Datasets:

martelzhang
/

RoboMonster_assets

import trimesh
import json
import numpy as np

PI = np.pi

# 可以是标量（各向同性）或三元组（各向异性）
# 例如：1.0  或  [0.08, 0.4, 0.08]
MODEL_SCALE = 0.004

GRASP_OFFSET = [0., 0., 0.]   # 相对“顶部中心”的偏移
GRASP_ROT = [PI, 0.0, PI]             # 欧拉角 (rx, ry, rz), 弧度

def _to_scale_vec(scale):
    """将标量/数组统一成 3 维缩放向量 [sx, sy, sz]."""
    arr = np.asarray(scale, dtype=float)
    if arr.ndim == 0:
        return [float(arr)] * 3
    if arr.shape == (3,):
        return arr.tolist()
    raise ValueError(f"MODEL_SCALE 需为标量或长度为3的向量，收到形状: {arr.shape}")

def create_model_data(id="vase"):
    file_path = f"./{id}.glb"
    save_path = f"./model_data.json"

    # 1) 读模型并融合为单一 Trimesh
    with open(file_path, "rb") as f:
        loaded = trimesh.load(f, file_type="glb")
    mesh = loaded.to_mesh() if isinstance(loaded, trimesh.Scene) else loaded

    # 2) 应用缩放（标量或三元向量都可）
    scale_vec = _to_scale_vec(MODEL_SCALE)
    mesh.apply_scale(scale_vec)  # 支持 float 或 (3,) 向量

    # 3) OBB 信息
    obb = mesh.bounding_box_oriented
    center = obb.centroid
    ext = obb.extents
    diag = np.linalg.norm(ext)

    # 4) 计算“底部中心” -> 原点的平移
    rotation_matrix = obb.transform[:3, :3]
    bottom_center = center - rotation_matrix[:, 2] * (ext[2] / 2.0)
    mesh.apply_translation(-bottom_center)

    # 5) 更新 OBB
    obb = mesh.bounding_box_oriented
    center = obb.centroid
    ext = obb.extents
    rotation_matrix = obb.transform[:3, :3]

    # 6) 顶部中心（现在模型底部已对齐原点，Z 轴正向为“上”）
    top_center = center + rotation_matrix[:, 2] * (ext[2] / 2.0)

    # 7) 组合抓取位姿：先平移到顶部中心 -> 旋转 -> 偏移
    grasp_translation = trimesh.transformations.translation_matrix(top_center)
    grasp_rotation = trimesh.transformations.euler_matrix(*GRASP_ROT)
    grasp_offset = trimesh.transformations.translation_matrix(GRASP_OFFSET)
    grasp_transform = grasp_translation @ grasp_rotation @ grasp_offset

    # 8) 可视化
    scene = trimesh.Scene(mesh)
    grasp_sphere = trimesh.creation.icosphere(subdivisions=2, radius=diag * 0.05)
    grasp_sphere.apply_transform(grasp_transform)
    grasp_sphere.visual.vertex_colors = np.array([[1.0, 0.0, 0.0, 0.5]] * len(grasp_sphere.vertices))
    scene.add_geometry(grasp_sphere)

    grasp_axis = trimesh.creation.axis(origin_size=0.05, axis_length=diag * 0.2)
    grasp_axis.apply_transform(grasp_transform)
    scene.add_geometry(grasp_axis)

    # 9) 保存 JSON（注意 scale 为三元向量）
    data = {
        "center": center.tolist(),
        "extents": ext.tolist(),
        "scale": scale_vec,  
        "contact_points_pose": [grasp_transform.tolist()], 
        "transform_matrix": trimesh.transformations.identity_matrix().tolist(),
        "functional_matrix": [],
        "orientation_point": grasp_transform.tolist(),
        "contact_points_group": [],
        "contact_points_mask": [],
        "contact_points_discription": [],
        "target_point_discription": ["Grasp pose at the top edge center."],
        "functional_point_discription": [""],
        "orientation_point_discription": ["Grasp pose with adjustable offset and rotation."]
    }
    with open(save_path, "w", encoding="utf-8") as f:
        json.dump(data, f, indent=4, ensure_ascii=False, separators=(",", ": "))

    # 10) 显示场景
    scene.show()

if __name__ == "__main__":
    create_model_data("vase")

	import trimesh
	import json
	import numpy as np

	PI = np.pi

	# 可以是标量（各向同性）或三元组（各向异性）
	# 例如：1.0 或 [0.08, 0.4, 0.08]
	MODEL_SCALE = 0.004

	GRASP_OFFSET = [0., 0., 0.] # 相对“顶部中心”的偏移
	GRASP_ROT = [PI, 0.0, PI] # 欧拉角 (rx, ry, rz), 弧度

	def _to_scale_vec(scale):
	"""将标量/数组统一成 3 维缩放向量 [sx, sy, sz]."""
	arr = np.asarray(scale, dtype=float)
	if arr.ndim == 0:
	return [float(arr)] * 3
	if arr.shape == (3,):
	return arr.tolist()
	raise ValueError(f"MODEL_SCALE 需为标量或长度为3的向量，收到形状: {arr.shape}")

	def create_model_data(id="vase"):
	file_path = f"./{id}.glb"
	save_path = f"./model_data.json"

	# 1) 读模型并融合为单一 Trimesh
	with open(file_path, "rb") as f:
	loaded = trimesh.load(f, file_type="glb")
	mesh = loaded.to_mesh() if isinstance(loaded, trimesh.Scene) else loaded

	# 2) 应用缩放（标量或三元向量都可）
	scale_vec = _to_scale_vec(MODEL_SCALE)
	mesh.apply_scale(scale_vec) # 支持 float 或 (3,) 向量

	# 3) OBB 信息
	obb = mesh.bounding_box_oriented
	center = obb.centroid
	ext = obb.extents
	diag = np.linalg.norm(ext)

	# 4) 计算“底部中心” -> 原点的平移
	rotation_matrix = obb.transform[:3, :3]
	bottom_center = center - rotation_matrix[:, 2] * (ext[2] / 2.0)
	mesh.apply_translation(-bottom_center)

	# 5) 更新 OBB
	obb = mesh.bounding_box_oriented
	center = obb.centroid
	ext = obb.extents
	rotation_matrix = obb.transform[:3, :3]

	# 6) 顶部中心（现在模型底部已对齐原点，Z 轴正向为“上”）
	top_center = center + rotation_matrix[:, 2] * (ext[2] / 2.0)

	# 7) 组合抓取位姿：先平移到顶部中心 -> 旋转 -> 偏移
	grasp_translation = trimesh.transformations.translation_matrix(top_center)
	grasp_rotation = trimesh.transformations.euler_matrix(*GRASP_ROT)
	grasp_offset = trimesh.transformations.translation_matrix(GRASP_OFFSET)
	grasp_transform = grasp_translation @ grasp_rotation @ grasp_offset

	# 8) 可视化
	scene = trimesh.Scene(mesh)
	grasp_sphere = trimesh.creation.icosphere(subdivisions=2, radius=diag * 0.05)
	grasp_sphere.apply_transform(grasp_transform)
	grasp_sphere.visual.vertex_colors = np.array([[1.0, 0.0, 0.0, 0.5]] * len(grasp_sphere.vertices))
	scene.add_geometry(grasp_sphere)

	grasp_axis = trimesh.creation.axis(origin_size=0.05, axis_length=diag * 0.2)
	grasp_axis.apply_transform(grasp_transform)
	scene.add_geometry(grasp_axis)

	# 9) 保存 JSON（注意 scale 为三元向量）
	data = {
	"center": center.tolist(),
	"extents": ext.tolist(),
	"scale": scale_vec,
	"contact_points_pose": [grasp_transform.tolist()],
	"transform_matrix": trimesh.transformations.identity_matrix().tolist(),
	"functional_matrix": [],
	"orientation_point": grasp_transform.tolist(),
	"contact_points_group": [],
	"contact_points_mask": [],
	"contact_points_discription": [],
	"target_point_discription": ["Grasp pose at the top edge center."],
	"functional_point_discription": [""],
	"orientation_point_discription": ["Grasp pose with adjustable offset and rotation."]
	}
	with open(save_path, "w", encoding="utf-8") as f:
	json.dump(data, f, indent=4, ensure_ascii=False, separators=(",", ": "))

	# 10) 显示场景
	scene.show()

	if __name__ == "__main__":
	create_model_data("vase")