feat(nodes): add list_images endpoint

- add `list_images` endpoint at `GET api/v1/images`
- extend `ImageStorageBase` with `list()` method, implemented it for `DiskImageStorage`
- add `ImageReponse` class to for image responses, which includes urls, metadata
- add `ImageMetadata` class (basically a stub at the moment)
- uploaded images now named `"{uuid}_{timestamp}.png"`
- add `models` modules. besides separating concerns more clearly, this helps to mitigate circular dependencies
- improve thumbnail handling

invokeai/app/api/models/images.py

@@ -0,0 +1,14 @@
+from pydantic import BaseModel, Field
+
+from invokeai.app.models.image import ImageType
+from invokeai.app.models.metadata import ImageMetadata
+
+
+class ImageResponse(BaseModel):
+    """The response type for images"""
+
+    image_type: ImageType = Field(description="The type of the image")
+    image_name: str = Field(description="The name of the image")
+    image_url: str = Field(description="The url of the image")
+    thumbnail_url: str = Field(description="The url of the image's thumbnail")
+    metadata: ImageMetadata = Field(description="The image's metadata")

invokeai/app/api/routers/images.py

@@ -1,18 +1,20 @@
 # Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)
 
 from datetime import datetime, timezone
+import uuid
 
-from fastapi import Path, Request, UploadFile
+from fastapi import Path, Query, Request, UploadFile
 from fastapi.responses import FileResponse, Response
 from fastapi.routing import APIRouter
 from PIL import Image
+from invokeai.app.api.models.images import ImageResponse
+from invokeai.app.services.item_storage import PaginatedResults
 
 from ...services.image_storage import ImageType
 from ..dependencies import ApiDependencies
 
 images_router = APIRouter(prefix="/v1/images", tags=["images"])
 
-
 @images_router.get("/{image_type}/{image_name}", operation_id="get_image")
 async def get_image(
     image_type: ImageType = Path(description="The type of image to get"),
@@ -53,14 +55,30 @@ async def upload_image(file: UploadFile, request: Request):
         # Error opening the image
         return Response(status_code=415)
 
-    filename = f"{str(int(datetime.now(timezone.utc).timestamp()))}.png"
+    filename = f"{uuid.uuid4()}_{str(int(datetime.now(timezone.utc).timestamp()))}.png"
     ApiDependencies.invoker.services.images.save(ImageType.UPLOAD, filename, im)
 
     return Response(
         status_code=201,
         headers={
             "Location": request.url_for(
-                "get_image", image_type=ImageType.UPLOAD, image_name=filename
+                "get_image", image_type=ImageType.UPLOAD.value, image_name=filename
             )
         },
     )
+
+@images_router.get(
+    "/",
+    operation_id="list_images",
+    responses={200: {"model": PaginatedResults[ImageResponse]}},
+)
+async def list_images(
+    image_type: ImageType = Query(default=ImageType.RESULT, description="The type of images to get"),
+    page: int = Query(default=0, description="The page of images to get"),
+    per_page: int = Query(default=10, description="The number of images per page"),
+) -> PaginatedResults[ImageResponse]:
+    """Gets a list of images"""
+    result = ApiDependencies.invoker.services.images.list(
+        image_type, page, per_page
+    )
+    return result

invokeai/app/cli/commands.py

@@ -6,7 +6,8 @@ from typing import Any, Callable, Iterable, Literal, get_args, get_origin, get_t
 from pydantic import BaseModel, Field
 import networkx as nx
 import matplotlib.pyplot as plt
-from ..invocations.image import ImageField
+
+from ..models.image import ImageField
 from ..services.graph import GraphExecutionState
 from ..services.invoker import Invoker
 

invokeai/app/invocations/cv.py

@@ -7,9 +7,9 @@ import numpy
 from PIL import Image, ImageOps
 from pydantic import Field
 
-from ..services.image_storage import ImageType
+from invokeai.app.models.image import ImageField, ImageType
 from .baseinvocation import BaseInvocation, InvocationContext
-from .image import ImageField, ImageOutput
+from .image import ImageOutput
 
 
 class CvInpaintInvocation(BaseInvocation):

invokeai/app/invocations/generate.py

@@ -8,12 +8,13 @@ from torch import Tensor
 
 from pydantic import Field
 
-from ..services.image_storage import ImageType
+from invokeai.app.models.image import ImageField, ImageType
 from .baseinvocation import BaseInvocation, InvocationContext
-from .image import ImageField, ImageOutput
+from .image import ImageOutput
 from ...backend.generator import Txt2Img, Img2Img, Inpaint, InvokeAIGenerator
 from ...backend.stable_diffusion import PipelineIntermediateState
-from ..util.util import diffusers_step_callback_adapter, CanceledException
+from ..models.exceptions import CanceledException
+from ..util.step_callback import diffusers_step_callback_adapter
 
 SAMPLER_NAME_VALUES = Literal[
     tuple(InvokeAIGenerator.schedulers())

invokeai/app/invocations/image.py

@@ -7,20 +7,10 @@ import numpy
 from PIL import Image, ImageFilter, ImageOps
 from pydantic import BaseModel, Field
 
-from ..services.image_storage import ImageType
+from ..models.image import ImageField, ImageType
 from ..services.invocation_services import InvocationServices
 from .baseinvocation import BaseInvocation, BaseInvocationOutput, InvocationContext
 
-
-class ImageField(BaseModel):
-    """An image field used for passing image objects between invocations"""
-
-    image_type: str = Field(
-        default=ImageType.RESULT, description="The type of the image"
-    )
-    image_name: Optional[str] = Field(default=None, description="The name of the image")
-
-
 class ImageOutput(BaseInvocationOutput):
     """Base class for invocations that output an image"""
     #fmt: off

invokeai/app/invocations/reconstruct.py

@@ -3,10 +3,10 @@ from typing import Literal, Union
 
 from pydantic import Field
 
-from ..services.image_storage import ImageType
+from invokeai.app.models.image import ImageField, ImageType
 from ..services.invocation_services import InvocationServices
 from .baseinvocation import BaseInvocation, InvocationContext
-from .image import ImageField, ImageOutput
+from .image import ImageOutput
 
 class RestoreFaceInvocation(BaseInvocation):
     """Restores faces in an image."""

invokeai/app/invocations/upscale.py

@@ -5,10 +5,10 @@ from typing import Literal, Union
 
 from pydantic import Field
 
-from ..services.image_storage import ImageType
+from invokeai.app.models.image import ImageField, ImageType
 from ..services.invocation_services import InvocationServices
 from .baseinvocation import BaseInvocation, InvocationContext
-from .image import ImageField, ImageOutput
+from .image import ImageOutput
 
 
 class UpscaleInvocation(BaseInvocation):

invokeai/app/models/exceptions.py

@@ -0,0 +1,3 @@
+class CanceledException(Exception):
+    """Execution canceled by user."""
+    pass

invokeai/app/models/image.py

@@ -0,0 +1,26 @@
+from enum import Enum
+from typing import Optional
+from pydantic import BaseModel, Field
+
+
+class ImageType(str, Enum):
+    RESULT = "results"
+    INTERMEDIATE = "intermediates"
+    UPLOAD = "uploads"
+
+
+class ImageField(BaseModel):
+    """An image field used for passing image objects between invocations"""
+
+    image_type: str = Field(
+        default=ImageType.RESULT, description="The type of the image"
+    )
+    image_name: Optional[str] = Field(default=None, description="The name of the image")
+
+    class Config:
+        schema_extra = {
+            "required": [
+                "image_type",
+                "image_name",
+            ]
+        }

invokeai/app/models/metadata.py

@@ -0,0 +1,11 @@
+from typing import Optional
+from pydantic import BaseModel, Field
+
+class ImageMetadata(BaseModel):
+    """An image's metadata"""
+
+    timestamp: float = Field(description="The creation timestamp of the image")
+    width: int = Field(description="The width of the image in pixels")
+    height: int = Field(description="The height of the image in pixels")
+    # TODO: figure out metadata
+    sd_metadata: Optional[dict] = Field(default={}, description="The image's SD-specific metadata")

invokeai/app/services/image_storage.py

@@ -2,24 +2,25 @@
 
 import datetime
 import os
+from glob import glob
 from abc import ABC, abstractmethod
 from enum import Enum
 from pathlib import Path
 from queue import Queue
-from typing import Dict
+from typing import Callable, Dict, List
 
 from PIL.Image import Image
+import PIL.Image as PILImage
+from pydantic import BaseModel
+from invokeai.app.api.models.images import ImageResponse
+from invokeai.app.models.image import ImageField, ImageType
+from invokeai.app.models.metadata import ImageMetadata
+from invokeai.app.services.item_storage import PaginatedResults
 from invokeai.app.util.save_thumbnail import save_thumbnail
 
 from invokeai.backend.image_util import PngWriter
 
 
-class ImageType(str, Enum):
-    RESULT = "results"
-    INTERMEDIATE = "intermediates"
-    UPLOAD = "uploads"
-
-
 class ImageStorageBase(ABC):
     """Responsible for storing and retrieving images."""
 
@@ -27,9 +28,17 @@ class ImageStorageBase(ABC):
     def get(self, image_type: ImageType, image_name: str) -> Image:
         pass
 
+    @abstractmethod
+    def list(
+        self, image_type: ImageType, page: int = 0, per_page: int = 10
+    ) -> PaginatedResults[ImageResponse]:
+        pass
+
     # TODO: make this a bit more flexible for e.g. cloud storage
     @abstractmethod
-    def get_path(self, image_type: ImageType, image_name: str) -> str:
+    def get_path(
+        self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
+    ) -> str:
         pass
 
     @abstractmethod
@@ -71,19 +80,74 @@ class DiskImageStorage(ImageStorageBase):
                 parents=True, exist_ok=True
             )
 
+    def list(
+        self, image_type: ImageType, page: int = 0, per_page: int = 10
+    ) -> PaginatedResults[ImageResponse]:
+        dir_path = os.path.join(self.__output_folder, image_type)
+        image_paths = glob(f"{dir_path}/*.png")
+        count = len(image_paths)
+
+        sorted_image_paths = sorted(
+            glob(f"{dir_path}/*.png"), key=os.path.getctime, reverse=True
+        )
+
+        page_of_image_paths = sorted_image_paths[
+            page * per_page : (page + 1) * per_page
+        ]
+
+        page_of_images: List[ImageResponse] = []
+
+        for path in page_of_image_paths:
+            filename = os.path.basename(path)
+            img = PILImage.open(path)
+            page_of_images.append(
+                ImageResponse(
+                    image_type=image_type.value,
+                    image_name=filename,
+                    # TODO: DiskImageStorage should not be building URLs...?
+                    image_url=f"api/v1/images/{image_type.value}/{filename}",
+                    thumbnail_url=f"api/v1/images/{image_type.value}/thumbnails/{os.path.splitext(filename)[0]}.webp",
+                    # TODO: Creation of this object should happen elsewhere, just making it fit here so it works
+                    metadata=ImageMetadata(
+                        timestamp=os.path.getctime(path),
+                        width=img.width,
+                        height=img.height,
+                    ),
+                )
+            )
+
+        page_count_trunc = int(count / per_page)
+        page_count_mod = count % per_page
+        page_count = page_count_trunc if page_count_mod == 0 else page_count_trunc + 1
+
+        return PaginatedResults[ImageResponse](
+            items=page_of_images,
+            page=page,
+            pages=page_count,
+            per_page=per_page,
+            total=count,
+        )
+
     def get(self, image_type: ImageType, image_name: str) -> Image:
         image_path = self.get_path(image_type, image_name)
         cache_item = self.__get_cache(image_path)
         if cache_item:
             return cache_item
 
-        image = Image.open(image_path)
+        image = PILImage.open(image_path)
         self.__set_cache(image_path, image)
         return image
 
     # TODO: make this a bit more flexible for e.g. cloud storage
-    def get_path(self, image_type: ImageType, image_name: str) -> str:
+    def get_path(
-        path = os.path.join(self.__output_folder, image_type, image_name)
+        self, image_type: ImageType, image_name: str, is_thumbnail: bool = False
+    ) -> str:
+        if is_thumbnail:
+            path = os.path.join(
+                self.__output_folder, image_type, "thumbnails", image_name
+            )
+        else:
+            path = os.path.join(self.__output_folder, image_type, image_name)
         return path
 
     def save(self, image_type: ImageType, image_name: str, image: Image) -> None:
@@ -101,12 +165,19 @@ class DiskImageStorage(ImageStorageBase):
 
     def delete(self, image_type: ImageType, image_name: str) -> None:
         image_path = self.get_path(image_type, image_name)
+        thumbnail_path = self.get_path(image_type, image_name, True)
         if os.path.exists(image_path):
             os.remove(image_path)
 
         if image_path in self.__cache:
             del self.__cache[image_path]
 
+        if os.path.exists(thumbnail_path):
+            os.remove(thumbnail_path)
+
+        if thumbnail_path in self.__cache:
+            del self.__cache[thumbnail_path]
+
     def __get_cache(self, image_name: str) -> Image:
         return None if image_name not in self.__cache else self.__cache[image_name]
 

invokeai/app/services/processor.py

@@ -4,7 +4,7 @@ from threading import Event, Thread
 from ..invocations.baseinvocation import InvocationContext
 from .invocation_queue import InvocationQueueItem
 from .invoker import InvocationProcessorABC, Invoker
-from ..util.util import CanceledException
+from ..models.exceptions import CanceledException
 
 class DefaultInvocationProcessor(InvocationProcessorABC):
     __invoker_thread: Thread

invokeai/app/util/step_callback.py

@@ -1,14 +1,16 @@
 import torch
-from PIL import Image
 from ..invocations.baseinvocation import InvocationContext
 from ...backend.util.util import image_to_dataURL
 from ...backend.generator.base import Generator
 from ...backend.stable_diffusion import PipelineIntermediateState
 
-class CanceledException(Exception):
+def fast_latents_step_callback(
-    pass
+    sample: torch.Tensor,
-
+    step: int,
-def fast_latents_step_callback(sample: torch.Tensor, step: int, steps: int, id: str, context: InvocationContext, ):
+    steps: int,
+    id: str,
+    context: InvocationContext,
+):
     # TODO: only output a preview image when requested
     image = Generator.sample_to_lowres_estimated_image(sample)
 
@@ -21,15 +23,12 @@ def fast_latents_step_callback(sample: torch.Tensor, step: int, steps: int, id:
     context.services.events.emit_generator_progress(
         context.graph_execution_state_id,
         id,
-        {
+        {"width": width, "height": height, "dataURL": dataURL},
-            "width": width,
-            "height": height,
-            "dataURL": dataURL
-        },
         step,
         steps,
     )
 
+
 def diffusers_step_callback_adapter(*cb_args, **kwargs):
     """
     txt2img gives us a Tensor in the step_callbak, while img2img gives us a PipelineIntermediateState.
@@ -37,6 +36,8 @@ def diffusers_step_callback_adapter(*cb_args, **kwargs):
     """
     if isinstance(cb_args[0], PipelineIntermediateState):
         progress_state: PipelineIntermediateState = cb_args[0]
-        return fast_latents_step_callback(progress_state.latents, progress_state.step, **kwargs)
+        return fast_latents_step_callback(
+            progress_state.latents, progress_state.step, **kwargs
+        )
     else:
         return fast_latents_step_callback(*cb_args, **kwargs)