+
+    colors = dataset_meta.get('segmentation_colors', [])
+
+    for i, label in enumerate(dataset_meta.get('label_map', {}).values()):
+        if label not in label_map:
+            label_map[label] = [None, [], []]
+
+        if any(colors) and colors[i] is not None:
+            label_map[label][0] = tuple(colors[i])
+
+
+    return label_map
+
 def write_label_map(path, label_map):
     with open(path, 'w', encoding='utf-8') as f:
         f.write('# label:color_rgb:parts:actions\n')
@@ -171,6 +202,47 @@ def write_label_map(path, label_map):
 
             f.write('%s\n' % ':'.join([label_name, color_rgb, parts, actions]))
 
+def write_meta_file(path, label_map):
+    dataset_meta = {}
+
+    labels = []
+    labels_dict = {}
+    segmentation_colors = []
+    parts = {}
+    actions = {}
+
+    for i, (label_name, label_desc) in enumerate(label_map.items()):
+        labels.append(label_name)
+        if label_desc[0]:
+            labels_dict[str(i)] = label_name
+            segmentation_colors.append(
+                [int(label_desc[0][0]), int(label_desc[0][1]), int(label_desc[0][2])])
+
+        parts[str(i)] = label_desc[1]
+        actions[str(i)] = label_desc[2]
+
+    dataset_meta['labels'] = labels
+
+    if any(segmentation_colors):
+        dataset_meta['label_map'] = labels_dict
+        dataset_meta['segmentation_colors'] = segmentation_colors
+
+        bg_label = find(label_map.items(), lambda x: x[1] == (0, 0, 0))
+        if bg_label is not None:
+            dataset_meta['background_label'] = str(bg_label[0])
+
+    if any(parts):
+        dataset_meta['parts'] = parts
+
+    if any(actions):
+        dataset_meta['actions'] = actions
+
+    meta_file = get_meta_file(path)
+
+    with open(meta_file, 'w') as f:
+        json.dump(dataset_meta, f)
+
+
 def make_voc_categories(label_map=None):
     if label_map is None:
         label_map = make_voc_label_map()

datumaro/plugins/widerface_format.py

@@ -13,6 +13,7 @@
 from datumaro.components.extractor import DatasetItem, Importer, SourceExtractor
 from datumaro.components.format_detection import FormatDetectionContext
 from datumaro.util import str_to_bool
+from datumaro.util.meta_file_util import has_meta_file, parse_meta_file
 
 
 class WiderFacePath:
@@ -44,8 +45,13 @@ def __init__(self, path, subset=None):
 
     def _load_categories(self):
         label_cat = LabelCategories()
-        path = osp.join(self._dataset_dir, WiderFacePath.LABELS_FILE)
-        if osp.isfile(path):
+        if has_meta_file(self._dataset_dir):
+            labels = parse_meta_file(self._dataset_dir).keys()
+            for label in labels:
+                label_cat.add(label)
+        elif osp.isfile(osp.join(self._dataset_dir,
+                WiderFacePath.LABELS_FILE)):
+            path = osp.join(self._dataset_dir, WiderFacePath.LABELS_FILE)
             with open(path, encoding='utf-8') as labels_file:
                 for line in labels_file:
                     label_cat.add(line.strip())
@@ -157,9 +163,12 @@ def apply(self):
 
         label_categories = self._extractor.categories()[AnnotationType.label]
 
-        labels_path = osp.join(save_dir, WiderFacePath.LABELS_FILE)
-        with open(labels_path, 'w', encoding='utf-8') as f:
-            f.write('\n'.join(label.name for label in label_categories))
+        if self._save_dataset_meta:
+           self._save_meta_file(save_dir)
+        else:
+            labels_path = osp.join(save_dir, WiderFacePath.LABELS_FILE)
+            with open(labels_path, 'w', encoding='utf-8') as f:
+                f.write('\n'.join(label.name for label in label_categories))
 
         for subset_name, subset in self._extractor.subsets().items():
             subset_dir = osp.join(save_dir,