Merge pull request #11 from aoxolotl/bboxAPI

Add API for BoundingBox annotation

datatorch/api/entity/sources/image/bounding_box.py

@@ -1,6 +1,9 @@
 from ..source import Source
 
+from typing import Optional
 from .typings import Point2D
+from datatorch.api import ApiClient
+from ....entity.annotation import Annotation
 
 
 __all__ = "BoundingBox"
@@ -32,3 +35,64 @@ def bottom_right(self) -> Point2D:
     @property
     def size(self) -> float:
         return self.width * self.height
+
+    def from_points(self, top_left: Point2D, bottom_right: Point2D):
+        self.x = top_left[0]
+        self.y = top_left[1]
+        self.width = bottom_right[0] - top_left[0]
+        self.height = bottom_right[1] - top_left[1]
+
+    def create_new_bbox(self, label_id: str, file_id: str):
+        print("Creating new annotation")
+        new_annotation = Annotation()
+        new_annotation.label_id = label_id
+        new_annotation.file_id = file_id
+        new_annotation.create(ApiClient())
+
+        self.annotation_id = new_annotation.id
+        self.create(ApiClient())
+        print("BoundingBox created with annotation", new_annotation.id, flush=True)
+
+    def combine_bbox(self, annotation):
+        if self.annotation_id is None:
+            raise ValueError("No annotation id set")
+
+        self.annotation_id = annotation.id
+        existing_bbox = next(
+            x for x in annotation.get("sources") if x.get("type") == "PaperBox"
+        )
+
+        # Merge self and existing bbox
+        top_left = (
+            min(self.x, existing_bbox["x"]),
+            min(self.y, existing_bbox["y"]),
+        )
+        bottom_right = (
+            max(self.bottom_right[0], existing_bbox["x"] + existing_bbox["width"]),
+            max(self.bottom_right[1], existing_bbox["y"] + existing_bbox["height"]),
+        )
+
+        self.from_points(top_left, bottom_right)
+
+        self.save(ApiClient())
+        print(
+            f"Updated bounding box for annotation {annotation.id}",
+            flush=True,
+        )
+
+    def create_bbox_from_points(
+        self,
+        top_left: Point2D,
+        bottom_right: Point2D,
+        annotation=None,
+        label_id: Optional[str] = None,
+        file_id: Optional[str] = None,
+    ):
+        if annotation is None and (label_id is None or file_id is None):
+            raise ValueError("Either annotation or label_id and file_id must be set")
+
+        self.from_points(top_left, bottom_right)
+        if annotation:
+            self.combine_bbox(annotation)
+        else:
+            self.create_new_bbox(label_id, file_id)

datatorch/api/entity/sources/image/segmentations.py

@@ -64,12 +64,13 @@ def combine_segmentations(self, annotation):
             for polygon in multi:
                 self.path_data.append(list(polygon.exterior.coords[:-1]))
 
+        self.save(ApiClient())
         print(
             f"Updated segmentation for annotation {annotation.id}",
             flush=True,
         )
 
-    def create_new_annotation(self, label_id: str, file_id: str):
+    def create_new_segmentation(self, label_id: str, file_id: str):
         print("Creating new annotation")
         new_annotation = Annotation()
         new_annotation.label_id = label_id
@@ -79,7 +80,24 @@ def create_new_annotation(self, label_id: str, file_id: str):
 
         self.annotation_id = annotation_id
         self.create(ApiClient())
-        print("Segmentation created")
+        print("Segmentation created with annotation", annotation_id, flush=True)
+
+    def create_segmentation_from_mask(
+        self,
+        mask: np.array,
+        simplify: int = 0,
+        annotation=None,
+        label_id: Optional[str] = None,
+        file_id: Optional[str] = None,
+    ):
+        if annotation is None and (label_id is None or file_id is None):
+            raise ValueError("Either annotation or label_id and file_id must be set")
+
+        self.from_mask(mask, simplify=simplify)
+        if annotation:
+            self.combine_segmentations(annotation)
+        else:
+            self.create_new_segmentation(label_id, file_id)
 
     def to_mask(self) -> np.array:
-        pass
+        raise NotImplementedError("to_mask not implemented")

setup.py

@@ -32,7 +32,7 @@
 
 setup(
     name="datatorch",
-    version="0.4.8.0",
+    version="0.4.8.1",
     description="A CLI and library for interacting with DataTorch.",
     author="DataTorch",
     author_email="[email protected]",