refactor DWOpenPose and add type hints

invokeai/app/invocations/controlnet_image_processors.py

@@ -39,7 +39,7 @@ from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.app.util.controlnet_utils import CONTROLNET_MODE_VALUES, CONTROLNET_RESIZE_VALUES, heuristic_resize
 from invokeai.backend.image_util.canny import get_canny_edges
 from invokeai.backend.image_util.depth_anything import DEPTH_ANYTHING_MODELS, DepthAnythingDetector
-from invokeai.backend.image_util.dw_openpose import DWOpenposeDetector
+from invokeai.backend.image_util.dw_openpose import DWPOSE_MODELS, DWOpenposeDetector
 from invokeai.backend.image_util.hed import HEDProcessor
 from invokeai.backend.image_util.lineart import LineartProcessor
 from invokeai.backend.image_util.lineart_anime import LineartAnimeProcessor
@@ -633,7 +633,11 @@ class DWOpenposeImageProcessorInvocation(ImageProcessorInvocation):
     image_resolution: int = InputField(default=512, ge=1, description=FieldDescriptions.image_res)
 
     def run_processor(self, image: Image.Image, context: InvocationContext) -> Image.Image:
-        dw_openpose = DWOpenposeDetector(context)
+        mm = context.models
+        onnx_det = mm.download_and_cache_ckpt(DWPOSE_MODELS["yolox_l.onnx"])
+        onnx_pose = mm.download_and_cache_ckpt(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"])
+
+        dw_openpose = DWOpenposeDetector(onnx_det=onnx_det, onnx_pose=onnx_pose)
         processed_image = dw_openpose(
             image,
             draw_face=self.draw_face,

invokeai/backend/image_util/dw_openpose/__init__.py

@@ -1,31 +1,53 @@
+from pathlib import Path
+from typing import Dict
+
 import numpy as np
 import torch
 from controlnet_aux.util import resize_image
 from PIL import Image
 
-from invokeai.app.services.shared.invocation_context import InvocationContext
-from invokeai.backend.image_util.dw_openpose.utils import draw_bodypose, draw_facepose, draw_handpose
+from invokeai.backend.image_util.dw_openpose.utils import NDArrayInt, draw_bodypose, draw_facepose, draw_handpose
 from invokeai.backend.image_util.dw_openpose.wholebody import Wholebody
 
+DWPOSE_MODELS = {
+    "yolox_l.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true",
+    "dw-ll_ucoco_384.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true",
+}
 
-def draw_pose(pose, H, W, draw_face=True, draw_body=True, draw_hands=True, resolution=512):
+
+def draw_pose(
+    pose: Dict[str, NDArrayInt | Dict[str, NDArrayInt]],
+    H: int,
+    W: int,
+    draw_face: bool = True,
+    draw_body: bool = True,
+    draw_hands: bool = True,
+    resolution: int = 512,
+) -> Image.Image:
     bodies = pose["bodies"]
     faces = pose["faces"]
     hands = pose["hands"]
+
+    assert isinstance(bodies, dict)
     candidate = bodies["candidate"]
+
+    assert isinstance(bodies, dict)
     subset = bodies["subset"]
+
     canvas = np.zeros(shape=(H, W, 3), dtype=np.uint8)
 
     if draw_body:
         canvas = draw_bodypose(canvas, candidate, subset)
 
     if draw_hands:
+        assert isinstance(hands, np.ndarray)
         canvas = draw_handpose(canvas, hands)
 
     if draw_face:
-        canvas = draw_facepose(canvas, faces)
+        assert isinstance(hands, np.ndarray)
+        canvas = draw_facepose(canvas, faces)  # type: ignore
 
-    dwpose_image = resize_image(
+    dwpose_image: Image.Image = resize_image(
         canvas,
         resolution,
     )
@@ -40,11 +62,16 @@ class DWOpenposeDetector:
     Credits: https://github.com/IDEA-Research/DWPose
     """
 
-    def __init__(self, context: InvocationContext) -> None:
-        self.pose_estimation = Wholebody(context)
+    def __init__(self, onnx_det: Path, onnx_pose: Path) -> None:
+        self.pose_estimation = Wholebody(onnx_det=onnx_det, onnx_pose=onnx_pose)
 
     def __call__(
-        self, image: Image.Image, draw_face=False, draw_body=True, draw_hands=False, resolution=512
+        self,
+        image: Image.Image,
+        draw_face: bool = False,
+        draw_body: bool = True,
+        draw_hands: bool = False,
+        resolution: int = 512,
     ) -> Image.Image:
         np_image = np.array(image)
         H, W, C = np_image.shape
@@ -80,3 +107,6 @@ class DWOpenposeDetector:
             return draw_pose(
                 pose, H, W, draw_face=draw_face, draw_hands=draw_hands, draw_body=draw_body, resolution=resolution
             )
+
+
+__all__ = ["DWPOSE_MODELS", "DWOpenposeDetector"]

invokeai/backend/image_util/dw_openpose/utils.py

@@ -5,11 +5,13 @@ import math
 import cv2
 import matplotlib
 import numpy as np
+import numpy.typing as npt
 
 eps = 0.01
+NDArrayInt = npt.NDArray[np.uint8]
 
 
-def draw_bodypose(canvas, candidate, subset):
+def draw_bodypose(canvas: NDArrayInt, candidate: NDArrayInt, subset: NDArrayInt) -> NDArrayInt:
     H, W, C = canvas.shape
     candidate = np.array(candidate)
     subset = np.array(subset)
@@ -88,7 +90,7 @@ def draw_bodypose(canvas, candidate, subset):
     return canvas
 
 
-def draw_handpose(canvas, all_hand_peaks):
+def draw_handpose(canvas: NDArrayInt, all_hand_peaks: NDArrayInt) -> NDArrayInt:
     H, W, C = canvas.shape
 
     edges = [
@@ -142,7 +144,7 @@ def draw_handpose(canvas, all_hand_peaks):
     return canvas
 
 
-def draw_facepose(canvas, all_lmks):
+def draw_facepose(canvas: NDArrayInt, all_lmks: NDArrayInt) -> NDArrayInt:
     H, W, C = canvas.shape
     for lmks in all_lmks:
         lmks = np.array(lmks)

invokeai/backend/image_util/dw_openpose/wholebody.py

@@ -2,33 +2,26 @@
 # Modified pathing to suit Invoke
 
 
+from pathlib import Path
+
 import numpy as np
 import onnxruntime as ort
 
 from invokeai.app.services.config.config_default import get_config
-from invokeai.app.services.shared.invocation_context import InvocationContext
 from invokeai.backend.util.devices import TorchDevice
 
 from .onnxdet import inference_detector
 from .onnxpose import inference_pose
 
-DWPOSE_MODELS = {
-    "yolox_l.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/yolox_l.onnx?download=true",
-    "dw-ll_ucoco_384.onnx": "https://huggingface.co/yzd-v/DWPose/resolve/main/dw-ll_ucoco_384.onnx?download=true",
-}
-
 config = get_config()
 
 
 class Wholebody:
-    def __init__(self, context: InvocationContext):
+    def __init__(self, onnx_det: Path, onnx_pose: Path):
         device = TorchDevice.choose_torch_device()
 
         providers = ["CUDAExecutionProvider"] if device.type == "cuda" else ["CPUExecutionProvider"]
 
-        onnx_det = context.models.download_and_cache_ckpt(DWPOSE_MODELS["yolox_l.onnx"])
-        onnx_pose = context.models.download_and_cache_ckpt(DWPOSE_MODELS["dw-ll_ucoco_384.onnx"])
-
         self.session_det = ort.InferenceSession(path_or_bytes=onnx_det, providers=providers)
         self.session_pose = ort.InferenceSession(path_or_bytes=onnx_pose, providers=providers)