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getmatlab.py
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getmatlab.py
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import os
import glob
import numpy as np
import pyvista as pv
import nibabel as nib
from scipy.io import savemat
import mne
import cv2
def compute_and_save_fiducial_points(niiFiles, subject, subjects_dir):
# 读取 NIfTI 文件
nifti_file = glob.glob(os.path.join(niiFiles, '*.gz')) + glob.glob(os.path.join(niiFiles, '*.nii')) # 替换为你的 NIfTI 文件路径
if not nifti_file:
print("未找到.nii/nii.gz文件")
return
nifti_file = nifti_file[0]
# 读取 .obj 或 .stl 文件
obj_files = glob.glob(os.path.join(subjects_dir, subject, '*.obj'))
if not obj_files:
print("未找到.obj文件")
return
mesh = pv.read(obj_files[0]) # 或者使用 'path_to_your_file.stl'
# 提取点云数据
points = mesh.points
# 找到与X轴的交点 (Y=0, Z=0)
intersection_points_x = points[(abs(points[:, 1]) <= 1) & (abs(points[:, 2]) <= 1)]
# 找到与Y轴的交点 (X=0, Z=0)
intersection_points_y = points[(abs(points[:, 0]) <= 1) & (abs(points[:, 2]) <= 1)]
# 找到与Z轴的交点 (X=0, Y=0)
intersection_points_z = points[(abs(points[:, 0]) <= 1) & (abs(points[:, 1]) <= 1)]
def add_intersection_points(intersection_points, idx=0):
if intersection_points.size != 0:
# 找到最外侧的点 (坐标最大和最小的点)
min_point = intersection_points[np.argmin(intersection_points[:, idx])]
max_point = intersection_points[np.argmax(intersection_points[:, idx])]
print(f"与轴的交点的最小坐标的点:", min_point)
print(f"与轴的交点的最大坐标的点:", max_point)
# 返回最外侧的点
return min_point, max_point
else:
print("没有找到与轴的交点")
return None, None
# 可视化X轴交点
min_x_point, max_x_point = add_intersection_points(intersection_points_x, idx=0)
# 可视化Y轴交点
min_y_point, max_y_point = add_intersection_points(intersection_points_y, idx=1)
# 可视化Z轴交点
min_z_point, max_z_point = add_intersection_points(intersection_points_z, idx=2)
print(intersection_points_z)
# 读取NIfTI文件中的仿射矩阵
img = nib.load(nifti_file)
vox2ras = img.affine
# 定义转换矩阵
transform_matrix = np.linalg.pinv(np.array([[-1,0,0,128],[0,0,1,-128],[0,-1,0,128],[0,0,0,1]]))
# transform_matrix = np.linalg.pinv(vox2ras)
# 标准转个体
Z_MNI = transform_matrix @ np.concatenate([np.array(max_z_point),np.ones(1)]).T
L_MNI = transform_matrix @ np.concatenate([np.array(min_x_point),np.ones(1)]).T
R_MNI = transform_matrix @ np.concatenate([np.array(max_x_point),np.ones(1)]).T
N_MNI = transform_matrix @ np.concatenate([np.array(max_y_point),np.ones(1)]).T
Z_MNI = Z_MNI[0:3]
L_MNI = L_MNI[0:3]
R_MNI = R_MNI[0:3]
N_MNI = N_MNI[0:3]
# 保存为.mat文件
mni_coordinates = np.array([Z_MNI, L_MNI, R_MNI, N_MNI])
savemat(os.path.join(subjects_dir, subject, 'fiducial.mat'), {'fiducial_point': mni_coordinates})
# 设置源空间并保存
src = mne.setup_source_space(subject, subjects_dir=subjects_dir, spacing='oct6', add_dist=False)
src_file = os.path.join(subjects_dir, subject, 'src.fif')
mne.write_source_spaces(src_file, src, overwrite=True)
# 保存曲率
lcurv_file = os.path.join(subjects_dir, subject, 'surf', 'lh.curv')
lcurv_data = nib.freesurfer.io.read_morph_data(lcurv_file)
rcurv_file = os.path.join(subjects_dir, subject, 'surf', 'rh.curv')
rcurv_data = nib.freesurfer.io.read_morph_data(rcurv_file)
curv = np.concatenate([lcurv_data[src[0]['inuse']==1],rcurv_data[src[1]['inuse']==1]]).T
curvcurv = curv.copy()
curvcurv[curv<0] = -1
curvcurv[curv>0] = 1
savemat(os.path.join(subjects_dir, subject, 'curv.mat'), {'curvature': curvcurv})
# # 可视化原始点云数据和交点
# p = pv.Plotter(off_screen=True)
# p.add_points(points, color='black', point_size=1)
# p.show_axes()
# p.add_mesh(mesh, color='white')
# if min_x_point is not None and max_x_point is not None:
# p.add_mesh(pv.Sphere(radius=5, center=min_x_point), color='blue')
# p.add_mesh(pv.Sphere(radius=5, center=max_x_point), color='blue')
# if min_y_point is not None and max_y_point is not None:
# p.add_mesh(pv.Sphere(radius=5, center=min_y_point), color='green')
# p.add_mesh(pv.Sphere(radius=5, center=max_y_point), color='green')
# if min_z_point is not None and max_z_point is not None:
# p.add_mesh(pv.Sphere(radius=5, center=min_z_point), color='red')
# p.add_mesh(pv.Sphere(radius=5, center=max_z_point), color='red')
# outputDir='output_images_camera_path'
# capture_camera_path_images(p, outputDir)
# images_to_avi(outputDir, os.path.join(subjects_dir, subject, 'res.avi'))
def images_to_avi(folder_path, output_path, fps=30):
"""
将指定文件夹中的图片按顺序合成一个AVI格式的视频。
参数：
folder_path (str): 图片文件夹的路径。
output_path (str): 输出视频的保存路径和名称。
fps (int): 每秒显示的图片数（帧率）。默认为30。
返回值：
无
"""
# 获取文件夹中的所有图片文件
images = [img for img in os.listdir(folder_path) if img.endswith('.jpg') or img.endswith('.png')]
# 确保图片按顺序排列
images.sort()
# 检查是否有图片
if not images:
raise ValueError("文件夹中没有找到图片")
# 读取第一张图片以获取视频帧的尺寸
first_image = cv2.imread(os.path.join(folder_path, images[0]))
height, width, layers = first_image.shape
# 定义视频编码器
fourcc = cv2.VideoWriter_fourcc(*'DIVX')
video = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
# 将所有图片写入视频
for image in images:
img = cv2.imread(os.path.join(folder_path, image))
video.write(img)
# 释放资源
video.release()
cv2.destroyAllWindows()
def capture_camera_path_images(plotter, output_dir='output_images_camera_path'):
"""
Capture images along a camera path and save them to the specified directory.
Parameters:
- plotter: The PyVista plotter object used for rendering.
- output_dir: Directory to save the images. Defaults to 'output_images_camera_path'.
"""
# 创建保存图像的目录
os.makedirs(output_dir, exist_ok=True)
# 相机视角设置
elevation_angles_up = np.linspace(-60, 30, num=90) # 从-30度到30度的俯仰角
elevation_angles_down = np.linspace(30, 0, num=50) # 从30度回到0度的俯仰角
azimuth_angles = np.linspace(0, 360, num=360) # 从0到360度的方位角
frame_counter = 0
# 俯仰角从-30度到30度
for elevation in elevation_angles_up:
plotter.camera.elevation = elevation
plotter.render()
image_filename = os.path.join(output_dir, f'image_{frame_counter:04d}.png')
plotter.screenshot(image_filename)
frame_counter += 1
# 俯仰角从30度回到0度
for elevation in elevation_angles_down:
plotter.camera.elevation = elevation
plotter.render()
image_filename = os.path.join(output_dir, f'image_{frame_counter:04d}.png')
plotter.screenshot(image_filename)
frame_counter += 1
# 绕轴旋转360度
for azimuth in azimuth_angles:
plotter.camera.azimuth = azimuth
plotter.render()
image_filename = os.path.join(output_dir, f'image_{frame_counter:04d}.png')
plotter.screenshot(image_filename)
frame_counter += 1
if __name__ == '__main__':
# 使用你的文件路径替换 'F:\\程序\\MEG_FT'
compute_and_save_fiducial_points('dataInput', 'fastSurfer_web_2024-04-11-10-18-32_GCqR9', 'freesurfer')
# dataInput 为nii的文件夹
# fastSurfer_web_2024-04-11-10-18-32_GCqR9 是freesurfer分割的subject
# freesurfer 是subject 的文件夹