Initial add of support for DWPose preprocessor for ControlNet depth control.

invokeai/app/invocations/controlnet_image_processors.py

@@ -6,9 +6,11 @@ from typing import Dict, List, Literal, Optional, Union
 
 import cv2
 import numpy as np
+import torch
 from controlnet_aux import (
     CannyDetector,
     ContentShuffleDetector,
+    DWposeDetector,
     HEDdetector,
     LeresDetector,
     LineartAnimeDetector,
@@ -589,3 +591,27 @@ class ColorMapImageProcessorInvocation(ImageProcessorInvocation):
         color_map = cv2.resize(color_map, (width, height), interpolation=cv2.INTER_NEAREST)
         color_map = Image.fromarray(color_map)
         return color_map
+
+
+@invocation(
+    "dwpose_image_processor",
+    title="DWPose Processor",
+    tags=["controlnet", "dwpose", "pose"],
+    category="controlnet",
+    version="1.0.0",
+)
+class DWPoseImageProcessorInvocation(ImageProcessorInvocation):
+    """Applies DW-Pose processing to image"""
+
+    detect_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.detect_res)
+    image_resolution: int = InputField(default=512, ge=0, description=FieldDescriptions.image_res)
+
+    def run_processor(self, image):
+        device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+        dwpose_processor = DWposeDetector(device=device)
+        processed_image = dwpose_processor(
+            image,
+            detect_resolution=self.detect_resolution,
+            image_resolution=self.image_resolution,
+        )
+        return processed_image