Merge pull request #271 from Labelbox/develop

3.3.0

Author: msokoloff1

CHANGELOG.md

@@ -1,5 +1,14 @@
 # Changelog
 
+# Version 3.3.0 (2021-09-02)
+## Added
+* `Dataset.create_data_rows_sync()` for synchronous bulk uploads of data rows
+* `Model.delete()`, `ModelRun.delete()`, and `ModelRun.delete_annotation_groups()` to
+    Clean up models, model runs, and annotation groups.
+
+## Fix
+* Increased timeout for label exports since projects with many segmentation masks weren't finishing quickly enough.
+
 # Version 3.2.1 (2021-08-31)
 ## Fix
 * Resolved issue with `create_data_rows()` was not working on amazon linux

labelbox/__init__.py

@@ -1,5 +1,5 @@
 name = "labelbox"
-__version__ = "3.2.1"
+__version__ = "3.3.0"
 
 from labelbox.schema.project import Project
 from labelbox.client import Client

labelbox/data/annotation_types/__init__.py

@@ -29,3 +29,4 @@
 from .collection import LabelGenerator
 
 from .metrics import ScalarMetric
+from .metrics import MetricAggregation

labelbox/data/annotation_types/annotation.py

@@ -1,7 +1,5 @@
 from typing import Any, Dict, List, Union
 
-from pydantic.main import BaseModel
-
 from .classification import Checklist, Dropdown, Radio, Text
 from .feature import FeatureSchema
 from .geometry import Geometry
@@ -16,6 +14,7 @@ class BaseAnnotation(FeatureSchema):
 
 class ClassificationAnnotation(BaseAnnotation):
     """Class representing classification annotations (annotations that don't have a location) """
+
     value: Union[Text, Checklist, Radio, Dropdown]
 
 

labelbox/data/annotation_types/classification/classification.py

@@ -1,10 +1,24 @@
 from typing import Any, Dict, List
 
-from pydantic.main import BaseModel
+try:
+    from typing import Literal
+except:
+    from typing_extensions import Literal
 
+from pydantic import BaseModel, validator
 from ..feature import FeatureSchema
 
 
+# TODO: Replace when pydantic adds support for unions that don't coerce types
+class _TempName(BaseModel):
+    name: str
+
+    def dict(self, *args, **kwargs):
+        res = super().dict(*args, **kwargs)
+        res.pop('name')
+        return res
+
+
 class ClassificationAnswer(FeatureSchema):
     """
     - Represents a classification option.
@@ -19,8 +33,9 @@ class Radio(BaseModel):
     answer: ClassificationAnswer
 
 
-class Checklist(BaseModel):
+class Checklist(_TempName):
     """ A classification with many selected options allowed """
+    name: Literal["checklist"] = "checklist"
     answer: List[ClassificationAnswer]
 
 
@@ -29,9 +44,10 @@ class Text(BaseModel):
     answer: str
 
 
-class Dropdown(BaseModel):
+class Dropdown(_TempName):
     """
     - A classification with many selected options allowed .
     - This is not currently compatible with MAL.
     """
+    name: Literal["dropdown"] = "dropdown"
     answer: List[ClassificationAnswer]

labelbox/data/annotation_types/data/raster.py

@@ -81,7 +81,8 @@ def value(self) -> np.ndarray:
             with open(self.file_path, "rb") as img:
                 im_bytes = img.read()
             self.im_bytes = im_bytes
-            return self.bytes_to_np(im_bytes)
+            arr = self.bytes_to_np(im_bytes)
+            return arr
         elif self.url is not None:
             im_bytes = self.fetch_remote()
             self.im_bytes = im_bytes
@@ -92,7 +93,7 @@ def value(self) -> np.ndarray:
     def set_fetch_fn(self, fn):
         object.__setattr__(self, 'fetch_remote', lambda: fn(self))
 
-    @retry.Retry(deadline=15.)
+    @retry.Retry(deadline=60.)
     def fetch_remote(self) -> bytes:
         """
         Method for accessing url.
@@ -104,7 +105,7 @@ def fetch_remote(self) -> bytes:
         response.raise_for_status()
         return response.content
 
-    @retry.Retry(deadline=15.)
+    @retry.Retry(deadline=30.)
     def create_url(self, signer: Callable[[bytes], str]) -> str:
         """
         Utility for creating a url from any of the other image representations.

labelbox/data/annotation_types/label.py

@@ -1,4 +1,5 @@
 from collections import defaultdict
+from labelbox.data.annotation_types.metrics.scalar import ScalarMetric
 
 from typing import Any, Callable, Dict, List, Union, Optional
 
@@ -21,7 +22,8 @@ class Label(BaseModel):
     data: Union[VideoData, ImageData, TextData]
     annotations: List[Union[ClassificationAnnotation, ObjectAnnotation,
                             VideoObjectAnnotation,
-                            VideoClassificationAnnotation, ScalarMetric]] = []
+                            VideoClassificationAnnotation, ScalarMetric,
+                            ScalarMetric]] = []
     extra: Dict[str, Any] = {}
 
     def object_annotations(self) -> List[ObjectAnnotation]:

labelbox/data/annotation_types/metrics.py

@@ -0,0 +1,2 @@
+from .scalar import ScalarMetric
+from .aggregations import MetricAggregation

labelbox/data/annotation_types/metrics/__init__.py

@@ -0,0 +1,8 @@
+from enum import Enum
+
+
+class MetricAggregation(Enum):
+    ARITHMETIC_MEAN = "ARITHMETIC_MEAN"
+    GEOMETRIC_MEAN = "GEOMETRIC_MEAN"
+    HARMONIC_MEAN = "HARMONIC_MEAN"
+    SUM = "SUM"