feat(nodes): move fully* to new images service

* except i haven't rebuilt inpaint in latents

invokeai/app/invocations/latent.py

@@ -3,7 +3,7 @@
 import random
 from typing import Literal, Optional, Union
 import einops
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, Field, validator
 import torch
 
 from invokeai.app.invocations.util.choose_model import choose_model
@@ -23,7 +23,7 @@ from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationCont
 import numpy as np
 from ..services.image_file_storage import ImageType
 from .baseinvocation import BaseInvocation, InvocationContext
-from .image import ImageField, ImageOutput, build_image_output
+from .image import ImageField, ImageOutput
 from .compel import ConditioningField
 from ...backend.stable_diffusion import PipelineIntermediateState
 from diffusers.schedulers import SchedulerMixin as Scheduler
@@ -362,19 +362,9 @@ class LatentsToImageInvocation(BaseInvocation):
             np_image = model.decode_latents(latents)
             image = model.numpy_to_pil(np_image)[0]
 
-            # image_type = ImageType.RESULT
-            # image_name = context.services.images.create_name(
-            #     context.graph_execution_state_id, self.id
-            # )
+            torch.cuda.empty_cache()
 
-            # metadata = context.services.metadata.build_metadata(
-            #     session_id=context.graph_execution_state_id, node=self
-            # )
-
-            # torch.cuda.empty_cache()
-
-            # context.services.images.save(image_type, image_name, image, metadata)
-            image_dto = context.services.images_new.create(
+            image_dto = context.services.images.create(
                 image=image,
                 image_type=ImageType.RESULT,
                 image_category=ImageCategory.GENERAL,
@@ -382,10 +372,13 @@ class LatentsToImageInvocation(BaseInvocation):
                 node_id=self.id,
             )
 
-            return build_image_output(
-                image_type=image_dto.image_type,
-                image_name=image_dto.image_name,
-                image=image,
+            return ImageOutput(
+                image=ImageField(
+                    image_name=image_dto.image_name,
+                    image_type=image_dto.image_type,
+                ),
+                width=image_dto.width,
+                height=image_dto.height,
             )
 
 
@@ -474,7 +467,7 @@ class ImageToLatentsInvocation(BaseInvocation):
 
     @torch.no_grad()
     def invoke(self, context: InvocationContext) -> LatentsOutput:
-        image = context.services.images.get(
+        image = context.services.images.get_pil_image(
             self.image.image_type, self.image.image_name
         )
 
@@ -496,3 +489,4 @@ class ImageToLatentsInvocation(BaseInvocation):
         name = f"{context.graph_execution_state_id}__{self.id}"
         context.services.latents.save(name, latents)
         return build_latents_output(latents_name=name, latents=latents)
+