moved object definitions into separate files

core/database/classes/__init__.py

@@ -0,0 +1,4 @@
+from __future__ import annotations
+
+from .exceptions import NoDocumentFoundException
+from .visual_communication import VisualCommunication

core/database/classes/exceptions.py

@@ -0,0 +1,5 @@
+from __future__ import annotations
+
+
+class NoDocumentFoundException(Exception):
+    pass

core/database/classes/visual_communication.py

@@ -0,0 +1,78 @@
+from __future__ import annotations
+
+import logging
+from base64 import b64decode
+from base64 import b64encode
+from io import BytesIO
+from pathlib import Path
+
+from PIL import Image
+from pydantic import BaseModel
+from pydantic import field_serializer
+from pydantic import field_validator
+
+from core.dto import ModelData
+
+
+class VisualCommunication(BaseModel):
+    name: str
+    image: Image.Image
+    annotation: ModelData | None = None
+    prediction: ModelData | None = None
+
+    class Config:
+        arbitrary_types_allowed = True
+
+    @classmethod
+    def classname(cls) -> str:
+        """Return classname."""
+        return cls.__name__
+
+    @classmethod
+    def from_file(cls, path: Path) -> VisualCommunication:
+        """Instantiate from file."""
+        name = path.stem
+        image = Image.open(path)
+        image.load()
+        return VisualCommunication(name=name, image=image)
+
+    @classmethod
+    def decode_image(cls, content: str) -> Image.Image:
+        """Decode image."""
+        _, content_data = content.split(',')
+        return Image.open(BytesIO(b64decode(content_data)))
+
+    @field_serializer('image')
+    def serialize_image(image: Image.Image) -> bytes:   # type: ignore
+        buffer = BytesIO()
+        image.save(buffer, format='JPEG')
+        return buffer.getvalue()
+
+    @field_validator('image', mode='before')
+    @classmethod
+    def convert_to_image(
+        cls,
+        image: Image.Image | BytesIO | bytes,
+    ) -> Image.Image:
+        if isinstance(image, bytes):
+            image = BytesIO(image)
+        if isinstance(image, BytesIO):
+            image = Image.open(image)
+        return image
+
+    def __repr__(self) -> str:
+        return f"{self.classname()}(name='{self.name}')"
+
+    def webencoded_image(self) -> str:
+        """Convert image to be displayed on webpage."""
+        # convert images to bytes string
+        buffer = BytesIO()
+        self.image.save(buffer, format='png')
+        img_enc = b64encode(buffer.getvalue()).decode('utf-8')
+        return f"data:image/png;base64, {img_enc}"
+
+    def generate_random_prediction(self, force: bool = False) -> None:
+        """Generate random prediction values."""
+        if not force and self.prediction is not None:
+            logging.warning('set force=True to overwrite existing values.')
+        self.prediction = ModelData.from_random()