From c85b6b94f6579b56176407b8c95b2d8c9ca0acf8 Mon Sep 17 00:00:00 2001 From: Flash Date: Sun, 27 Jul 2025 19:18:17 +0800 Subject: [PATCH] h5ad generation --- embryo-backend/Data/CS11.h5ad | 4 +- embryo-backend/Data/CS12.h5ad | 2 +- embryo-backend/Data/glbTrans.py | 82 ++++++++++++++++----------------- 3 files changed, 44 insertions(+), 44 deletions(-) diff --git a/embryo-backend/Data/CS11.h5ad b/embryo-backend/Data/CS11.h5ad index b8cb597..50dc3d3 100644 --- a/embryo-backend/Data/CS11.h5ad +++ b/embryo-backend/Data/CS11.h5ad @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:7e1d1d9f21d310f47aed5762fa553025be93895a7c4e39c9c14dddeacfdd5a87 -size 122218584 +oid sha256:6353b3cee5103db171a71f73549ca6a24599d454f05ec57b4f6ac548a697734d +size 122226666 diff --git a/embryo-backend/Data/CS12.h5ad b/embryo-backend/Data/CS12.h5ad index b04e33b..a59f784 100644 --- a/embryo-backend/Data/CS12.h5ad +++ b/embryo-backend/Data/CS12.h5ad @@ -1,3 +1,3 @@ version https://git-lfs.github.com/spec/v1 -oid sha256:1925467fd995d5022e62bd4c37131aa037414e0b96f87451f331f20b964eb41e +oid sha256:193b724e6202db09c01728a76b920c48a55977a706b21f4dfeb43165374f2e2e size 122242830 diff --git a/embryo-backend/Data/glbTrans.py b/embryo-backend/Data/glbTrans.py index 07198ff..3323d16 100644 --- a/embryo-backend/Data/glbTrans.py +++ b/embryo-backend/Data/glbTrans.py @@ -3,7 +3,6 @@ import trimesh import pandas as pd import numpy as np import anndata as ad -from collections import defaultdict # ==== 参数 ==== script_dir = os.path.dirname(os.path.realpath(__file__)) @@ -30,32 +29,26 @@ true_markers = { # ==== 采样函数 ==== def sample_mesh(mesh, label, n_samples): - """采样点云 + 颜色 + 标签""" - if use_surface_sampling: - points, face_idx = trimesh.sample.sample_surface(mesh, n_samples) - if hasattr(mesh.visual, "vertex_colors") and len(mesh.visual.vertex_colors) == len(mesh.vertices): - face_colors = mesh.visual.vertex_colors[mesh.faces] - colors = face_colors.mean(axis=1)[face_idx, :3] - else: - mat_color = np.array([200, 200, 200]) - colors = np.tile(mat_color, (n_samples, 1)) + if len(mesh.vertices) == 0: + print(f"⚠️ {label} 无顶点，跳过") + return np.zeros((0,3)), np.zeros((0,3)), np.array([]) + + if mesh.faces is None or len(mesh.faces) == 0 or not use_surface_sampling: + idx = np.random.choice(len(mesh.vertices), min(n_samples, len(mesh.vertices)), replace=False) + points = mesh.vertices[idx] else: - verts = mesh.vertices - if len(verts) > n_samples: - idx = np.random.choice(len(verts), n_samples, replace=False) - verts = verts[idx] - else: - idx = np.arange(len(verts)) - if hasattr(mesh.visual, "vertex_colors") and len(mesh.visual.vertex_colors) == len(mesh.vertices): - colors = mesh.visual.vertex_colors[idx, :3] - else: - mat_color = np.array([200, 200, 200]) - colors = np.tile(mat_color, (len(verts), 1)) - points = verts + points, face_idx = trimesh.sample.sample_surface(mesh, n_samples) + + if hasattr(mesh.visual, "vertex_colors") and len(mesh.visual.vertex_colors) == len(mesh.vertices): + colors = mesh.visual.vertex_colors[:len(points), :3] + else: + mat_color = np.array([200,200,200]) + colors = np.tile(mat_color, (len(points),1)) + labels = np.array([label] * len(points)) return points, colors, labels -# ==== Step 1: 计算全局最大边长 ==== +# ==== Step 1: 计算全局边界 ==== all_bounds = [] for glb_name in glb_files: glb_path = os.path.join(script_dir, glb_name) @@ -74,7 +67,7 @@ global_max = np.max(all_bounds[:,1,:], axis=0) global_size = np.max(global_max - global_min) print(f"🌍 统一缩放基准: global_size={global_size}") -# ==== Step 2: 处理单个 GLB（应用全局变换） ==== +# ==== Step 2: 处理单个 GLB ==== def process_glb(glb_path, sample_name): scene = trimesh.load(glb_path) all_points, all_colors, all_labels = [], [], [] @@ -82,23 +75,32 @@ def process_glb(glb_path, sample_name): if isinstance(scene, trimesh.Scene): total_points = sum(len(g.vertices) for g in scene.geometry.values()) for name, geom in scene.geometry.items(): - ratio = len(geom.vertices) / total_points - n_samples = max(1, int(N_total * ratio)) + if len(geom.vertices) == 0: + print(f"⚠️ {sample_name}: 子网格 {name} 无顶点，跳过") + continue - # ✅ 保护性获取变换矩阵 + ratio = len(geom.vertices) / total_points if total_points > 0 else 0 + n_samples = max(100, int(N_total * ratio)) # ✅ 最少100点 + + # ✅ 自动检测 & 兼容修复 try: transform = scene.graph.get(name)[0] + verts_world = trimesh.transform_points(geom.vertices, transform) except Exception: - print(f"⚠️ {sample_name}: 子网格 {name} 没有变换路径，使用单位矩阵") - transform = np.eye(4) + # 判断顶点是否已经全局化 + local_bounds = geom.bounds + local_size = np.max(local_bounds[1] - local_bounds[0]) + if local_size > 0.5 * global_size: # 说明已在全局坐标 + print(f"ℹ️ {sample_name}: 子网格 {name} 似乎已是全局坐标 → 直接使用") + verts_world = geom.vertices.copy() + else: + print(f"⚠️ {sample_name}: 子网格 {name} 无变换路径且看似局部坐标 → 仍使用原始顶点（可能错位）") + verts_world = geom.vertices.copy() - # ✅ 应用全局变换 - verts_world = trimesh.transform_points(geom.vertices, transform) - - # ✅ 生成全局 mesh 进行采样 mesh_world = trimesh.Trimesh(vertices=verts_world, faces=geom.faces, process=False) p, c, l = sample_mesh(mesh_world, name, n_samples) - + if len(p) == 0: + continue all_points.append(p) all_colors.append(c) all_labels.append(l) @@ -108,15 +110,14 @@ def process_glb(glb_path, sample_name): all_colors.append(c) all_labels.append(l) + if len(all_points) == 0: + raise RuntimeError(f"❌ {sample_name}: 没有有效点被采样！") + points = np.vstack(all_points) colors = np.vstack(all_colors) labels = np.concatenate(all_labels) - if len(points) > N_total: - idx = np.random.choice(len(points), N_total, replace=False) - points, colors, labels = points[idx], colors[idx], labels[idx] - - # ✅ 一次性中心化 + 统一缩放 + # ✅ 中心化 + 统一缩放 center = points.mean(axis=0) points_centered = points - center points_scaled = points_centered / global_size @@ -127,10 +128,9 @@ def process_glb(glb_path, sample_name): csv_file = os.path.join(script_dir, f"{sample_name}_point_cloud_30000_centered_scaled.csv") df.to_csv(csv_file, index=False) - print(f"✅ 已导出 {csv_file} (修正组织错位, 中心化 & 统一比例)") + print(f"✅ 已导出 {csv_file} (自动检测 + 兼容修复)") return df - # ==== Step 3: 生成 h5ad ==== def create_h5ad(df, sample_name): points = df[['x','y','z']].to_numpy()