Feature/feedback v1

.gitignore

@@ -8,6 +8,7 @@ frontend/.pnp.js
 
 # testing
 frontend/coverage
+postgres-data/*
 
 # production
 frontend/build

backend/core/admin.py

@@ -7,13 +7,13 @@
 
 
 @admin.register(Dataset)
-class DatasetAdmin(geoadmin.GeoModelAdmin):
+class DatasetAdmin(geoadmin.OSMGeoAdmin):
     list_display = ["name", "created_by"]
 
 
 @admin.register(Model)
-class ModelAdmin(geoadmin.GeoModelAdmin):
-    list_display = ["get_dataset_id", "name", "status", "created_at"]
+class ModelAdmin(geoadmin.OSMGeoAdmin):
+    list_display = ["get_dataset_id", "name", "status", "created_at", "created_by"]
 
     def get_dataset_id(self, obj):
         return obj.dataset.id
@@ -22,7 +22,7 @@ def get_dataset_id(self, obj):
 
 
 @admin.register(Training)
-class TrainingAdmin(geoadmin.GeoModelAdmin):
+class TrainingAdmin(geoadmin.OSMGeoAdmin):
     list_display = [
         "get_model_id",
         "description",
@@ -37,3 +37,13 @@ def get_model_id(self, obj):
         return obj.model.id
 
     get_model_id.short_description = "Model"
+
+
+@admin.register(FeedbackAOI)
+class FeedbackAOIAdmin(geoadmin.OSMGeoAdmin):
+    list_display = ["training", "user"]
+
+
+@admin.register(Feedback)
+class FeedbackAdmin(geoadmin.OSMGeoAdmin):
+    list_display = ["feedback_type", "training", "user", "created_at"]

backend/core/serializers.py

@@ -1,3 +1,4 @@
+from django.conf import settings
 from login.models import OsmUser
 from rest_framework import serializers
 from rest_framework_gis.serializers import (
@@ -102,32 +103,36 @@ def to_representation(self, instance):
         return ret
 
 
-class LabelSerializer(
-    GeoFeatureModelSerializer
-):  # serializers are used to translate models objects to api
+class LabelSerializer(GeoFeatureModelSerializer):
     class Meta:
         model = Label
-        geo_field = "geom"  # this will be used as geometry in order to create geojson api , geofeatureserializer will let you create api in geojson
+        geo_field = "geom"
         # auto_bbox = True
-        fields = "__all__"  # defining all the fields to  be included in curd for now , we can restrict few if we want
+        fields = "__all__"
 
-        read_only_fields = ("created_at", "osm_id")
+        # read_only_fields = ("created_at", "osm_id")
 
 
 class FeedbackLabelSerializer(GeoFeatureModelSerializer):
     class Meta:
         model = FeedbackLabel
         geo_field = "geom"
         fields = "__all__"
-        read_only_fields = ("created_at", "osm_id")
+        # read_only_fields = ("created_at", "osm_id")
 
 
-class LabelFileSerializer(
-    GeoFeatureModelSerializer
-):  # serializers are used to translate models objects to api
+class LabelFileSerializer(GeoFeatureModelSerializer):
     class Meta:
         model = Label
-        geo_field = "geom"  # this will be used as geometry in order to create geojson api , geofeatureserializer will let you create api in geojson
+        geo_field = "geom"
+        # auto_bbox = True
+        fields = ("osm_id",)
+
+
+class FeedbackLabelFileSerializer(GeoFeatureModelSerializer):
+    class Meta:
+        model = FeedbackLabel
+        geo_field = "geom"
         # auto_bbox = True
         fields = ("osm_id",)
 
@@ -160,7 +165,55 @@ class FeedbackParamSerializer(serializers.Serializer):
     training_id = serializers.IntegerField(required=True)
     epochs = serializers.IntegerField(required=False)
     batch_size = serializers.IntegerField(required=False)
-    freeze_layers = serializers.BooleanField(required=False)
+    zoom_level = serializers.ListField(child=serializers.IntegerField(), required=False)
+
+    def validate_training_id(self, value):
+        try:
+            Training.objects.get(id=value)
+        except Training.DoesNotExist:
+            raise serializers.ValidationError("Training doesn't exist")
+
+        return value
+
+    def validate(self, data):
+        training_id = data.get("training_id")
+
+        try:
+            fd_aois = FeedbackAOI.objects.filter(training=training_id)
+        except FeedbackAOI.DoesNotExist:
+            raise serializers.ValidationError(
+                "No feedback AOI is associated with Training"
+            )
+
+        if fd_aois.filter(
+            label_status=FeedbackAOI.DownloadStatus.NOT_DOWNLOADED
+        ).exists():
+            raise serializers.ValidationError(
+                "Not all AOIs have their labels downloaded"
+            )
+
+        if "epochs" in data and (
+            data["epochs"] > settings.EPOCHS_LIMIT or data["epochs"] <= 0
+        ):
+            raise serializers.ValidationError(
+                f"Epochs should be 1 - {settings.EPOCHS_LIMIT} on this server"
+            )
+
+        if "batch_size" in data and (
+            data["batch_size"] > settings.BATCH_SIZE_LIMIT or data["batch_size"] <= 0
+        ):
+            raise serializers.ValidationError(
+                f"Batch size should be 1 - {settings.BATCH_SIZE_LIMIT} on this server"
+            )
+
+        if "zoom_level" in data:
+            for zoom in data["zoom_level"]:
+                if zoom < 19 or zoom > 21:
+                    raise serializers.ValidationError(
+                        "Zoom level must be between 19 and 21"
+                    )
+
+        return data
 
 
 class PredictionParamSerializer(serializers.Serializer):

backend/core/tasks.py

@@ -10,8 +10,12 @@
 import ramp.utils
 import tensorflow as tf
 from celery import shared_task
-from core.models import AOI, Feedback, Label, Training
-from core.serializers import FeedbackFileSerializer, LabelFileSerializer
+from core.models import AOI, Feedback, FeedbackAOI, FeedbackLabel, Label, Training
+from core.serializers import (
+    FeedbackFileSerializer,
+    FeedbackLabelFileSerializer,
+    LabelFileSerializer,
+)
 from core.utils import bbox, download_imagery, get_start_end_download_coords
 from django.conf import settings
 from django.contrib.gis.db.models.aggregates import Extent
@@ -65,34 +69,32 @@ def train_model(
                 shutil.rmtree(training_input_image_source)
             os.makedirs(training_input_image_source)
             if feedback:
-                feedback_objects = Feedback.objects.filter(
-                    training__id=feedback,
-                    validated=True,
-                )
-                bbox_feedback = feedback_objects.aggregate(Extent("geom"))[
-                    "geom__extent"
-                ]
-                bbox_geo = GEOSGeometry(
-                    f"POLYGON(({bbox_feedback[0]} {bbox_feedback[1]},{bbox_feedback[2]} {bbox_feedback[1]},{bbox_feedback[2]} {bbox_feedback[3]},{bbox_feedback[0]} {bbox_feedback[3]},{bbox_feedback[0]} {bbox_feedback[1]}))"
-                )
-                print(training_input_image_source)
-                print(bbox_feedback)
-                with open(
-                    os.path.join(training_input_image_source, "labels_bbox.geojson"),
-                    "w",
-                    encoding="utf-8",
-                ) as f:
-                    f.write(bbox_geo.geojson)
+                try:
+                    aois = FeedbackAOI.objects.filter(training=feedback)
+                except FeedbackAOI.DoesNotExist:
+                    raise ValueError(
+                        f"No Feedback AOI is attached with supplied training id:{dataset_id}, Create AOI first",
+                    )
+
+            else:
+                try:
+                    aois = AOI.objects.filter(dataset=dataset_id)
+                except AOI.DoesNotExist:
+                    raise ValueError(
+                        f"No AOI is attached with supplied dataset id:{dataset_id}, Create AOI first",
+                    )
 
+            for obj in aois:
+                bbox_coords = bbox(obj.geom.coords[0])
                 for z in zoom_level:
                     zm_level = z
                     print(
                         f"""Running Download process for
-                                feedback {training_id} - dataset : {dataset_id} , zoom : {zm_level}"""
+                            aoi : {obj.id} - dataset : {dataset_id} , zoom : {zm_level}"""
                     )
                     try:
                         tile_size = DEFAULT_TILE_SIZE  # by default
-                        bbox_coords = list(bbox_feedback)
+
                         start, end = get_start_end_download_coords(
                             bbox_coords, zm_level, tile_size
                         )
@@ -107,49 +109,17 @@ def train_model(
                     except Exception as ex:
                         raise ex
 
-            else:
-                try:
-                    aois = AOI.objects.filter(dataset=dataset_id)
-                except AOI.DoesNotExist:
-                    raise ValueError(
-                        f"No AOI is attached with supplied dataset id:{dataset_id}, Create AOI first",
-                    )
-
-                for obj in aois:
-                    bbox_coords = bbox(obj.geom.coords[0])
-                    for z in zoom_level:
-                        zm_level = z
-                        print(
-                            f"""Running Download process for
-                                aoi : {obj.id} - dataset : {dataset_id} , zoom : {zm_level}"""
-                        )
-                        try:
-                            tile_size = DEFAULT_TILE_SIZE  # by default
-
-                            start, end = get_start_end_download_coords(
-                                bbox_coords, zm_level, tile_size
-                            )
-                            # start downloading
-                            download_imagery(
-                                start,
-                                end,
-                                zm_level,
-                                base_path=training_input_image_source,
-                                source=source_imagery,
-                            )
-                        except Exception as ex:
-                            raise ex
-
             ## -----------LABEL GENERATOR---------
-            logging.debug("Label Generator started")
+            logging.info("Label Generator started")
+            aoi_list = [r.id for r in aois]
+            logging.info(aoi_list)
+
             if feedback:
-                feedback_objects = Feedback.objects.filter(
-                    training__id=feedback,
-                    validated=True,
-                )
-                serialized_field = FeedbackFileSerializer(feedback_objects, many=True)
+                label = FeedbackLabel.objects.filter(feedback_aoi__in=aoi_list)
+                logging.info(label)
+
+                serialized_field = FeedbackLabelFileSerializer(label, many=True)
             else:
-                aoi_list = [r.id for r in aois]
                 label = Label.objects.filter(aoi__in=aoi_list)
                 serialized_field = LabelFileSerializer(label, many=True)
 

backend/core/urls.py

@@ -11,11 +11,13 @@
     FeedbackLabelViewset,
     FeedbackView,
     FeedbackViewset,
+    GenerateFeedbackAOIGpxView,
     GenerateGpxView,
     LabelViewSet,
     ModelViewSet,
     PredictionView,
-    RawdataApiView,
+    RawdataApiAOIView,
+    RawdataApiFeedbackView,
     TrainingViewSet,
     TrainingWorkspaceDownloadView,
     TrainingWorkspaceView,
@@ -39,15 +41,22 @@
 
 urlpatterns = [
     path("", include(router.urls)),
-    path("label/osm/fetch/<int:aoi_id>/", RawdataApiView.as_view()),
+    path("label/osm/fetch/<int:aoi_id>/", RawdataApiAOIView.as_view()),
+    path(
+        "label/feedback/osm/fetch/<int:feedbackaoi_id>/",
+        RawdataApiFeedbackView.as_view(),
+    ),
     # path("download/<int:dataset_id>/", download_training_data),
     path("training/status/<str:run_id>/", run_task_status),
     path("training/publish/<int:training_id>/", publish_training),
     path("prediction/", PredictionView.as_view()),
-    path("apply/feedback/", FeedbackView.as_view()),
+    path("feedback/training/submit/", FeedbackView.as_view()),
     path("status/", APIStatus.as_view()),
     path("geojson2osm/", geojson2osmconverter, name="geojson2osmconverter"),
     path("aoi/gpx/<int:aoi_id>/", GenerateGpxView.as_view()),
+    path(
+        "feedback-aoi/gpx/<int:feedback_aoi_id>/", GenerateFeedbackAOIGpxView.as_view()
+    ),
     path("workspace/", TrainingWorkspaceView.as_view()),
     path(
         "workspace/download/<path:lookup_dir>/", TrainingWorkspaceDownloadView.as_view()