Added annotation characteristics

Author: epou

api/serializers.py

@@ -800,12 +800,44 @@ class Meta:
                 "confidence": {"read_only": True},
             }
 
+    class AnnotationCharacteristicsSerializer(serializers.Serializer):
+        sex = serializers.ChoiceField(choices=['male', 'female'], required=False, allow_null=True)
+        is_blood_fed = serializers.BooleanField(required=False, default=False)
+        is_gravid = serializers.BooleanField(required=False, default=False)
+
+        def to_internal_value(self, data):
+            sex = data.pop('sex', None)
+            is_blood_fed = data.pop('is_blood_fed', False)
+            is_gravid = data.pop('is_gravid', False)
+
+            ret = {}
+            if sex == 'male':
+                blood_genre = 'male'
+            elif sex == 'female':
+                if is_gravid and is_blood_fed:
+                    blood_genre = 'fgblood'
+                elif is_gravid:
+                    blood_genre = 'fgravid'
+                elif is_blood_fed:
+                    blood_genre = 'fblood'
+                else:
+                    blood_genre = 'female'
+            else:
+                blood_genre = 'dk'
+
+            ret['blood_genre'] = blood_genre
+            return ret
+
+        class Meta:
+            fields = ("sex", "is_blood_fed", "is_gravid")
+
     user_hidden_obj = serializers.HiddenField(default=serializers.CurrentUserDefault())
 
     user = SimpleAnnotatorUserSerializer(read_only=True)
     feedback = AnnotationFeedbackSerializer(source='*', required=False)
 
     classification = AnnotationClassificationSerializer(source='*', required=True, allow_null=True)
+    characteristics = AnnotationCharacteristicsSerializer(required=False, write_only=True)
     best_photo_uuid = serializers.UUIDField(write_only=True, required=False)
     best_photo = SimplePhotoSerializer(read_only=True, allow_null=True)
     tags = TagListSerializerField(required=False, allow_empty=True)
@@ -866,17 +898,26 @@ def validate(self, data):
 
     def create(self, validated_data):
         is_favourite = validated_data.pop("is_favourite", False)
+        characteristics = validated_data.pop("characteristics", {})
+        blood_genre = characteristics.get("blood_genre", None)
         with transaction.atomic():
             instance = super().create(validated_data)
             if is_favourite:
                 FavoritedReports.objects.get_or_create(
                     user=instance.user,
                     report=instance.report,
                 )
+            if blood_genre and instance.best_photo:
+                # Update the best photo with the blood_genre
+                instance.best_photo.blood_genre = blood_genre
+                instance.best_photo.save()
+
         return instance
 
     def update(self, instance, validated_data):
         is_favourite = validated_data.pop("is_favourite", False)
+        characteristics = validated_data.pop("characteristics", {})
+        blood_genre = characteristics.get("blood_genre", None)
         with transaction.atomic():
             instance = super().update(instance, validated_data)
             if is_favourite:
@@ -889,6 +930,10 @@ def update(self, instance, validated_data):
                     user=instance.user,
                     report=instance.report,
                 ).delete()
+            if blood_genre and instance.best_photo:
+                # Update the best photo with the blood_genre
+                instance.best_photo.blood_genre = blood_genre
+                instance.best_photo.save()
         return instance
 
     class Meta:
@@ -901,6 +946,7 @@ class Meta:
             "best_photo_uuid",
             "best_photo",
             "classification",
+            "characteristics",
             "feedback",
             "type",
             "is_flagged",

api/tests/test_views.py

@@ -16,7 +16,7 @@
 from rest_framework_simplejwt.settings import api_settings
 
 from tigacrafting.models import ExpertReportAnnotation, IdentificationTask, PhotoPrediction, FavoritedReports
-from tigaserver_app.models import TigaUser, Report, Device, MobileApp
+from tigaserver_app.models import TigaUser, Report, Device, MobileApp, Photo
 
 from api.tests.clients import AppAPIClient
 from api.tests.integration.observations.factories import create_observation_object
@@ -843,6 +843,43 @@ def test_is_favourite_does_nothing_if_already_exists_FavoritedReports(self, api_
             user=annotation.user
         ).exists()
 
+    @pytest.mark.parametrize(
+        "sex, is_blood_fed, is_gravid, expected_genre_blood",
+        [
+            ('male', False, False, Photo.BLOOD_GENRE_MALE),
+            ('male', False, True, Photo.BLOOD_GENRE_MALE),
+            ('male', True, False, Photo.BLOOD_GENRE_MALE),
+            ('male', True, True, Photo.BLOOD_GENRE_MALE),
+            ('female', False, False, Photo.BLOOD_GENRE_FEMALE),
+            ('female', False, True, Photo.BLOOD_GENRE_FEMALE_GRAVID),
+            ('female', True, False, Photo.BLOOD_GENRE_FEMALE_BLOOD_FED),
+            ('female', True, True, Photo.BLOOD_GENRE_FEMALE_GRAVID_BLOOD_FED),
+            (None, False, False, Photo.BLOOD_GENRE_UNKNOWN),
+            (None, False, True, Photo.BLOOD_GENRE_UNKNOWN),
+            (None, True, False, Photo.BLOOD_GENRE_UNKNOWN),
+            (None, True, True, Photo.BLOOD_GENRE_UNKNOWN),
+        ]
+    )
+    def test_characteristics_sets_Photo_blood_genre_field(self, api_client, endpoint, identification_task, common_post_data, with_add_permission, sex, is_blood_fed, is_gravid, expected_genre_blood):
+        post_data = common_post_data
+        post_data['best_photo_uuid'] = identification_task.photo.uuid
+        post_data['characteristics'] = {
+            'sex': sex,
+            'is_blood_fed': is_blood_fed,
+            'is_gravid': is_gravid
+        }
+
+        response = api_client.post(
+            endpoint,
+            data=post_data,
+            format='json'
+        )
+        assert response.status_code == status.HTTP_201_CREATED
+
+        annotation = ExpertReportAnnotation.objects.get(pk=response.data['id'])
+        photo = annotation.best_photo
+        assert photo.blood_genre == expected_genre_blood
+
     @pytest.mark.parametrize(
         "pre_assign",
         [True, False]

tigaserver_app/models.py

@@ -2983,12 +2983,19 @@ def wrapper(instance, filename):
     return wrapper
 '''
 
-BLOOD_GENRE = (('male', 'Male'), ('female', 'Female'), ('fblood', 'Female blood'), ('fgravid', 'Female gravid'), ('fgblood', 'Female gravid + blood'), ('dk', 'Dont know') )
-
 class Photo(models.Model):
     """
     Photo uploaded by user.
     """
+    BLOOD_GENRE_MALE = 'male'
+    BLOOD_GENRE_FEMALE = 'female'
+    BLOOD_GENRE_FEMALE_BLOOD_FED = 'fblood'
+    BLOOD_GENRE_FEMALE_GRAVID = 'fgravid'
+    BLOOD_GENRE_FEMALE_GRAVID_BLOOD_FED = 'fgblood'
+    BLOOD_GENRE_UNKNOWN = 'dk'
+
+    BLOOD_GENRE = ((BLOOD_GENRE_MALE, 'Male'), (BLOOD_GENRE_FEMALE, 'Female'), (BLOOD_GENRE_FEMALE_BLOOD_FED, 'Female blood'), (BLOOD_GENRE_FEMALE_GRAVID, 'Female gravid'), (BLOOD_GENRE_FEMALE_GRAVID_BLOOD_FED, 'Female gravid + blood'), (BLOOD_GENRE_UNKNOWN, 'Dont know') )
+
     photo = ProcessedImageField(
         upload_to=make_image_uuid,
         processors=[ResizeToFit(height=2160, upscale=False)],