From 6f77477a1c881a73b204efab4d803f9585575312 Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Tue, 27 Feb 2024 20:29:43 +0530
Subject: [PATCH 1/2] cleanup: remove manual offload from depth anything

---
 invokeai/app/invocations/controlnet_image_processors.py | 5 ++---
 invokeai/backend/image_util/depth_anything/__init__.py  | 5 +----
 2 files changed, 3 insertions(+), 7 deletions(-)

diff --git a/invokeai/app/invocations/controlnet_image_processors.py b/invokeai/app/invocations/controlnet_image_processors.py
index 9eba3acdca..610dbd433f 100644
--- a/invokeai/app/invocations/controlnet_image_processors.py
+++ b/invokeai/app/invocations/controlnet_image_processors.py
@@ -576,7 +576,7 @@ DEPTH_ANYTHING_MODEL_SIZES = Literal["large", "base", "small"]
     title="Depth Anything Processor",
     tags=["controlnet", "depth", "depth anything"],
     category="controlnet",
-    version="1.0.0",
+    version="1.0.1",
 )
 class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
     """Generates a depth map based on the Depth Anything algorithm"""
@@ -585,13 +585,12 @@ class DepthAnythingImageProcessorInvocation(ImageProcessorInvocation):
         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: Image.Image):
         depth_anything_detector = DepthAnythingDetector()
         depth_anything_detector.load_model(model_size=self.model_size)
 
-        processed_image = depth_anything_detector(image=image, resolution=self.resolution, offload=self.offload)
+        processed_image = depth_anything_detector(image=image, resolution=self.resolution)
         return processed_image
 
 
diff --git a/invokeai/backend/image_util/depth_anything/__init__.py b/invokeai/backend/image_util/depth_anything/__init__.py
index fcd600b99e..ddb0aaa0c4 100644
--- a/invokeai/backend/image_util/depth_anything/__init__.py
+++ b/invokeai/backend/image_util/depth_anything/__init__.py
@@ -84,7 +84,7 @@ class DepthAnythingDetector:
         self.model.to(device)
         return self
 
-    def __call__(self, image, resolution=512, offload=False):
+    def __call__(self, image, resolution=512):
         image = np.array(image, dtype=np.uint8)
         image = image[:, :, ::-1] / 255.0
 
@@ -103,7 +103,4 @@ class DepthAnythingDetector:
         new_height = int(image_height * (resolution / image_width))
         depth_map = depth_map.resize((resolution, new_height))
 
-        if offload:
-            del self.model
-
         return depth_map

From 41b77cd5ff70804b1740bae09143ff529bd370a7 Mon Sep 17 00:00:00 2001
From: blessedcoolant <54517381+blessedcoolant@users.noreply.github.com>
Date: Tue, 27 Feb 2024 20:50:15 +0530
Subject: [PATCH 2/2] fix: minor fixes to types in the DA Detector

---
 .../image_util/depth_anything/__init__.py     | 23 +++++++++++--------
 1 file changed, 14 insertions(+), 9 deletions(-)

diff --git a/invokeai/backend/image_util/depth_anything/__init__.py b/invokeai/backend/image_util/depth_anything/__init__.py
index ddb0aaa0c4..78b828d816 100644
--- a/invokeai/backend/image_util/depth_anything/__init__.py
+++ b/invokeai/backend/image_util/depth_anything/__init__.py
@@ -17,6 +17,8 @@ from invokeai.backend.util.util import download_with_progress_bar
 
 config = InvokeAIAppConfig.get_config()
 
+DEPTH_ANYTHING_MODEL_SIZES = Literal["large", "base", "small"]
+
 DEPTH_ANYTHING_MODELS = {
     "large": {
         "url": "https://huggingface.co/spaces/LiheYoung/Depth-Anything/resolve/main/checkpoints/depth_anything_vitl14.pth?download=true",
@@ -53,9 +55,9 @@ transform = Compose(
 class DepthAnythingDetector:
     def __init__(self) -> None:
         self.model = None
-        self.model_size: Union[Literal["large", "base", "small"], None] = None
+        self.model_size: Union[DEPTH_ANYTHING_MODEL_SIZES, None] = None
 
-    def load_model(self, model_size=Literal["large", "base", "small"]):
+    def load_model(self, model_size: DEPTH_ANYTHING_MODEL_SIZES = "small"):
         DEPTH_ANYTHING_MODEL_PATH = pathlib.Path(config.models_path / DEPTH_ANYTHING_MODELS[model_size]["local"])
         if not DEPTH_ANYTHING_MODEL_PATH.exists():
             download_with_progress_bar(DEPTH_ANYTHING_MODELS[model_size]["url"], DEPTH_ANYTHING_MODEL_PATH)
@@ -84,16 +86,19 @@ class DepthAnythingDetector:
         self.model.to(device)
         return self
 
-    def __call__(self, image, resolution=512):
-        image = np.array(image, dtype=np.uint8)
-        image = image[:, :, ::-1] / 255.0
+    def __call__(self, image: Image.Image, resolution: int = 512):
+        if self.model is None:
+            raise Exception("Depth Anything Model not loaded")
 
-        image_height, image_width = image.shape[:2]
-        image = transform({"image": image})["image"]
-        image = torch.from_numpy(image).unsqueeze(0).to(choose_torch_device())
+        np_image = np.array(image, dtype=np.uint8)
+        np_image = np_image[:, :, ::-1] / 255.0
+
+        image_height, image_width = np_image.shape[:2]
+        np_image = transform({"image": image})["image"]
+        tensor_image = torch.from_numpy(np_image).unsqueeze(0).to(choose_torch_device())
 
         with torch.no_grad():
-            depth = self.model(image)
+            depth = self.model(tensor_image)
             depth = F.interpolate(depth[None], (image_height, image_width), mode="bilinear", align_corners=False)[0, 0]
             depth = (depth - depth.min()) / (depth.max() - depth.min()) * 255.0