nodes/kijai-ComfyUI-SCAIL-Pose
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Add options to disable hand/face drawing separately

Browse Source
This commit is contained in:
kijai
2025-12-14 21:35:23 +02:00
parent 93059f0fe4
commit b3cdd86997
2 changed files with 9 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files
NLFPoseExtract/nlf_render.py
+2 -2
View File
@@ -146,7 +146,7 @@ def collect_smpl_poses_samurai(data):
def render_nlf_as_images(smpl_poses, dw_poses, height, width, video_length, intrinsic_matrix=None, draw_2d=True):
def render_nlf_as_images(smpl_poses, dw_poses, height, width, video_length, intrinsic_matrix=None, draw_2d=True, draw_face=True, draw_hands=True):
""" return a list of images """
base_colors_255_dict = {
@@ -244,7 +244,7 @@ def render_nlf_as_images(smpl_poses, dw_poses, height, width, video_length, intr
frames_np_rgba = render_whole(cylinder_specs_list, H=height, W=width, fx=focal_x, fy=focal_y, cx=princpt[0], cy=princpt[1])
if dw_poses is not None and draw_2d:
canvas_2d = draw_pose_to_canvas_np(aligned_poses, pool=None, H=height, W=width, reshape_scale=0, show_feet_flag=False, show_body_flag=False, show_cheek_flag=True, dw_hand=True)
canvas_2d = draw_pose_to_canvas_np(aligned_poses, pool=None, H=height, W=width, reshape_scale=0, show_feet_flag=False, show_body_flag=False, show_cheek_flag=True, dw_hand=True, show_face_flag=draw_face, show_hand_flag=draw_hands)
for i in range(len(frames_np_rgba)):
frame_img = frames_np_rgba[i]
nodes.py
+7 -3
View File
@@ -164,6 +164,8 @@ class RenderNLFPoses:
"optional": {
"dw_poses": ("DWPOSES", {"default": None, "tooltip": "Optional DW pose model for 2D drawing"}),
"ref_dw_pose": ("DWPOSES", {"default": None, "tooltip": "Optional reference DW pose model for alignment"}),
"draw_face": ("BOOLEAN", {"default": True, "tooltip": "Whether to draw face keypoints"}),
"draw_hands": ("BOOLEAN", {"default": True, "tooltip": "Whether to draw hand keypoints"}),
}
}
@@ -172,7 +174,7 @@ class RenderNLFPoses:
FUNCTION = "predict"
CATEGORY = "WanVideoWrapper"
def predict(self, nlf_poses, width, height, dw_poses=None, ref_dw_pose=None):
def predict(self, nlf_poses, width, height, dw_poses=None, ref_dw_pose=None, draw_face=True, draw_hands=True):
from .NLFPoseExtract.nlf_render import render_nlf_as_images, shift_dwpose_according_to_nlf, process_data_to_COCO_format, intrinsic_matrix_from_field_of_view
from .NLFPoseExtract.align3d import solve_new_camera_params_central, solve_new_camera_params_down
@@ -224,9 +226,11 @@ class RenderNLFPoses:
logging.info(f"Scale - m: {scale_m}, face: {scale_face}")
shift_dwpose_according_to_nlf(pose_input, dw_pose_input, ori_camera_pose, new_camera_intrinsics, height, width)
frames_np = render_nlf_as_images(pose_input, dw_pose_input, height, width, len(pose_input), intrinsic_matrix=new_camera_intrinsics)
intrinsic_matrix = new_camera_intrinsics
else:
frames_np = render_nlf_as_images(pose_input, dw_pose_input, height, width, len(pose_input), intrinsic_matrix=ori_camera_pose)
intrinsic_matrix = ori_camera_pose
frames_np = render_nlf_as_images(pose_input, dw_pose_input, height, width, len(pose_input), intrinsic_matrix=intrinsic_matrix, draw_face=draw_face, draw_hands=draw_hands)
frames_tensor = torch.from_numpy(np.stack(frames_np, axis=0)).contiguous() / 255.0
frames_tensor, mask = frames_tensor[..., :3], frames_tensor[..., -1] > 0.5