wip

Author: Matt Sokoloff

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/metrics/scalar.py

@@ -16,3 +16,6 @@ class CustomScalarMetric(BaseModel):
     subclass_name: Optional[str] = None
     aggregation: MetricAggregation = MetricAggregation.ARITHMETIC_MEAN
     extra: Dict[str, Any] = {}
+
+
+# TODO: Create a metric type that is used once....

labelbox/data/serialization/ndjson/metric.py

@@ -1,7 +1,11 @@
-from labelbox.data.annotation_types.data import TextData, ImageData
+from labelbox.data.annotation_types.metrics.scalar import CustomScalarMetric
+from typing import Literal, Union
+
+from fiftyone.core.collections import aggregation
+
+from labelbox.data.annotation_types.data import ImageData, TextData
 from labelbox.data.annotation_types.metrics import ScalarMetric
 from labelbox.data.serialization.ndjson.base import NDJsonBase
-from typing import Union
 
 
 class NDDataRowScalarMetric(NDJsonBase):
@@ -19,16 +23,47 @@ def from_common(
                                      data_row={'id': data.uid})
 
 
+class NDCustomScalarMetric(NDJsonBase):
+    metric_name: float
+    metric_value: float
+    sublcass_name: float
+    aggregation: Union[Literal["ARITHMETIC_MEAN"], Literal["GEOMETRIC_MEAN"],
+                       Literal["HARMONIC_MEAN"], Literal["SUM"]]
+
+    def to_common(self) -> CustomScalarMetric:
+        return ScalarMetric(value=self.metric_value, extra={'uuid': self.uuid})
+
+    @classmethod
+    def from_common(cls, metric: ScalarMetric,
+                    data: Union[TextData, ImageData]) -> "NDCustomScalarMetric":
+        return NDCustomScalarMetric(uuid=metric.extra.get('uuid'),
+                                    metric_value=metric.value,
+                                    data_row={'id': data.uid})
+
+
 class NDMetricAnnotation:
 
     @classmethod
-    def to_common(cls, annotation: NDDataRowScalarMetric) -> ScalarMetric:
+    def to_common(cls, annotation: "NDMetricType") -> ScalarMetric:
+
         return annotation.to_common()
 
     @classmethod
-    def from_common(cls, annotation: ScalarMetric,
-                    data: Union[TextData, ImageData]) -> NDDataRowScalarMetric:
+    def from_common(cls, annotation: Union[ScalarMetric, CustomScalarMetric],
+                    data: Union[TextData, ImageData]) -> "NDMetricType":
         return NDDataRowScalarMetric.from_common(annotation, data)
 
+    @staticmethod
+    def lookup_object(
+            metric: Union[ScalarMetric, CustomScalarMetric]) -> "NDMetricType":
+        result = {
+            ScalarMetric: NDDataRowScalarMetric,
+            CustomScalarMetric: NDCustomScalarMetric,
+        }.get(type(metric))
+        if result is None:
+            raise TypeError(
+                f"Unable to convert object to MAL format. `{type(metric)}`")
+        return result
+
 
-NDMetricType = NDDataRowScalarMetric
+NDMetricType = Union[NDDataRowScalarMetric, NDCustomScalarMetric]

tests/data/annotation_types/test_metrics.py

@@ -1,10 +1,10 @@
+import pytest
+
 from labelbox.data.annotation_types.metrics.aggregations import MetricAggregation
 from labelbox.data.annotation_types.metrics.scalar import CustomScalarMetric
 from labelbox.data.annotation_types.collection import LabelList
 from labelbox.data.annotation_types import ScalarMetric, Label, ImageData
 
-import pytest
-
 
 def test_scalar_metric():
     value = 10

tests/integration/conftest.py

@@ -134,7 +134,9 @@ def client(environ: str):
 
 
 @pytest.fixture(scope="session")
-def image_url(client):
+def image_url(client, environ: str):
+    if environ == Environ.LOCAL:
+        return IMG_URL
     return client.upload_data(requests.get(IMG_URL).content, sign=True)