Merge branch 'develop' of https://github.com/Labelbox/labelbox-python into ms/video-classification-keyframe

Author: Matt Sokoloff

CHANGELOG.md

@@ -18,8 +18,8 @@
     * Set up a project from an existing ontology with `project.setup_edior()`
     * Added new `FeatureSchema` entity
 * Add support for new queue modes
-    * Send batches of data direction to a project with `project.queue()`
-    * Remove items from the queue with `project.dequeue()`
+    * Send batches of data directly to a project queue with `project.queue()`
+    * Remove items from a project queue with `project.dequeue()`
     * Query for and toggle the queue mode
 
 # Version 3.8.0 (2021-10-22)

README.md

@@ -57,9 +57,9 @@ The package `rasterio` installed by `labelbox[data]` relies on GDAL which could
 You may see the following error message:
 
 ```
-INFO:root:Building on Windows requires extra options to setup.py to locate needed GDAL files. More information is available in the README. 
+INFO:root:Building on Windows requires extra options to setup.py to locate needed GDAL files. More information is available in the README.
 
-ERROR: A GDAL API version must be specified. Provide a path to gdal-config using a GDAL_CONFIG environment variable or use a GDAL_VERSION environment variable. 
+ERROR: A GDAL API version must be specified. Provide a path to gdal-config using a GDAL_CONFIG environment variable or use a GDAL_VERSION environment variable.
 ```
 
 As a workaround:
@@ -72,7 +72,7 @@ As a workaround:
 
     Note: You need to download the right files for your Python version. In the files above `cp38` means CPython 3.8.
 
-2. After downloading the files, please run the following commands, in this particular order.  
+2. After downloading the files, please run the following commands, in this particular order.
 
 ```
 pip install GDAL‑3.3.2‑cp38‑cp38‑win_amd64.wh

docs/source/index.rst

@@ -154,3 +154,23 @@ Enums
    :members:
    :show-inheritance:
 
+ModelRun
+----------------------------
+
+.. automodule:: labelbox.schema.model_run
+   :members:
+   :show-inheritance:
+
+Model
+----------------------------
+
+.. automodule:: labelbox.schema.model
+   :members:
+   :show-inheritance:
+
+DataRowMetadata
+----------------------------
+
+.. automodule:: labelbox.schema.data_row_metadata
+   :members:
+   :show-inheritance:   

labelbox/data/annotation_types/classification/classification.py

@@ -1,4 +1,4 @@
-from typing import Any, Dict, List, Union
+from typing import Any, Dict, List, Union, Optional
 
 try:
     from typing import Literal
@@ -24,32 +24,47 @@ class ClassificationAnswer(FeatureSchema):
     - Represents a classification option.
     - Because it inherits from FeatureSchema
         the option can be represented with either the name or feature_schema_id
+
+    - The key frame arg only applies to video classifications.
+      Each answer can have a key frame indepdent of the others.
+        So unlike object annotations, classification annotations
+          track key frames at a classification answer level.
     """
     extra: Dict[str, Any] = {}
+    keyframe: Optional[bool] = None
 
-
-class VideoClassificationAnswer(ClassificationAnswer):
-    """
-    Each answer can have a key frame indepdent of the others.
-    So unlike object annotations, classification annotations
-      track key frames at a classification answer level.
-    """
-    keyframe: bool
+    def dict(self, *args, **kwargs):
+        res = super().dict(*args, **kwargs)
+        if res['keyframe'] is None:
+            res.pop('keyframe')
+        return res
 
 
 class Radio(BaseModel):
-    """ A classification with only one selected option allowed """
-    answer: Union[VideoClassificationAnswer, ClassificationAnswer]
+    """ A classification with only one selected option allowed
+
+    >>> Radio(answer = ClassificationAnswer(name = "dog"))
+
+    """
+    answer: ClassificationAnswer
 
 
 class Checklist(_TempName):
-    """ A classification with many selected options allowed """
+    """ A classification with many selected options allowed
+
+    >>> Checklist(answer = [ClassificationAnswer(name = "cloudy")])
+
+    """
     name: Literal["checklist"] = "checklist"
-    answer: Union[VideoClassificationAnswer, ClassificationAnswer]
+    answer: ClassificationAnswer
 
 
 class Text(BaseModel):
-    """ Free form text """
+    """ Free form text
+
+    >>> Text(answer = "some text answer")
+
+    """
     answer: str
 
 
@@ -59,4 +74,4 @@ class Dropdown(_TempName):
     - This is not currently compatible with MAL.
     """
     name: Literal["dropdown"] = "dropdown"
-    answer: List[Union[VideoClassificationAnswer, ClassificationAnswer]]
+    answer: List[ClassificationAnswer]

labelbox/data/annotation_types/data/text.py

@@ -9,7 +9,14 @@
 
 class TextData(BaseData):
     """
-    Represents text data
+    Represents text data. Requires arg file_path, text, or url
+
+    >>> TextData(text="") 
+
+    Args:
+        file_path (str)
+        text (str)
+        url (str)
     """
     file_path: Optional[str] = None
     text: Optional[str] = None

labelbox/data/annotation_types/geometry/line.py

@@ -3,6 +3,7 @@
 import geojson
 import numpy as np
 import cv2
+from pydantic import validator
 
 from .point import Point
 from .geometry import Geometry
@@ -14,6 +15,8 @@ class Line(Geometry):
     Args:
         points (List[Point]): A list of `Point` geometries
 
+    >>> Line(points = [Point(x=3,y=4), Point(x=3,y=5)])
+
     """
     points: List[Point]
 
@@ -47,3 +50,12 @@ def draw(self,
                              False,
                              color=color,
                              thickness=thickness)
+
+    @validator('points')
+    def is_geom_valid(cls, points):
+        if len(points) < 2:
+            raise ValueError(
+                f"A line must have at least 2 points to be valid. Found {points}"
+            )
+
+        return points

labelbox/data/serialization/labelbox_v1/classification.py

@@ -1,4 +1,3 @@
-from labelbox.data.annotation_types.classification.classification import VideoClassificationAnswer
 from typing import List, Union
 
 from pydantic.main import BaseModel
@@ -10,47 +9,37 @@
 
 
 class LBV1ClassificationAnswer(LBV1Feature):
-    ...
-
-
-def get_classification_answer(
-    answer: LBV1ClassificationAnswer
-) -> Union[ClassificationAnswer, VideoClassificationAnswer]:
-    kwargs = dict(feature_schema_id=answer.schema_id,
+    def to_common(self, answer: "LBV1ClassificationAnswer") -> ClassificationAnswer:
+        return ClassificationAnswer(feature_schema_id=answer.schema_id,
                   name=answer.title,
+                  keyframe = answer.keyframe,
                   extra={
                       'feature_id': answer.feature_id,
                       'value': answer.value
                   })
-    if answer.keyframe is not None:
-        return VideoClassificationAnswer(keyframe=answer.keyframe, **kwargs)
-    else:
-        return ClassificationAnswer(**kwargs)
 
-
-def get_lbv1_classification_answer(answer: Union[ClassificationAnswer,
-                                                 VideoClassificationAnswer]):
-    return LBV1ClassificationAnswer(
+    @classmethod
+    def from_common(cls, answer: ClassificationAnnotation) -> "LBV1ClassificationAnswer":
+        return cls(
         schema_id=answer.feature_schema_id,
         title=answer.name,
         value=answer.extra.get('value'),
         feature_id=answer.extra.get('feature_id'),
-        keyframe=getattr(answer, 'keyframe',
-                         None)  # Only applies to video clasifications
+        keyframe=answer.keyframe
     )
 
 
 class LBV1Radio(LBV1Feature):
     answer: LBV1ClassificationAnswer
 
     def to_common(self) -> Radio:
-        return Radio(answer=get_classification_answer(self.answer))
+        return Radio(answer=self.answer.to_common())
 
     @classmethod
     def from_common(cls, radio: Radio, feature_schema_id: Cuid,
                     **extra) -> "LBV1Radio":
         return cls(schema_id=feature_schema_id,
-                   answer=get_lbv1_classification_answer(radio.answer),
+                   answer=LBV1ClassificationAnswer.from_common(radio.answer),
                    **extra)
 
 
@@ -59,15 +48,15 @@ class LBV1Checklist(LBV1Feature):
 
     def to_common(self) -> Checklist:
         return Checklist(answer=[
-            get_classification_answer(answer) for answer in self.answers
+            answer.to_common() for answer in self.answers
         ])
 
     @classmethod
     def from_common(cls, checklist: Checklist, feature_schema_id: Cuid,
                     **extra) -> "LBV1Checklist":
         return cls(schema_id=feature_schema_id,
                    answers=[
-                       get_lbv1_classification_answer(answer)
+                       LBV1ClassificationAnswer.from_common(answer)
                        for answer in checklist.answer
                    ],
                    **extra)
@@ -78,15 +67,15 @@ class LBV1Dropdown(LBV1Feature):
 
     def to_common(self) -> Dropdown:
         return Dropdown(answer=[
-            get_classification_answer(answer) for answer in self.answer
+            answer.to_common() for answer in self.answer
         ])
 
     @classmethod
     def from_common(cls, dropdown: Dropdown, feature_schema_id: Cuid,
                     **extra) -> "LBV1Dropdown":
         return cls(schema_id=feature_schema_id,
                    answer=[
-                       get_lbv1_classification_answer(answer)
+                       LBV1ClassificationAnswer.from_common(answer)
                        for answer in dropdown.answer
                    ],
                    **extra)

labelbox/schema/data_row_metadata.py

@@ -32,6 +32,9 @@ class DataRowMetadataSchema(BaseModel):
 
     @property
     def id(self):
+        """ `DataRowMetadataSchema.id is being deprecated after version 3.9 
+            in favor of DataRowMetadataSchema.uid`
+        """
         warnings.warn("`id` is being deprecated in favor of `uid`")
         return self.uid
 

labelbox/schema/model_run.py

@@ -145,6 +145,9 @@ def model_run_data_rows(self):
             ['annotationGroups', 'pageInfo', 'endCursor'])
 
     def annotation_groups(self):
+        """ `ModelRun.annotation_groups is being deprecated after version 3.9
+            in favor of ModelRun.model_run_data_rows`
+        """
         warnings.warn(
             "`ModelRun.annotation_groups` is being deprecated in favor of `ModelRun.model_run_data_rows`"
         )
@@ -181,6 +184,9 @@ def delete_model_run_data_rows(self, data_row_ids):
         })
 
     def delete_annotation_groups(self, data_row_ids):
+        """ `ModelRun.delete_annotation_groups is being deprecated after version 3.9
+            in favor of ModelRun.delete_model_run_data_rows`
+        """
         warnings.warn(
             "`ModelRun.delete_annotation_groups` is being deprecated in favor of `ModelRun.delete_model_run_data_rows`"
         )

tests/data/annotation_types/classification/test_classification.py

@@ -125,6 +125,7 @@ def test_checklist():
 
     with pytest.raises(ValidationError):
         classification = Checklist(answer=answer)
+    breakpoint()
 
     classification = Checklist(answer=[answer])
     assert classification.dict() == {