feat: Add Resolution to DepthAnything

invokeai/app/invocations/controlnet_image_processors.py

@@ -621,6 +621,7 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
     model_size: DEPTH_ANYTHING_MODEL_SIZES = InputField(
         default="small", description="The size of the depth model to use"
     )
+    resolution: int = InputField(default=512, ge=64, multiple_of=64, description=FieldDescriptions.image_res)
     offload: bool = InputField(default=False)
 
     def run_processor(self, image):
@@ -630,5 +631,5 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
         if image.mode == "RGBA":
             image = image.convert("RGB")
 
-        processed_image = depth_anything_detector(image=image, offload=self.offload)
+        processed_image = depth_anything_detector(image=image, resolution=self.resolution, offload=self.offload)
         return processed_image

invokeai/backend/image_util/depth_anything/__init__.py

@@ -64,12 +64,15 @@ class DepthAnythingDetector:
             del self.model
             self.model_size = model_size
 
-            if self.model_size == "small":
+            match self.model_size:
+                case "small":
                     self.model = DPT_DINOv2(encoder="vits", features=64, out_channels=[48, 96, 192, 384])
-            if self.model_size == "base":
+                case "base":
                     self.model = DPT_DINOv2(encoder="vitb", features=128, out_channels=[96, 192, 384, 768])
-            if self.model_size == "large":
+                case "large":
                     self.model = DPT_DINOv2(encoder="vitl", features=256, out_channels=[256, 512, 1024, 1024])
+                case _:
+                    raise TypeError("Not a supported model")
 
             self.model.load_state_dict(torch.load(DEPTH_ANYTHING_MODEL_PATH.as_posix(), map_location="cpu"))
             self.model.eval()
@@ -81,12 +84,11 @@ class DepthAnythingDetector:
         self.model.to(device)
         return self
 
-    def __call__(self, image, offload=False):
+    def __call__(self, image, resolution=512, offload=False):
         image = np.array(image, dtype=np.uint8)
-        original_width, original_height = image.shape[:2]
         image = image[:, :, ::-1] / 255.0
 
-        image_width, image_height = image.shape[:2]
+        image_height, image_width = image.shape[:2]
         image = transform({"image": image})["image"]
         image = torch.from_numpy(image).unsqueeze(0).to(choose_torch_device())
 
@@ -97,7 +99,9 @@ class DepthAnythingDetector:
 
         depth_map = repeat(depth, "h w -> h w 3").cpu().numpy().astype(np.uint8)
         depth_map = Image.fromarray(depth_map)
-        depth_map = depth_map.resize((original_height, original_width))
+
+        new_height = int(image_height * (resolution / image_width))
+        depth_map = depth_map.resize((resolution, new_height))
 
         if offload:
             del self.model

invokeai/frontend/web/src/features/controlAdapters/components/processors/DepthAnyThingProcessor.tsx

@@ -1,5 +1,11 @@
 import type { ComboboxOnChange } from '@invoke-ai/ui';
-import { Combobox, FormControl, FormLabel } from '@invoke-ai/ui';
+import {
+  Combobox,
+  CompositeNumberInput,
+  CompositeSlider,
+  FormControl,
+  FormLabel,
+} from '@invoke-ai/ui';
 import { useProcessorNodeChanged } from 'features/controlAdapters/components/hooks/useProcessorNodeChanged';
 import { CONTROLNET_PROCESSORS } from 'features/controlAdapters/store/constants';
 import type {
@@ -23,7 +29,7 @@ type Props = {
 
 const DepthAnythingProcessor = (props: Props) => {
   const { controlNetId, processorNode, isEnabled } = props;
-  const { model_size } = processorNode;
+  const { model_size, resolution } = processorNode;
   const processorChanged = useProcessorNodeChanged();
 
   const { t } = useTranslation();
@@ -54,6 +60,17 @@ const DepthAnythingProcessor = (props: Props) => {
     [options, model_size]
   );
 
+  const handleResolutionChange = useCallback(
+    (v: number) => {
+      processorChanged(controlNetId, { resolution: v });
+    },
+    [controlNetId, processorChanged]
+  );
+
+  const handleResolutionDefaultChange = useCallback(() => {
+    processorChanged(controlNetId, { resolution: 512 });
+  }, [controlNetId, processorChanged]);
+
   return (
     <ProcessorWrapper>
       <FormControl isDisabled={!isEnabled}>
@@ -65,6 +82,27 @@ const DepthAnythingProcessor = (props: Props) => {
           onChange={handleModelSizeChange}
         />
       </FormControl>
+      <FormControl isDisabled={!isEnabled}>
+        <FormLabel>{t('controlnet.imageResolution')}</FormLabel>
+        <CompositeSlider
+          value={resolution}
+          onChange={handleResolutionChange}
+          defaultValue={DEFAULTS.resolution}
+          min={64}
+          max={4096}
+          step={64}
+          marks
+          onReset={handleResolutionDefaultChange}
+        />
+        <CompositeNumberInput
+          value={resolution}
+          onChange={handleResolutionChange}
+          defaultValue={DEFAULTS.resolution}
+          min={64}
+          max={4096}
+          step={64}
+        />
+      </FormControl>
     </ProcessorWrapper>
   );
 };

invokeai/frontend/web/src/features/controlAdapters/store/constants.ts

@@ -95,6 +95,7 @@ export const CONTROLNET_PROCESSORS: ControlNetProcessorsDict = {
       id: 'depth_anything_image_processor',
       type: 'depth_anything_image_processor',
       model_size: 'small',
+      resolution: 512,
       offload: false,
     },
   },

invokeai/frontend/web/src/features/controlAdapters/store/types.ts

@@ -80,7 +80,7 @@ export type RequiredContentShuffleImageProcessorInvocation = O.Required<
  */
 export type RequiredDepthAnythingImageProcessorInvocation = O.Required<
   DepthAnythingImageProcessorInvocation,
-  'type' | 'model_size' | 'offload'
+  'type' | 'model_size' | 'resolution' | 'offload'
 >;
 
 export const zDepthAnythingModelSize = z.enum(['large', 'base', 'small']);