fix: create annotate function to centralize annotation

robotoff/app/core.py

@@ -13,7 +13,7 @@
     SAVED_ANNOTATION_VOTE_RESULT,
     UNKNOWN_INSIGHT_RESULT,
     AnnotationResult,
-    InsightAnnotatorFactory,
+    annotate,
 )
 from robotoff.models import (
     AnnotationVote,
@@ -385,8 +385,7 @@ def save_annotation(
         if not verified:
             return SAVED_ANNOTATION_VOTE_RESULT
 
-    annotator = InsightAnnotatorFactory.get(insight.type)
-    result = annotator.annotate(insight, annotation, update, data=data, auth=auth)
+    result = annotate(insight, annotation, update, data=data, auth=auth)
     username = auth.get_username() if auth else "unknown annotator"
     events.event_processor.send_async(
         "question_answered", username, device_id, insight.barcode

robotoff/insights/annotate.py

@@ -504,5 +504,24 @@ def get(cls, identifier: str) -> InsightAnnotator:
         return cls.mapping[identifier]
 
 
+def annotate(
+    insight: ProductInsight,
+    annotation: int,
+    update: bool = True,
+    data: Optional[dict] = None,
+    auth: Optional[OFFAuthentication] = None,
+    automatic: bool = False,
+) -> AnnotationResult:
+    annotator = InsightAnnotatorFactory.get(insight.type)
+    return annotator.annotate(
+        insight=insight,
+        annotation=annotation,
+        update=update,
+        data=data,
+        auth=auth,
+        automatic=automatic,
+    )
+
+
 class InvalidInsight(Exception):
     pass

robotoff/logos.py

@@ -12,10 +12,7 @@
 
 from robotoff import settings
 from robotoff.elasticsearch import get_es_client
-from robotoff.insights.annotate import (
-    UPDATED_ANNOTATION_RESULT,
-    InsightAnnotatorFactory,
-)
+from robotoff.insights.annotate import UPDATED_ANNOTATION_RESULT, annotate
 from robotoff.insights.importer import import_insights
 from robotoff.logo_label_type import LogoLabelType
 from robotoff.models import (
@@ -397,11 +394,10 @@ def generate_insights_from_annotated_logos(
     ):
         insight = ProductInsight.get_or_none(id=created_id)
         if insight:
-            annotator = InsightAnnotatorFactory.get(insight.type)
             logger.info(
                 "Annotating insight %s (product: %s)", insight.id, insight.barcode
             )
-            annotation_result = annotator.annotate(insight, 1, auth=auth)
+            annotation_result = annotate(insight, 1, auth=auth)
             annotated += int(annotation_result == UPDATED_ANNOTATION_RESULT)
 
     return annotated

robotoff/scheduler/__init__.py

@@ -14,10 +14,7 @@
 from robotoff import settings, slack
 from robotoff.elasticsearch import get_es_client
 from robotoff.elasticsearch.export import ElasticsearchExporter
-from robotoff.insights.annotate import (
-    UPDATED_ANNOTATION_RESULT,
-    InsightAnnotatorFactory,
-)
+from robotoff.insights.annotate import UPDATED_ANNOTATION_RESULT, annotate
 from robotoff.insights.importer import import_insights
 from robotoff.metrics import (
     ensure_influx_database,
@@ -56,11 +53,10 @@ def process_insights():
             .iterator()
         ):
             try:
-                annotator = InsightAnnotatorFactory.get(insight.type)
                 logger.info(
                     "Annotating insight %s (product: %s)", insight.id, insight.barcode
                 )
-                annotation_result = annotator.annotate(insight, 1, update=True)
+                annotation_result = annotate(insight, 1, update=True)
                 processed += 1
 
                 if annotation_result == UPDATED_ANNOTATION_RESULT and insight.data.get(

tests/integration/test_annotate_image.py

@@ -8,6 +8,7 @@
 import robotoff.insights.importer
 import robotoff.taxonomy
 from robotoff.app.api import api
+from robotoff.insights.annotate import UPDATED_ANNOTATION_RESULT
 from robotoff.models import LogoAnnotation, Prediction, ProductInsight
 from robotoff.products import Product
 
@@ -164,6 +165,7 @@ def test_logo_annotation_brand(client, peewee_db, monkeypatch, mocker, fake_taxo
     mocker.patch(
         "robotoff.brands.get_brand_prefix", return_value={("Etorki", "0000000xxxxxx")}
     )
+    mocker.patch("robotoff.logos.annotate", return_value=UPDATED_ANNOTATION_RESULT)
     start = datetime.utcnow()
     result = client.simulate_post(
         "/api/v1/images/logos/annotate",
@@ -203,7 +205,7 @@ def test_logo_annotation_brand(client, peewee_db, monkeypatch, mocker, fake_taxo
     assert prediction.value_tag == "Etorki"
     assert prediction.predictor == "universal-logo-detector"
     assert start <= prediction.timestamp <= end
-    assert prediction.automatic_processing
+    assert prediction.automatic_processing is False
     # We check that this prediction in turn generates an insight
 
     with peewee_db:
@@ -222,12 +224,12 @@ def test_logo_annotation_brand(client, peewee_db, monkeypatch, mocker, fake_taxo
     assert insight.value_tag == "Etorki"
     assert insight.predictor == "universal-logo-detector"
     assert start <= prediction.timestamp <= end
-    assert insight.automatic_processing
+    assert insight.automatic_processing is False
     assert insight.username == "a"
     assert insight.completed_at is None  # we did not run annotate yet
 
 
-def test_logo_annotation_label(client, peewee_db, monkeypatch, fake_taxonomy):
+def test_logo_annotation_label(client, peewee_db, monkeypatch, fake_taxonomy, mocker):
     """This test will check that, given an image with a logo above the confidence threshold,
     that is then fed into the ANN logos and labels model, we annotate properly a product.
     """
@@ -237,6 +239,7 @@ def test_logo_annotation_label(client, peewee_db, monkeypatch, fake_taxonomy):
         )
     barcode = ann.image_prediction.image.barcode
     _fake_store(monkeypatch, barcode)
+    mocker.patch("robotoff.logos.annotate", return_value=UPDATED_ANNOTATION_RESULT)
     start = datetime.utcnow()
     result = client.simulate_post(
         "/api/v1/images/logos/annotate",
@@ -276,7 +279,7 @@ def test_logo_annotation_label(client, peewee_db, monkeypatch, fake_taxonomy):
     assert prediction.value_tag == "en:eu-organic"
     assert prediction.predictor == "universal-logo-detector"
     assert start <= prediction.timestamp <= end
-    assert prediction.automatic_processing
+    assert prediction.automatic_processing is False
     # We check that this prediction in turn generates an insight
     with peewee_db:
         insights = list(ProductInsight.select().filter(barcode=barcode).execute())
@@ -294,6 +297,6 @@ def test_logo_annotation_label(client, peewee_db, monkeypatch, fake_taxonomy):
     assert insight.value_tag == "en:eu-organic"
     assert insight.predictor == "universal-logo-detector"
     assert start <= prediction.timestamp <= end
-    assert insight.automatic_processing
+    assert insight.automatic_processing is False
     assert insight.username == "a"
     assert insight.completed_at is None