Merge branch 'develop' into feat_correct

CHANGELOG.md

@@ -15,7 +15,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   (<https://github.com/openvinotoolkit/datumaro/pull/996>)
 - Add VocInstanceSegmentationImporter and VocInstanceSegmentationExporter
   (<https://github.com/openvinotoolkit/datumaro/pull/997>)
-- Add Corrector transformation
+- Add Segment Anything data format support
+  (<https://github.com/openvinotoolkit/datumaro/pull/1005>)
+- Add Correct transformation
   (<https://github.com/openvinotoolkit/datumaro/pull/1006>)
 
 ### Enhancements
@@ -27,6 +29,8 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   (<https://github.com/openvinotoolkit/datumaro/pull/981>)
 - Add MOT and MOTS data format docs
   (<https://github.com/openvinotoolkit/datumaro/pull/999>)
+- Improve RemoveAnnotations to remove specific annotations with ids
+  (<https://github.com/openvinotoolkit/datumaro/pull/1004>)
 
 ### Bug fixes
 - Fix Mapillary Vistas data format

datumaro/components/format_detection.py

@@ -265,6 +265,20 @@ def require_files(
 
         return sorted(self._require_files_iter(pattern, exclude_fnames=exclude_fnames))
 
+    def require_files_iter(
+        self,
+        pattern: str,
+        *,
+        exclude_fnames: Union[str, Collection[str]] = (),
+    ) -> Iterator[str]:
+        """
+        Same as `require_files`, but returns a generator.
+        """
+
+        self._start_requirement("require_files_iter")
+
+        return self._require_files_iter(pattern, exclude_fnames=exclude_fnames)
+
     def _require_files_iter(
         self,
         pattern: str,

datumaro/plugins/data_formats/segment_anything/__init__.py

@@ -0,0 +1,9 @@
+# Copyright (C) 2023 Intel Corporation
+#
+# SPDX-License-Identifier: MIT
+
+from .base import SegmentAnythingBase
+from .exporter import SegmentAnythingExporter
+from .importer import SegmentAnythingImporter
+
+__all__ = ["SegmentAnythingBase", "SegmentAnythingImporter", "SegmentAnythingExporter"]

datumaro/plugins/data_formats/segment_anything/base.py

@@ -0,0 +1,169 @@
+# Copyright (C) 2023 Intel Corporation
+#
+# SPDX-License-Identifier: MIT
+
+import os.path as osp
+from glob import glob
+from inspect import isclass
+from typing import Any, Dict, Optional, Tuple, Type, TypeVar, Union
+
+from datumaro.components.annotation import Bbox, RleMask
+from datumaro.components.dataset_base import DatasetItem, SubsetBase
+from datumaro.components.errors import (
+    DatasetImportError,
+    InvalidAnnotationError,
+    InvalidFieldTypeError,
+    MissingFieldError,
+)
+from datumaro.components.importer import ImportContext
+from datumaro.components.media import Image
+from datumaro.util import NOTSET, parse_json_file
+
+T = TypeVar("T")
+
+
+def parse_field(
+    ann: Dict[str, Any],
+    key: str,
+    cls: Union[Type[T], Tuple[Type, ...]],
+    default: Any = NOTSET,
+) -> Any:
+    value = ann.get(key, NOTSET)
+    if value is NOTSET:
+        if default is not NOTSET:
+            return default
+        raise MissingFieldError(key)
+    elif not isinstance(value, cls):
+        cls = (cls,) if isclass(cls) else cls
+        raise InvalidFieldTypeError(
+            key, actual=str(type(value)), expected=tuple(str(t) for t in cls)
+        )
+    return value
+
+
+class SegmentAnythingBase(SubsetBase):
+    def __init__(
+        self,
+        path: str,
+        *,
+        subset: Optional[str] = None,
+        ctx: Optional[ImportContext] = None,
+    ):
+        if not osp.isdir(path):
+            raise DatasetImportError(f"path {path} must be directory.")
+        self._path = path
+
+        super().__init__(subset=subset, ctx=ctx)
+        self._items = self._load_items()
+
+    def _load_items(self):
+        pbar = self._ctx.progress_reporter
+        items = []
+        for annotation_file in pbar.iter(
+            glob(osp.join(self._path, "*.json")),
+            desc=f"Parsing data in {osp.basename(self._path)}",
+        ):
+            image_id = None
+            annotations = []
+            item_kwargs = {
+                "id": None,
+                "subset": self._subset,
+                "media": None,
+                "annotations": [],
+                "attributes": {},
+            }
+
+            try:
+                contents = parse_json_file(annotation_file)
+                image_info = contents["image"]
+                annotations = contents["annotations"]
+
+                image_id = parse_field(image_info, "image_id", int)
+                item_kwargs["attributes"]["id"] = image_id
+
+                image_size = (
+                    parse_field(image_info, "height", int, default=None),
+                    parse_field(image_info, "width", int, default=None),
+                )
+                if any(i is None for i in image_size):
+                    image_size = None
+                file_name = parse_field(image_info, "file_name", str)
+
+                item_kwargs["id"] = osp.splitext(file_name)[0]
+                item_kwargs["media"] = Image.from_file(
+                    path=osp.join(self._path, file_name), size=image_size
+                )
+            except Exception as e:
+                self._ctx.error_policy.report_item_error(e, item_id=(image_id, self._subset))
+
+            try:
+                for annotation in annotations:
+                    anno_id = parse_field(annotation, "id", int)
+                    attributes = {
+                        "predicted_iou": parse_field(
+                            annotation,
+                            "predicted_iou",
+                            float,
+                            0.0,
+                        ),
+                        "stability_score": parse_field(
+                            annotation,
+                            "stability_score",
+                            float,
+                            0.0,
+                        ),
+                        "point_coords": parse_field(
+                            annotation,
+                            "point_coords",
+                            list,
+                            [[]],
+                        ),
+                        "crop_box": parse_field(annotation, "crop_box", list, []),
+                    }
+
+                    group = anno_id  # make sure all tasks' annotations are merged
+
+                    segmentation = parse_field(annotation, "segmentation", dict, None)
+                    if segmentation is None:
+                        raise InvalidAnnotationError("'segmentation' label is not found.")
+                    item_kwargs["annotations"].append(
+                        RleMask(
+                            rle=segmentation,
+                            label=None,
+                            id=anno_id,
+                            attributes=attributes,
+                            group=group,
+                        )
+                    )
+
+                    bbox = parse_field(annotation, "bbox", list, None)
+                    if bbox is None:
+                        bbox = item_kwargs["annotations"][-1].get_bbox().tolist()
+
+                    if len(bbox) > 0:
+                        if len(bbox) != 4:
+                            raise InvalidAnnotationError(
+                                f"Bbox has wrong value count {len(bbox)}. Expected 4 values."
+                            )
+                        x, y, w, h = bbox
+                        item_kwargs["annotations"].append(
+                            Bbox(
+                                x,
+                                y,
+                                w,
+                                h,
+                                label=None,
+                                id=anno_id,
+                                attributes=attributes,
+                                group=group,
+                            )
+                        )
+            except Exception as e:
+                self._ctx.error_policy.report_annotation_error(e, item_id=(image_id, self._subset))
+
+            try:
+                items.append(DatasetItem(**item_kwargs))
+            except Exception as e:
+                self._ctx.error_policy.report_item_error(e, item_id=(image_id, self._subset))
+
+        return items

datumaro/plugins/data_formats/segment_anything/exporter.py

@@ -0,0 +1,163 @@
+# Copyright (C) 2023 Intel Corporation
+#
+# SPDX-License-Identifier: MIT
+
+
+import logging as log
+import os
+import os.path as osp
+from itertools import chain
+from typing import List, Union
+
+from pycocotools import mask as mask_utils
+
+from datumaro.components.annotation import AnnotationType, Ellipse, Polygon
+from datumaro.components.errors import MediaTypeError
+from datumaro.components.exporter import Exporter
+from datumaro.components.media import Image
+from datumaro.util import annotation_util as anno_tools
+from datumaro.util import dump_json_file, mask_tools
+
+
+class SegmentAnythingExporter(Exporter):
+    DEFAULT_IMAGE_EXT = ".jpg"
+
+    _polygon_types = {AnnotationType.polygon, AnnotationType.ellipse}
+    _allowed_types = {
+        AnnotationType.bbox,
+        AnnotationType.polygon,
+        AnnotationType.mask,
+        AnnotationType.ellipse,
+    }
+
+    def __init__(
+        self,
+        extractor,
+        save_dir,
+        **kwargs,
+    ):
+        super().__init__(extractor, save_dir, **kwargs)
+
+    @staticmethod
+    def find_instance_anns(annotations):
+        return [a for a in annotations if a.type in SegmentAnythingExporter._allowed_types]
+
+    @classmethod
+    def find_instances(cls, annotations):
+        return anno_tools.find_instances(cls.find_instance_anns(annotations))
+
+    def get_annotation_info(self, group, img_width, img_height):
+        boxes = [a for a in group if a.type == AnnotationType.bbox]
+        polygons: List[Union[Polygon, Ellipse]] = [
+            a for a in group if a.type in self._polygon_types
+        ]
+        masks = [a for a in group if a.type == AnnotationType.mask]
+
+        anns = boxes + polygons + masks
+        leader = anno_tools.find_group_leader(anns)
+        if len(boxes) > 0:
+            bbox = anno_tools.max_bbox(boxes)
+        else:
+            bbox = anno_tools.max_bbox(anns)
+        polygons = [p.as_polygon() for p in polygons]
+
+        mask = None
+        if polygons:
+            mask = mask_tools.rles_to_mask(polygons, img_width, img_height)
+        if masks:
+            masks = (m.image for m in masks)
+            if mask is not None:
+                masks = chain(masks, [mask])
+            mask = mask_tools.merge_masks(masks)
+        if mask is None:
+            return None
+        mask = mask_tools.mask_to_rle(mask)
+
+        segmentation = {
+            "counts": list(int(c) for c in mask["counts"]),
+            "size": list(int(c) for c in mask["size"]),
+        }
+        rles = mask_utils.frPyObjects(segmentation, img_height, img_width)
+        if isinstance(rles["counts"], bytes):
+            rles["counts"] = rles["counts"].decode()
+        area = mask_utils.area(rles)
+
+        annotation_data = {
+            "id": leader.group,
+            "segmentation": rles,
+            "bbox": bbox,
+            "area": area,
+            "predicted_iou": max(ann.attributes.get("predicted_iou", 0.0) for ann in anns),
+            "stability_score": max(ann.attributes.get("stability_score", 0.0) for ann in anns),
+            "crop_box": anno_tools.max_bbox([ann.attributes.get("crop_box", []) for ann in anns]),
+            "point_coords": list(
+                set(
+                    tuple(point_coord)
+                    for ann in anns
+                    for point_coord in ann.attributes.get("point_coords", [[]])
+                )
+            ),
+        }
+        return annotation_data
+
+    def apply(self):
+        if self._extractor.media_type() and not issubclass(self._extractor.media_type(), Image):
+            raise MediaTypeError("Media type is not an image")
+
+        os.makedirs(self._save_dir, exist_ok=True)
+
+        subsets = self._extractor.subsets()
+        pbars = self._ctx.progress_reporter.split(len(subsets))
+
+        max_image_id = 1
+        for pbar, (subset_name, subset) in zip(pbars, subsets.items()):
+            for item in pbar.iter(subset, desc=f"Exporting {subset_name}"):
+                try:
+                    # make sure file_name is flat
+                    file_name = self._make_image_filename(item).replace("/", "__")
+                    try:
+                        image_id = int(item.attributes.get("id", max_image_id))
+                    except ValueError:
+                        image_id = max_image_id
+                    max_image_id += 1
+
+                    if not item.media or not item.media.size:
+                        log.warning(
+                            f"Item '{item.id}': skipping writing instances since no image info available"
+                        )
+                        continue
+
+                    height, width = item.media.size
+                    json_data = {
+                        "image": {
+                            "image_id": image_id,
+                            "file_name": file_name,
+                            "height": height,
+                            "width": width,
+                        },
+                        "annotations": [],
+                    }
+
+                    instances = self.find_instances(item.annotations)
+                    annotations = [self.get_annotation_info(i, width, height) for i in instances]
+                    annotations = [i for i in annotations if i is not None]
+                    if not annotations:
+                        log.warning(
+                            f"Item '{item.id}': skipping writing instances since no annotation available"
+                        )
+                        continue
+                    json_data["annotations"] = annotations
+
+                    dump_json_file(
+                        os.path.join(self._save_dir, osp.splitext(file_name)[0] + ".json"),
+                        json_data,
+                    )
+
+                    if self._save_media:
+                        self._save_image(
+                            item,
+                            path=osp.abspath(osp.join(self._save_dir, file_name)),
+                        )
+
+                except Exception as e:
+                    self._ctx.error_policy.report_item_error(e, item_id=(item.id, item.subset))