feat(nodes): address feedback

- Address database feedback:
  - Remove all the extraneous tables. Only an `images` table now:
  - Image type and category are unrestricted strings. When creating images, the provided values are checked to ensure they are a valid type and category.
  - Add `updated_at` and `deleted_at` columns. `deleted_at` is currently unused.
  - Use SQLite's built-in timestamp features to populate these. Add a trigger to update `updated_at` when the row is updated. Currently no way to update a row.
  - Rename the `id` column in `images` to `image_name`
- Rename `ImageCategory.IMAGE` to `ImageCategory.GENERAL`
- Move all exceptions outside their base classes to make them more portable.
- Add `width` and `height` columns to the database. These store the actual dimensions of the image file, whereas the metadata's `width` and `height` refer to the respective generation parameters and are nullable.
- Make `deserialize_image_record` take a `dict` instead of `sqlite3.Row`
- Improve comments throughout
- Tidy up unused code/files and some minor organisation

Author: psychedelicious

invokeai/app/api/routers/images.py

@@ -30,7 +30,7 @@ async def upload_image(
     image_type: ImageType,
     request: Request,
     response: Response,
-    image_category: ImageCategory = ImageCategory.IMAGE,
+    image_category: ImageCategory = ImageCategory.GENERAL,
 ) -> ImageDTO:
     """Uploads an image"""
     if not file.content_type.startswith("image"):

invokeai/app/invocations/generate.py

@@ -95,7 +95,7 @@ def invoke(self, context: InvocationContext) -> ImageOutput:
         image_dto = context.services.images_new.create(
             image=generate_output.image,
             image_type=ImageType.RESULT,
-            image_category=ImageCategory.IMAGE,
+            image_category=ImageCategory.GENERAL,
             session_id=context.graph_execution_state_id,
             node_id=self.id,
         )
@@ -119,7 +119,7 @@ def invoke(self, context: InvocationContext) -> ImageOutput:
         # context.services.images_db.set(
         #     id=image_name,
         #     image_type=ImageType.RESULT,
-        #     image_category=ImageCategory.IMAGE,
+        #     image_category=ImageCategory.GENERAL,
         #     session_id=context.graph_execution_state_id,
         #     node_id=self.id,
         #     metadata=GeneratedImageOrLatentsMetadata(),

invokeai/app/invocations/latent.py

@@ -372,7 +372,7 @@ def invoke(self, context: InvocationContext) -> ImageOutput:
             image_dto = context.services.images_new.create(
                 image=image,
                 image_type=ImageType.RESULT,
-                image_category=ImageCategory.IMAGE,
+                image_category=ImageCategory.GENERAL,
                 session_id=context.graph_execution_state_id,
                 node_id=self.id,
             )

invokeai/app/models/image.py

@@ -2,7 +2,7 @@
 from typing import Optional, Tuple
 from pydantic import BaseModel, Field
 
-from invokeai.app.util.enum import MetaEnum
+from invokeai.app.util.metaenum import MetaEnum
 
 
 class ImageType(str, Enum, metaclass=MetaEnum):
@@ -13,20 +13,32 @@ class ImageType(str, Enum, metaclass=MetaEnum):
     INTERMEDIATE = "intermediates"
 
 
+class InvalidImageTypeException(ValueError):
+    """Raised when a provided value is not a valid ImageType.
+
+    Subclasses `ValueError`.
+    """
+
+    def __init__(self, message="Invalid image type."):
+        super().__init__(message)
+
+
 class ImageCategory(str, Enum, metaclass=MetaEnum):
     """The category of an image. Use ImageCategory.OTHER for non-default categories."""
 
-    IMAGE = "image"
-    CONTROL_IMAGE = "control_image"
+    GENERAL = "general"
+    CONTROL = "control"
     OTHER = "other"
 
 
-def is_image_type(obj):
-    try:
-        ImageType(obj)
-    except ValueError:
-        return False
-    return True
+class InvalidImageCategoryException(ValueError):
+    """Raised when a provided value is not a valid ImageCategory.
+
+    Subclasses `ValueError`.
+    """
+
+    def __init__(self, message="Invalid image category."):
+        super().__init__(message)
 
 
 class ImageField(BaseModel):

invokeai/app/models/metadata.py

@@ -26,50 +26,66 @@ class Config:
         default=None,
         description="The type of the ancestor node of the image output node.",
     )
+    """The type of the ancestor node of the image output node."""
     positive_conditioning: Optional[StrictStr] = Field(
         default=None, description="The positive conditioning."
     )
+    """The positive conditioning"""
     negative_conditioning: Optional[StrictStr] = Field(
         default=None, description="The negative conditioning."
     )
+    """The negative conditioning"""
     width: Optional[StrictInt] = Field(
         default=None, description="Width of the image/latents in pixels."
     )
+    """Width of the image/latents in pixels"""
     height: Optional[StrictInt] = Field(
         default=None, description="Height of the image/latents in pixels."
     )
+    """Height of the image/latents in pixels"""
     seed: Optional[StrictInt] = Field(
         default=None, description="The seed used for noise generation."
     )
+    """The seed used for noise generation"""
     cfg_scale: Optional[StrictFloat] = Field(
         default=None, description="The classifier-free guidance scale."
     )
+    """The classifier-free guidance scale"""
     steps: Optional[StrictInt] = Field(
         default=None, description="The number of steps used for inference."
     )
+    """The number of steps used for inference"""
     scheduler: Optional[StrictStr] = Field(
         default=None, description="The scheduler used for inference."
     )
+    """The scheduler used for inference"""
     model: Optional[StrictStr] = Field(
         default=None, description="The model used for inference."
     )
+    """The model used for inference"""
     strength: Optional[StrictFloat] = Field(
         default=None,
         description="The strength used for image-to-image/latents-to-latents.",
     )
+    """The strength used for image-to-image/latents-to-latents."""
     latents: Optional[StrictStr] = Field(
         default=None, description="The ID of the initial latents."
     )
+    """The ID of the initial latents"""
     vae: Optional[StrictStr] = Field(
         default=None, description="The VAE used for decoding."
     )
+    """The VAE used for decoding"""
     unet: Optional[StrictStr] = Field(
         default=None, description="The UNet used dor inference."
     )
+    """The UNet used dor inference"""
     clip: Optional[StrictStr] = Field(
         default=None, description="The CLIP Encoder used for conditioning."
     )
+    """The CLIP Encoder used for conditioning"""
     extra: Optional[StrictStr] = Field(
         default=None,
         description="Uploaded image metadata, extracted from the PNG tEXt chunk.",
     )
+    """Uploaded image metadata, extracted from the PNG tEXt chunk."""