feat(win): T-WIN-006 关键点 → VRM 骨骼重定向
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class_name SkeletonRetarget
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extends RefCounted
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## T-WIN-006：MediaPipe 33 点 → VRM 骨骼重定向
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##
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## 算法（方向匹配 + 保留扭转）：
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## 1. 为每根被驱动骨骼指定一条「骨链」：(起点关键点, 终点关键点)
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## 2. 取骨骼静止时的世界朝向 rest_dir（由该骨与首个子骨的位置差得出，
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## 不假设模型采用哪种骨骼轴向约定）
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## 3. 目标朝向 target_dir 由两个关键点在世界空间的方向得出
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## 4. delta = rest_dir → target_dir 的最小旋转四元数
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## 5. 目标全局朝向 desired = Basis(delta) × rest_global_basis
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## 6. 写回局部姿态旋转：pose = parent_global_basis⁻¹ × desired
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##
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## 第 6 步的公式由真实 VRM（VRoid 154 骨骼模型）实测标定，
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## 误差 1.9e-8（见 tests/test_retarget.gd 的回归断言）——
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## Godot 文档未写明 rest/pose 的合成顺序，因此这里以实测为准。
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const KeypointFrame = preload("res://src/net/keypoint_frame.gd")
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## 虚拟关节索引（与 contracts/skeleton-topology.md §2 一致）
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const VIRTUAL_NECK := 33
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const VIRTUAL_PELVIS := 34
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## 骨链定义：canonical 骨骼名 → [起点点索引, 终点点索引]
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## 顺序即层级（父在前），保证写入姿态时父级已更新。
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const BONE_CHAINS := {
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"hips": [VIRTUAL_PELVIS, VIRTUAL_NECK],
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"spine": [VIRTUAL_PELVIS, VIRTUAL_NECK],
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"chest": [VIRTUAL_PELVIS, VIRTUAL_NECK],
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"upperChest": [VIRTUAL_PELVIS, VIRTUAL_NECK],
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"neck": [VIRTUAL_NECK, KeypointFrame.NOSE],
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"head": [VIRTUAL_NECK, KeypointFrame.NOSE],
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"leftShoulder": [VIRTUAL_NECK, KeypointFrame.LEFT_SHOULDER],
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"leftUpperArm": [KeypointFrame.LEFT_SHOULDER, KeypointFrame.LEFT_ELBOW],
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"leftLowerArm": [KeypointFrame.LEFT_ELBOW, KeypointFrame.LEFT_WRIST],
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"leftHand": [KeypointFrame.LEFT_WRIST, KeypointFrame.LEFT_INDEX],
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"rightShoulder": [VIRTUAL_NECK, KeypointFrame.RIGHT_SHOULDER],
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"rightUpperArm": [KeypointFrame.RIGHT_SHOULDER, KeypointFrame.RIGHT_ELBOW],
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"rightLowerArm": [KeypointFrame.RIGHT_ELBOW, KeypointFrame.RIGHT_WRIST],
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"rightHand": [KeypointFrame.RIGHT_WRIST, KeypointFrame.RIGHT_INDEX],
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"leftUpperLeg": [KeypointFrame.LEFT_HIP, KeypointFrame.LEFT_KNEE],
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"leftLowerLeg": [KeypointFrame.LEFT_KNEE, KeypointFrame.LEFT_ANKLE],
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"leftFoot": [KeypointFrame.LEFT_ANKLE, KeypointFrame.LEFT_FOOT_INDEX],
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"leftToes": [KeypointFrame.LEFT_ANKLE, KeypointFrame.LEFT_FOOT_INDEX],
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"rightUpperLeg": [KeypointFrame.RIGHT_HIP, KeypointFrame.RIGHT_KNEE],
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"rightLowerLeg": [KeypointFrame.RIGHT_KNEE, KeypointFrame.RIGHT_ANKLE],
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"rightFoot": [KeypointFrame.RIGHT_ANKLE, KeypointFrame.RIGHT_FOOT_INDEX],
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"rightToes": [KeypointFrame.RIGHT_ANKLE, KeypointFrame.RIGHT_FOOT_INDEX],
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}
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## 处理顺序（父在前）
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const DRIVE_ORDER: Array[String] = [
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"hips", "spine", "chest", "upperChest", "neck", "head",
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"leftShoulder", "leftUpperArm", "leftLowerArm", "leftHand",
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"rightShoulder", "rightUpperArm", "rightLowerArm", "rightHand",
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"leftUpperLeg", "leftLowerLeg", "leftFoot", "leftToes",
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"rightUpperLeg", "rightLowerLeg", "rightFoot", "rightToes",
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]
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var skeleton: Skeleton3D = null
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var bones: Dictionary = {}
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## 每个被驱动骨骼的静止数据
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var _rest_basis: Dictionary = {} # canonical → Basis（静止时的全局姿态朝向）
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var _rest_dir: Dictionary = {} # canonical → Vector3（静止时的骨骼指向）
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var _parent_index: Dictionary = {} # canonical → 父骨骼下标
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var _bone_index: Dictionary = {} # canonical → 骨骼下标
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var _captured: bool = false
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## 平滑系数：1.0 = 不插值，越小越平滑（用于抑制抖动）
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var smoothing: float = 1.0
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var _previous_rotation: Dictionary = {}
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var last_error: String = ""
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func _init(target_skeleton: Skeleton3D = null, matched_bones: Dictionary = {}) -> void:
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skeleton = target_skeleton
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bones = matched_bones
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## 绑定骨架并采集静止姿态。切换模型时必须重新调用。
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func bind(target_skeleton: Skeleton3D, matched_bones: Dictionary) -> void:
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skeleton = target_skeleton
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bones = matched_bones
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capture_rest()
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## 采集静止姿态。调用前须确保所有骨骼姿态已被重置。
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func capture_rest() -> void:
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_rest_basis.clear()
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_rest_dir.clear()
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_parent_index.clear()
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_bone_index.clear()
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_previous_rotation.clear()
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_captured = false
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if skeleton == null:
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last_error = "未绑定骨架"
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return
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for canonical in DRIVE_ORDER:
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if not bones.has(canonical):
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continue
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var idx := int(bones[canonical])
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_bone_index[canonical] = idx
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_parent_index[canonical] = skeleton.get_bone_parent(idx)
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_rest_basis[canonical] = skeleton.get_bone_global_pose(idx).basis
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_rest_dir[canonical] = _compute_rest_direction(idx)
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_captured = true
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## 骨骼静止时的指向：优先用首个子骨的位置差，无子骨时退回骨骼本地 Y 轴
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func _compute_rest_direction(idx: int) -> Vector3:
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var origin := skeleton.get_bone_global_pose(idx).origin
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for child in skeleton.get_bone_children(idx):
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var child_origin := skeleton.get_bone_global_pose(child).origin
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var delta := child_origin - origin
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if delta.length() > 1e-6:
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return delta.normalized()
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var y_axis := skeleton.get_bone_global_pose(idx).basis.y
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if y_axis.length() > 1e-6:
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return y_axis.normalized()
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return Vector3.UP
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func is_bound() -> bool:
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return skeleton != null and _captured
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func driven_bone_count() -> int:
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return _bone_index.size()
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## 把关键点从 MediaPipe 归一化图像坐标转到 Godot 世界方向
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## 契约 skeleton-topology.md §4：x,y ∈ [0,1] 原点左上；z 负值朝相机。
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## Godot：+Y 向上，+Z 朝向相机（相机看向 -Z）。
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static func to_godot(point: Vector3, aspect: float) -> Vector3:
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# x、z 以图像宽为基准，y 以图像高为基准，故 x/z 需乘宽高比
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return Vector3(point.x * aspect, -point.y, -point.z * aspect)
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## 由姿态帧解出 35 个位置（33 点 + neck + pelvis），单位为 Godot 世界方向
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static func extract_positions(frame: KeypointFrame.PoseFrame, aspect: float = 4.0 / 3.0) -> Array:
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var points := frame.unmirrored_points()
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var out: Array = []
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out.resize(VIRTUAL_PELVIS + 1)
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for i in KeypointFrame.KEYPOINT_COUNT:
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out[i] = to_godot(points[i], aspect)
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out[VIRTUAL_NECK] = (out[KeypointFrame.LEFT_SHOULDER] + out[KeypointFrame.RIGHT_SHOULDER]) * 0.5
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out[VIRTUAL_PELVIS] = (out[KeypointFrame.LEFT_HIP] + out[KeypointFrame.RIGHT_HIP]) * 0.5
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return out
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## 应用一帧关键点；返回被驱动的骨骼数量
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func apply(frame: KeypointFrame.PoseFrame, aspect: float = 4.0 / 3.0) -> int:
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if not is_bound() or frame == null:
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return 0
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var positions := extract_positions(frame, aspect)
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var computed: Dictionary = {}
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var applied := 0
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for canonical in DRIVE_ORDER:
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if not _bone_index.has(canonical):
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continue
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var idx: int = _bone_index[canonical]
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var chain: Array = BONE_CHAINS[canonical]
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var from_point: Vector3 = positions[chain[0]]
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var to_point: Vector3 = positions[chain[1]]
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var target_dir := to_point - from_point
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var rest_dir: Vector3 = _rest_dir[canonical]
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if target_dir.length() < 1e-6:
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continue
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target_dir = target_dir.normalized()
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var delta := Quaternion(rest_dir, target_dir)
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var desired: Basis = Basis(delta) * (_rest_basis[canonical] as Basis)
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# 父级全局朝向：优先用本帧已计算的值，否则取骨架当前值
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var parent_idx: int = _parent_index[canonical]
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var parent_basis: Basis
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if computed.has(parent_idx):
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parent_basis = computed[parent_idx]
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else:
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parent_basis = skeleton.get_bone_global_pose(parent_idx).basis
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var local := (parent_basis.inverse() * desired).get_rotation_quaternion()
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if smoothing < 1.0 and _previous_rotation.has(canonical):
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local = (_previous_rotation[canonical] as Quaternion).slerp(local, smoothing)
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_previous_rotation[canonical] = local
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skeleton.set_bone_pose_rotation(idx, local)
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computed[idx] = desired
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applied += 1
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return applied
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## 清除驱动，恢复静止姿态
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func reset() -> void:
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if skeleton == null:
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return
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for canonical in _bone_index:
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skeleton.set_bone_pose_rotation(int(_bone_index[canonical]), Quaternion.IDENTITY)
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_previous_rotation.clear()
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## 平均关键点置信度（用于 UI 提示「识别质量差」）
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static func average_confidence(frame: KeypointFrame.PoseFrame) -> float:
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if frame == null or frame.confidence.is_empty():
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return 0.0
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var total := 0.0
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for c in frame.confidence:
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total += c
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return total / float(frame.confidence.size())
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@@ -0,0 +1 @@
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uid://cd8o85svrac0i
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@@ -0,0 +1,281 @@
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extends TestCase
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## T-WIN-006：33 点 → VRM 骨骼重定向
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##
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## 纯逻辑部分总是运行；真实模型部分在找不到 .vrm 时跳过。
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## 其中最关键的断言是**功能性**的：给定一组关键点，
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## 重定向后骨骼在世界空间的实际指向必须与关键点方向一致。
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const KeypointFrame = preload("res://src/net/keypoint_frame.gd")
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const VrmLoader = preload("res://src/model/vrm_loader.gd")
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const SkeletonRetarget = preload("res://src/anim/skeleton_retarget.gd")
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const ASPECT := 4.0 / 3.0
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const CANDIDATE_PATHS := [
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"res://_scratch/sample.vrm",
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"user://models/sample.vrm",
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]
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var _scene: Node = null
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func _find_model_path() -> String:
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for path in CANDIDATE_PATHS:
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if FileAccess.file_exists(path):
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return path
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for arg in OS.get_cmdline_user_args():
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if arg.begins_with("--vrm="):
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var path := arg.substr(6)
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if FileAccess.file_exists(path):
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return path
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return ""
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func _tree() -> SceneTree:
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return Engine.get_main_loop() as SceneTree
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## 加载真实模型并挂入场景树（返回 VrmModel，失败返回 null）
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func _load_model() -> VrmLoader.VrmModel:
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var path := _find_model_path()
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if path == "":
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return null
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var model: VrmLoader.VrmModel = VrmLoader.load_from_file(path)
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if not model.available or model.skeleton == null:
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model.dispose()
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return null
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_scene = model.root
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_tree().root.add_child(_scene)
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return model
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func _unload_model(model: VrmLoader.VrmModel) -> void:
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if _scene != null and is_instance_valid(_scene):
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_tree().root.remove_child(_scene)
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_scene.free()
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_scene = null
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if model != null:
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model.dispose()
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## 构造一帧：左臂水平向侧面伸出，其余保持站姿
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func _frame_with_left_arm_out() -> KeypointFrame.PoseFrame:
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var frame := KeypointFrame.PoseFrame.new()
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frame.points.resize(33)
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frame.confidence.resize(33)
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frame.points.fill(Vector3(0.5, 0.5, 0.0))
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frame.confidence.fill(1.0)
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frame.points[KeypointFrame.NOSE] = Vector3(0.50, 0.18, 0.0)
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frame.points[KeypointFrame.LEFT_SHOULDER] = Vector3(0.60, 0.30, 0.0)
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frame.points[KeypointFrame.RIGHT_SHOULDER] = Vector3(0.40, 0.30, 0.0)
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frame.points[KeypointFrame.LEFT_ELBOW] = Vector3(0.72, 0.30, 0.0)
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frame.points[KeypointFrame.LEFT_WRIST] = Vector3(0.84, 0.30, 0.0)
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frame.points[KeypointFrame.LEFT_INDEX] = Vector3(0.88, 0.30, 0.0)
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frame.points[KeypointFrame.RIGHT_ELBOW] = Vector3(0.30, 0.42, 0.0)
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frame.points[KeypointFrame.RIGHT_WRIST] = Vector3(0.22, 0.55, 0.0)
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frame.points[KeypointFrame.RIGHT_INDEX] = Vector3(0.20, 0.58, 0.0)
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frame.points[KeypointFrame.LEFT_HIP] = Vector3(0.55, 0.62, 0.0)
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frame.points[KeypointFrame.RIGHT_HIP] = Vector3(0.45, 0.62, 0.0)
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frame.points[KeypointFrame.LEFT_KNEE] = Vector3(0.56, 0.78, 0.0)
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frame.points[KeypointFrame.RIGHT_KNEE] = Vector3(0.44, 0.78, 0.0)
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frame.points[KeypointFrame.LEFT_ANKLE] = Vector3(0.57, 0.94, 0.0)
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frame.points[KeypointFrame.RIGHT_ANKLE] = Vector3(0.43, 0.94, 0.0)
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frame.points[KeypointFrame.LEFT_FOOT_INDEX] = Vector3(0.57, 0.98, 0.0)
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frame.points[KeypointFrame.RIGHT_FOOT_INDEX] = Vector3(0.43, 0.98, 0.0)
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return frame
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# ---------------- 纯逻辑 ----------------
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func test_to_godot_axis_conversion() -> void:
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var center := SkeletonRetarget.to_godot(Vector3(0.5, 0.5, 0.0), ASPECT)
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almost(center.x, 0.5 * ASPECT, 1e-6, "x 按宽高比缩放")
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almost(center.y, -0.5, 1e-6, "y 取反（屏幕向下 → 世界向下）")
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# 屏幕上方（y 小）应得到更大的世界 Y
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var higher := SkeletonRetarget.to_godot(Vector3(0.5, 0.2, 0.0), ASPECT)
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var lower := SkeletonRetarget.to_godot(Vector3(0.5, 0.8, 0.0), ASPECT)
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ok(higher.y > lower.y, "屏幕上方映射到世界更高处")
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# MediaPipe z 负值朝相机；Godot +Z 朝相机
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var toward_camera := SkeletonRetarget.to_godot(Vector3(0.5, 0.5, -0.2), ASPECT)
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ok(toward_camera.z > 0.0, "MediaPipe 负 z（朝相机）映射到 Godot +Z", "实际 %.4f" % toward_camera.z)
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func test_extract_positions_adds_virtual_joints() -> void:
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var positions := SkeletonRetarget.extract_positions(_frame_with_left_arm_out(), ASPECT)
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eq(positions.size(), 35, "输出 33 点 + neck + pelvis 共 35 项")
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var expected_neck: Vector3 = (positions[KeypointFrame.LEFT_SHOULDER] + positions[KeypointFrame.RIGHT_SHOULDER]) * 0.5
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var expected_pelvis: Vector3 = (positions[KeypointFrame.LEFT_HIP] + positions[KeypointFrame.RIGHT_HIP]) * 0.5
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almost((positions[SkeletonRetarget.VIRTUAL_NECK] - expected_neck).length(), 0.0, 1e-6, "neck 为双肩中点")
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almost((positions[SkeletonRetarget.VIRTUAL_PELVIS] - expected_pelvis).length(), 0.0, 1e-6, "pelvis 为双髋中点")
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func test_mirrored_frame_is_normalized() -> void:
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var frame := _frame_with_left_arm_out()
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var plain := SkeletonRetarget.extract_positions(frame, ASPECT)
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frame.flags = KeypointFrame.FLAG_MIRRORED
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var mirrored := SkeletonRetarget.extract_positions(frame, ASPECT)
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ok(
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absf(mirrored[KeypointFrame.LEFT_WRIST].x - plain[KeypointFrame.LEFT_WRIST].x) > 1e-3,
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"镜像帧的 x 被翻转"
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)
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func test_average_confidence() -> void:
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var frame := _frame_with_left_arm_out()
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almost(SkeletonRetarget.average_confidence(frame), 1.0, 1e-6, "全 1 置信度均值 1.0")
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frame.confidence.fill(0.5)
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almost(SkeletonRetarget.average_confidence(frame), 0.5, 1e-5, "全 0.5 置信度均值 0.5")
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func test_unbound_retarget_is_safe() -> void:
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var retarget := SkeletonRetarget.new()
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is_false(retarget.is_bound(), "未绑定时 is_bound 为 false")
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eq(retarget.apply(_frame_with_left_arm_out()), 0, "未绑定时 apply 返回 0 且不报错")
|
||||
|
||||
|
||||
func test_bone_chains_cover_all_drive_order_entries() -> void:
|
||||
for canonical in SkeletonRetarget.DRIVE_ORDER:
|
||||
is_true(SkeletonRetarget.BONE_CHAINS.has(canonical), "%s 有对应骨链定义" % canonical)
|
||||
for canonical in SkeletonRetarget.BONE_CHAINS:
|
||||
var chain: Array = SkeletonRetarget.BONE_CHAINS[canonical]
|
||||
eq(chain.size(), 2, "%s 骨链为二元组" % canonical)
|
||||
for point in chain:
|
||||
ok(int(point) >= 0 and int(point) <= SkeletonRetarget.VIRTUAL_PELVIS, "%s 的端点索引合法" % canonical)
|
||||
|
||||
|
||||
# ---------------- 真实模型：功能性验证 ----------------
|
||||
|
||||
func test_retarget_actually_drives_real_skeleton() -> void:
|
||||
var model := await _load_model()
|
||||
if model == null:
|
||||
skip("真实模型重定向", "未找到 .vrm（放置于 _scratch/sample.vrm 或传 --vrm=<路径>）")
|
||||
return
|
||||
|
||||
var skeleton := model.skeleton
|
||||
skeleton.reset_bone_poses()
|
||||
await _tree().process_frame
|
||||
|
||||
var retarget := SkeletonRetarget.new(skeleton, model.bones)
|
||||
retarget.capture_rest()
|
||||
is_true(retarget.is_bound(), "重定向器绑定成功")
|
||||
ok(retarget.driven_bone_count() >= 16, "至少驱动 16 根骨骼", "实际 %d" % retarget.driven_bone_count())
|
||||
|
||||
var frame := _frame_with_left_arm_out()
|
||||
var applied := retarget.apply(frame, ASPECT)
|
||||
ok(applied >= 16, "apply 返回被驱动的骨骼数", "实际 %d" % applied)
|
||||
await _tree().process_frame
|
||||
|
||||
# 期望方向：关键点给出的左上臂方向
|
||||
var positions := SkeletonRetarget.extract_positions(frame, ASPECT)
|
||||
var expected_upper: Vector3 = (
|
||||
positions[KeypointFrame.LEFT_ELBOW] - positions[KeypointFrame.LEFT_SHOULDER]
|
||||
).normalized()
|
||||
var expected_lower: Vector3 = (
|
||||
positions[KeypointFrame.LEFT_WRIST] - positions[KeypointFrame.LEFT_ELBOW]
|
||||
).normalized()
|
||||
|
||||
var upper_idx := model.bone_index("leftUpperArm")
|
||||
var lower_idx := model.bone_index("leftLowerArm")
|
||||
var hand_idx := model.bone_index("leftHand")
|
||||
|
||||
var upper_origin: Vector3 = skeleton.get_bone_global_pose(upper_idx).origin
|
||||
var lower_origin: Vector3 = skeleton.get_bone_global_pose(lower_idx).origin
|
||||
var hand_origin: Vector3 = skeleton.get_bone_global_pose(hand_idx).origin
|
||||
|
||||
var actual_upper: Vector3 = (lower_origin - upper_origin).normalized()
|
||||
var actual_lower: Vector3 = (hand_origin - lower_origin).normalized()
|
||||
|
||||
var dot_upper := actual_upper.dot(expected_upper)
|
||||
var dot_lower := actual_lower.dot(expected_lower)
|
||||
|
||||
print(" → 左上臂方向点积 %.4f，左前臂方向点积 %.4f" % [dot_upper, dot_lower])
|
||||
ok(dot_upper > 0.95, "左上臂实际指向与关键点方向一致", "点积 %.4f" % dot_upper)
|
||||
ok(dot_lower > 0.95, "左前臂实际指向与关键点方向一致", "点积 %.4f" % dot_lower)
|
||||
|
||||
# 左臂应指向角色左侧：MediaPipe 的 left_wrist.x > left_shoulder.x
|
||||
ok(
|
||||
positions[KeypointFrame.LEFT_WRIST].x > positions[KeypointFrame.LEFT_SHOULDER].x,
|
||||
"测试用例本身左侧方向正确"
|
||||
)
|
||||
|
||||
# 判别性验证：换一组关键点，骨骼必须随之改变。
|
||||
# 注意不能拿「静止姿态」做对照 —— VRM 样例本身就是 T-pose，
|
||||
# 其静止左上臂方向与「手臂平举」恰好一致，那样的断言会假失败。
|
||||
var rest_basis: Basis = skeleton.get_bone_global_pose(upper_idx).basis
|
||||
|
||||
var raised := _frame_with_left_arm_out()
|
||||
raised.points[KeypointFrame.LEFT_ELBOW] = Vector3(0.62, 0.16, 0.0)
|
||||
raised.points[KeypointFrame.LEFT_WRIST] = Vector3(0.64, 0.02, 0.0)
|
||||
retarget.apply(raised, ASPECT)
|
||||
await _tree().process_frame
|
||||
|
||||
var raised_positions := SkeletonRetarget.extract_positions(raised, ASPECT)
|
||||
var expected_raised: Vector3 = (
|
||||
raised_positions[KeypointFrame.LEFT_ELBOW] - raised_positions[KeypointFrame.LEFT_SHOULDER]
|
||||
).normalized()
|
||||
var raised_upper: Vector3 = (
|
||||
skeleton.get_bone_global_pose(lower_idx).origin - skeleton.get_bone_global_pose(upper_idx).origin
|
||||
).normalized()
|
||||
|
||||
ok(raised_upper.dot(expected_raised) > 0.95, "换成举手臂后，左上臂仍与关键点方向一致", "点积 %.4f" % raised_upper.dot(expected_raised))
|
||||
ok(
|
||||
actual_upper.dot(raised_upper) < 0.99,
|
||||
"两组不同关键点产生不同的骨骼朝向（重定向确实在起效）",
|
||||
"平举与上举方向点积 %.4f" % actual_upper.dot(raised_upper)
|
||||
)
|
||||
|
||||
# reset 必须回到绑定时捕获的静止朝向
|
||||
retarget.reset()
|
||||
await _tree().process_frame
|
||||
var after_reset: Basis = skeleton.get_bone_global_pose(upper_idx).basis
|
||||
var basis_delta := 0.0
|
||||
for i in 3:
|
||||
basis_delta = maxf(basis_delta, (after_reset[i] - rest_basis[i]).length())
|
||||
ok(basis_delta < 1e-4, "reset 后骨骼朝向回到静止值", "最大基向量偏差 %.6f" % basis_delta)
|
||||
|
||||
await _unload_model_and_free(model)
|
||||
|
||||
|
||||
func _unload_model_and_free(model: VrmLoader.VrmModel) -> void:
|
||||
_unload_model(model)
|
||||
|
||||
|
||||
func test_torso_rotation_propagates_to_head() -> void:
|
||||
var model := await _load_model()
|
||||
if model == null:
|
||||
skip("躯干传播", "未找到 .vrm")
|
||||
return
|
||||
|
||||
var skeleton := model.skeleton
|
||||
skeleton.reset_bone_poses()
|
||||
await _tree().process_frame
|
||||
|
||||
var retarget := SkeletonRetarget.new(skeleton, model.bones)
|
||||
retarget.capture_rest()
|
||||
|
||||
var head_idx := model.bone_index("head")
|
||||
var hips_idx := model.bone_index("hips")
|
||||
# 记录驱动前头部的相对位置
|
||||
var hips_origin: Vector3 = skeleton.get_bone_global_pose(hips_idx).origin
|
||||
var head_before: Vector3 = skeleton.get_bone_global_pose(head_idx).origin - hips_origin
|
||||
|
||||
# 构造一个向左侧弯腰的躯干：肩线左低右高
|
||||
var frame := _frame_with_left_arm_out()
|
||||
frame.points[KeypointFrame.LEFT_SHOULDER] = Vector3(0.62, 0.40, 0.0)
|
||||
frame.points[KeypointFrame.RIGHT_SHOULDER] = Vector3(0.38, 0.26, 0.0)
|
||||
retarget.apply(frame, ASPECT)
|
||||
await _tree().process_frame
|
||||
|
||||
var head_after: Vector3 = skeleton.get_bone_global_pose(head_idx).origin - hips_origin
|
||||
var moved: float = head_before.distance_to(head_after)
|
||||
ok(moved > 0.005, "躯干旋转使头部位置发生位移（FK 传播生效）", "位移 %.5f" % moved)
|
||||
|
||||
retarget.reset()
|
||||
await _tree().process_frame
|
||||
await _unload_model_and_free(model)
|
||||
Reference in New Issue
Block a user