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https://github.com/comfyanonymous/ComfyUI.git
synced 2026-06-23 16:29:25 +08:00
Naming and tooltip adjustments
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kijai
parent
0d0b008b83
commit
3fe0a695b1
@ -54,10 +54,10 @@ class SAM3DBody_Loader(io.ComfyNode):
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io.Combo.Input(
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"model_file",
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options=folder_paths.get_filename_list("detection"),
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tooltip="SAM 3D Body weights (.safetensors) in the 'detection' folder",
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),
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],
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outputs=[SAM3DBodyModel.Output("model", display_name="sam3d_body_model")],
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outputs=[SAM3DBodyModel.Output(display_name="sam3d_body_model")],
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)
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@ -126,40 +126,35 @@ class SAM3DBody_Predict(io.ComfyNode):
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def define_schema(cls):
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return io.Schema(
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node_id="SAM3DBody_Predict",
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display_name="Predict SAM3D Body",
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category="image/detection/sam3dbody/",
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display_name="Run SAM3D Body Prediction",
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category="image/detection",
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inputs=[
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SAM3DBodyModel.Input("sam3d_body_model"),
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io.Image.Input("image"),
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SAM3TrackData.Input(
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"sam3_track_data", optional=True,
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tooltip=("Output of SAM3 Video Track, required for multi-person detection"),
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"track_data", optional=True,
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tooltip=("Tracking data from SAM3 Video Track, required for multi-person detection"),
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),
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io.BoundingBox.Input(
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"bboxes", optional=True, force_input=True,
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tooltip=(
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"Per-frame person boxes (e.g. RT-DETR Detect with class_name='person'). "
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"Use for better detection as alternative to SAM3 tracks."
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"Per-frame bounding boxes used for better detection. Can be used as an alternative to tracking data. "
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),
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),
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io.Boolean.Input(
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"run_hand_refinement", default=True,
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tooltip="Improves hand pose at the cost of extra inference time and memory use"),
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io.Float.Input(
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"fov_degrees",
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default=0.0, min=0.0, max=170.0, step=0.5,
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"fov",
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tooltip=(
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"Vertical FOV in degrees. Affects predicted depth (cam_t.z) and "
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"absolute scale. 0 = fall back to ~53° (16:9). Feed MoGeGeometryToFOV "
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"here to derive it from a MoGe estimate."
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"Vertical FoV in degrees. Affects predicted depth and absolute scale. 0 = fall back to ~53° (16:9)."
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),
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),
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io.Int.Input(
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"chunk_size", #TODO: automate?
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default=64, min=1, max=512, step=1, advanced=True,
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tooltip=(
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"Max person-crops per forward. Higher = throughput + VRAM; "
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"per-chunk frame count is chunk_size / persons_per_frame."
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"Max frames to process as a batch. Larger values utilize more VRAM for faster inference."
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),
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),
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],
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@ -167,7 +162,7 @@ class SAM3DBody_Predict(io.ComfyNode):
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)
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@classmethod
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def execute(cls, sam3d_body_model, image, sam3_track_data=None, bboxes=None, run_hand_refinement=True, fov_degrees=0.0, chunk_size=64) -> io.NodeOutput:
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def execute(cls, sam3d_body_model, image, sam3_track_data=None, bboxes=None, run_hand_refinement=True, fov=0.0, chunk_size=64) -> io.NodeOutput:
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comfy.model_management.load_model_gpu(sam3d_body_model)
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inner: SAM3DBody = sam3d_body_model.model
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@ -187,8 +182,8 @@ class SAM3DBody_Predict(io.ComfyNode):
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per_frame_bboxes = [full_frame_bbox.clone() for _ in range(B)]
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per_frame_masks = None
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inference_type = "full" if run_hand_refinement else "body"
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# fov_degrees > 0 sets intrinsics; else None falls back to prepare_batch's diagonal default.
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cam_int = cam_int_from_fov(int(H), int(W), float(fov_degrees))
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# fov > 0 sets intrinsics; else None falls back to prepare_batch's diagonal default.
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cam_int = cam_int_from_fov(int(H), int(W), float(fov))
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frames_rgb: List[Optional[torch.Tensor]] = []
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for f in range(B):
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@ -259,8 +254,8 @@ class SAM3DBody_FaceExpression(io.ComfyNode):
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display_name="Face Expression to SAM3D Body", #TODO: better name?
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category="image/detection/sam3dbody/",
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inputs=[
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MHRPoseData.Input("mhr_pose_data"),
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SAM3DBodyModel.Input("sam3d_body_model"),
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MHRPoseData.Input("mhr_pose_data"),
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io.Image.Input("image"),
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io.Float.Input(
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"strength", default=1.0, min=0.0, max=4.0, step=0.05,
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@ -268,17 +263,17 @@ class SAM3DBody_FaceExpression(io.ComfyNode):
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),
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io.Float.Input(
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"mouth_strength", default=1.0, min=0.0, max=4.0, step=0.05,
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tooltip="Multiplier on mouth/jaw shapes. MP's jawOpen saturates near 1.0.",
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tooltip="Multiplier on mouth/jaw shapes. MediaPipe's jawOpen saturates near 1.0.",
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advanced=True,
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),
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io.Float.Input(
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"eye_strength", default=2.0, min=0.0, max=4.0, step=0.05,
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tooltip="Multiplier on eye shapes. MP rarely exceeds 0.5; 2-3x often needed.",
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tooltip="Multiplier on eye shapes. MediaPipe rarely exceeds 0.5; 2-3x often needed.",
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advanced=True,
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),
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io.Float.Input(
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"brow_strength", default=2.0, min=0.0, max=4.0, step=0.05,
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tooltip="Multiplier on brow/cheek/sneer shapes. MP outputs ~0.1-0.3; 2-3x.",
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tooltip="Multiplier on brow/cheek/sneer shapes. MediaPipe outputs ~0.1-0.3; 2-3x.",
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advanced=True,
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),
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io.Float.Input(
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@ -451,23 +446,23 @@ class SAM3DBody_Smooth(io.ComfyNode):
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def define_schema(cls):
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return io.Schema(
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node_id="SAM3DBody_Smooth",
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description="Reduce frame-to-frame jitter via vertex-space temporal averaging",
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display_name="Smooth SAM3D Body Pose Frames",
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description="Reduce frame-to-frame jitter via temporal smoothing.",
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display_name="Smooth SAM3D Body Pose Data",
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category="image/detection/sam3dbody/",
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inputs=[
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MHRPoseData.Input("mhr_pose_data"),
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io.Float.Input(
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"strength",
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default=1.0, min=0.0, max=1.0, step=0.05,
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tooltip="Blend raw (0) → smoothed (1).",
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tooltip="Smoothing strength. 0 = raw, 1 = smoothed.",
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),
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io.Combo.Input(
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"method",
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options=["gaussian", "savgol"],
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default="gaussian", advanced=True,
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tooltip=(
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"'gaussian': symmetric weighted average, best general-purpose smoother. "
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"'savgol': sliding polynomial fit, preserves sharp peaks."
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"gaussian: symmetric weighted average, best general-purpose smoother./n"
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"savgol: sliding polynomial fit, preserves sharp peaks."
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),
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),
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io.Int.Input(
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@ -477,11 +472,11 @@ class SAM3DBody_Smooth(io.ComfyNode):
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),
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io.Float.Input(
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"rotation_threshold_deg",
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default=15.0, min=0.0, max=45.0, step=1.0, advanced=True,
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default=30.0, min=0.0, max=90.0, step=1.0, advanced=True,
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tooltip=(
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"Disables smoothing for this root-rotation rate (deg/frame) to preserve fast spins. "
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"15° suits most content, low values trigger on ordinary jitter and "
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"silently sabotage smoothing. 0 = disable."
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"Disables smoothing for this root rotation rate (degree/frame) to preserve fast spins. "
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"30° suits most content, low values might disable smoothing on ordinary jitter and "
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"silently impacts quality. 0 = disable."
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),
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),
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],
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@ -870,11 +865,9 @@ class SAM3DBody_Render(io.ComfyNode):
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),
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),
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io.Float.Input(
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"camera_fov", default=0.0, min=0.0, max=170.0, step=0.5, advanced=True,
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"fov", default=0.0, min=0.0, max=170.0, step=0.5, advanced=True,
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tooltip=(
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"Vertical FOV for the camera_info override. 0 = keep the SAM3D "
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"predicted camera's FOV (only the viewpoint changes). Any non-zero "
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"value overrides the lens. Ignored when camera_info is unwired."
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"Override the vertical FoV of the camera_info. Ignored when camera_info is empty. 0 = keep the FoV of the camera_info."
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),
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),
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io.DynamicCombo.Input(
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@ -900,7 +893,7 @@ class SAM3DBody_Render(io.ComfyNode):
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@classmethod
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def execute(cls, mhr_pose_data, background=None, width=0, height=0, camera_info=None, camera_fov=0.0, render_style=None) -> io.NodeOutput:
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def execute(cls, mhr_pose_data, background=None, width=0, height=0, camera_info=None, fov=0.0, render_style=None) -> io.NodeOutput:
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render_style = render_style or {"render_style": "mesh"}
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mode_key = render_style.get("render_style", "mesh")
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@ -919,7 +912,7 @@ class SAM3DBody_Render(io.ComfyNode):
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px_scale = min(new_W / native_W, new_H / native_H)
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if camera_info is not None:
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mhr_pose_data = apply_camera_override(mhr_pose_data, camera_info, H, W, fov_deg=float(camera_fov))
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mhr_pose_data = apply_camera_override(mhr_pose_data, camera_info, H, W, fov_deg=float(fov))
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B = len(mhr_pose_data["frames"])
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if B == 0:
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