converter demo working

Author: Matt Sokoloff

examples/annotation_types/annotation_type_basics.ipynb

@@ -1,9 +1,9 @@
 name = "labelbox"
 __version__ = "2.7.0"
 
+from labelbox.schema.project import Project
 from labelbox.client import Client
 from labelbox.schema.bulk_import_request import BulkImportRequest
-from labelbox.schema.project import Project
 from labelbox.schema.dataset import Dataset
 from labelbox.schema.data_row import DataRow
 from labelbox.schema.label import Label

examples/annotation_types/converters.ipynb

@@ -5,7 +5,7 @@
 
 from tqdm import tqdm
 
-from labelbox import OntologyBuilder
+from labelbox.schema import ontology
 from labelbox.orm.model import Entity
 from ..generator import PrefetchGenerator
 from .label import Label
@@ -25,7 +25,8 @@ def __init__(self, data: Iterable[Label]):
         self._index = 0
 
     def assign_schema_ids(
-            self, ontology_builder: OntologyBuilder) -> "LabelCollection":
+            self,
+            ontology_builder: "ontology.OntologyBuilder") -> "LabelCollection":
         """
         Adds schema ids to all FeatureSchema objects in the Labels.
         This is necessary for MAL.
@@ -166,7 +167,8 @@ def as_collection(self) -> "LabelCollection":
         return LabelCollection(data=list(self))
 
     def assign_schema_ids(
-            self, ontology_builder: OntologyBuilder) -> "LabelGenerator":
+            self,
+            ontology_builder: "ontology.OntologyBuilder") -> "LabelGenerator":
 
         def _assign_ids(label: Label):
             label.assign_schema_ids(ontology_builder)

labelbox/__init__.py

@@ -1,9 +1,10 @@
-from typing import Callable, Tuple, Union
+from typing import Callable, Optional, Tuple, Union
 
 import numpy as np
 from pydantic.class_validators import validator
 from rasterio.features import shapes
 from shapely.geometry import MultiPolygon, shape
+import cv2
 
 from ..data.raster import RasterData
 from .geometry import Geometry
@@ -25,21 +26,31 @@ def geometry(self):
             if val >= 1)
         return MultiPolygon(polygons).__geo_interface__
 
-    def raster(self, binary=False) -> np.ndarray:
+    def raster(self,
+               height: Optional[int] = None,
+               width: Optional[int] = None,
+               binary=False) -> np.ndarray:
         """
         Removes all pixels from the segmentation mask that do not equal self.color
 
+        Args:
+            height:
+
         Returns:
             np.ndarray representing only this object
         """
         mask = self.mask.data
         if len(mask.shape) == 2:
             mask = np.expand_dims(mask, axis=-1)
         mask = np.alltrue(mask == self.color, axis=2).astype(np.uint8)
+        if height is not None or width is not None:
+            mask = cv2.resize(mask,
+                              (width or mask.shape[1], height or mask.shape[0]))
+
         if binary:
             return mask
         elif isinstance(self.color, int):
-            return mask * self.color
+            mask = mask * self.color
         else:
             color_image = np.zeros((mask.shape[0], mask.shape[1], 3),
                                    dtype=np.uint8)

labelbox/data/annotation_types/collection.py

@@ -2,7 +2,7 @@
 
 from pydantic import BaseModel
 
-from labelbox import Classification as OClassification, OntologyBuilder, Option
+from labelbox.schema import ontology
 from labelbox.orm.model import Entity
 from .classification import ClassificationAnswer
 from .data import VideoData, TextData, RasterData
@@ -77,7 +77,8 @@ def create_data_row(self, dataset: "Entity.Dataset",
             self.data.external_id = data_row.external_id
         return self
 
-    def assign_schema_ids(self, ontology_builder: OntologyBuilder) -> "Label":
+    def assign_schema_ids(
+            self, ontology_builder: ontology.OntologyBuilder) -> "Label":
         """
         Adds schema ids to all FeatureSchema objects in the Labels.
         This is necessary for MAL.
@@ -104,18 +105,18 @@ def assign_schema_ids(self, ontology_builder: OntologyBuilder) -> "Label":
         return self
 
     def _get_feature_schema_lookup(
-        self, ontology_builder: OntologyBuilder
+        self, ontology_builder: ontology.OntologyBuilder
     ) -> Tuple[Dict[str, str], Dict[str, str]]:
         tool_lookup = {}
         classification_lookup = {}
 
         def flatten_classification(classifications):
             for classification in classifications:
-                if isinstance(classification, OClassification):
+                if isinstance(classification, ontology.OClassification):
                     classification_lookup[
                         classification.
                         instructions] = classification.feature_schema_id
-                elif isinstance(classification, Option):
+                elif isinstance(classification, ontology.Option):
                     classification_lookup[
                         classification.value] = classification.feature_schema_id
                 else:

labelbox/data/annotation_types/geometry/mask.py

@@ -53,6 +53,9 @@ def __init__(self,
             thread.daemon = True
             thread.start()
 
+        # Can only iterate over once it the queue.get hangs forever.
+        self.done = False
+
     def _process(self, value) -> Any:
         raise NotImplementedError("Abstract method needs to be implemented")
 
@@ -73,12 +76,15 @@ def __iter__(self):
         return self
 
     def __next__(self) -> Any:
+        if self.done:
+            raise StopIteration
         value = self.queue.get()
         while value is None:
             self.completed_threads += 1
             if self.completed_threads == self.max_concurrency:
                 for thread in self.threads:
                     thread.join()
+                self.done = True
                 raise StopIteration
             value = self.queue.get()
         return value

labelbox/data/annotation_types/label.py

@@ -79,7 +79,7 @@ def __init__(self, examples, client):
     def _process(self, value):
         if 'frames' in value['Label']:
             req = self._request(value)
-            value['Label'] = ndjson.loads(req.text)
+            value['Label'] = ndjson.loads(req)
             return value
 
     @retry.Retry(predicate=retry.if_exception_type(HTTPError))

labelbox/data/generator.py

@@ -148,6 +148,7 @@ def to_common(self) -> Label:
         else:
             annotations = self.label.to_common()
             data = self._infer_media_type()
+            print(data)
 
         return Label(data=data,
                      annotations=annotations,

labelbox/data/serialization/labelbox_v1/converter.py

@@ -4,11 +4,13 @@
 
 from typing import Any, Dict, List, Optional, Union
 
-from labelbox.schema.project import Project
+#from labelbox.schema.project import Project
 from labelbox.orm.db_object import DbObject
 from labelbox.orm.model import Field, Relationship
 from labelbox.exceptions import InconsistentOntologyException
 
+Project = "NONE"
+
 
 @dataclass
 class Option: