建模相关功能的修改

libs/common.py

@@ -138,6 +138,27 @@ def change_rcbox_deepth(pid,new_value):
         with open(rcbox_path, 'w') as f:
             f.write(new_content)
 
+def change_rcbox_center(pid,new_value):
+    rcbox_path = os.path.join(config.workdir, pid, f"{pid}.rcbox")
+    old_value_pattern = r'<center>(.*?)</center>'
+    #读取文件内容
+    with open(rcbox_path, 'r') as f:
+        content = f.read()
+    #使用正则表达式进行匹配
+    match = re.search(old_value_pattern,content)
+    if match:
+        old_value = match.group(1)
+        if old_value == "":
+            return 
+        #分割字符串
+        arrStr = old_value.split(" ")
+        #重新拼接字符串
+        strs = arrStr[0]+" "+arrStr[1]+" "+str(new_value)
+        new_content = re.sub(old_value_pattern,f'<center>{strs}</center>',content)
+        #重新写入进去
+        with open(rcbox_path, 'w') as f:
+            f.write(new_content)
+
 #修改rcproj文件,删除没有模型的component,保留最多model 的component
 def changeRcprojFile(pid):
     # 解析XML文件
@@ -224,6 +245,12 @@ def uploadControlPointsOss(pid):
     
 #截屏保存
 def saveScreenImg(pid):
+    #判断pid 是否是数字
+    if str(pid).isdigit() == False:
+        return 
+
+    if pid == 0 or pid == "":
+        return "pid 等于空"
     #获取当前的日志
     if not os.path.exists(os.path.join(config.workdir,"screen", time.strftime("%y%m%d",time.localtime()))):
         os.makedirs(os.path.join(config.workdir,"screen", time.strftime("%y%m%d",time.localtime())))

libs/computerRecboxCenterByPoint.py

@@ -0,0 +1,86 @@
+import open3d as o3d
+import numpy as np
+import matplotlib.pyplot as plt
+import sys
+import statistics
+import math
+import copy
+import os,time
+from scipy.stats import mode
+from scipy.spatial import KDTree
+from scipy.spatial import cKDTree
+import matplotlib.font_manager as fm
+
+#处理点云文件保存脚踝一下的部分点云
+def dealPointData(pidPath,pidNewPath):
+    # 读取 PLY 文件
+    point_cloud = o3d.io.read_point_cloud(pidPath)
+    # 移除离散点
+    cl, ind = point_cloud.remove_statistical_outlier(nb_neighbors=20, std_ratio=0.06)
+    point_cloud = point_cloud.select_by_index(ind)
+    # 保存处理后的点云
+    o3d.io.write_point_cloud(pidNewPath, point_cloud)
+    data = np.loadtxt(pidNewPath)
+    # 提取xyz坐标
+    x = data[:, 0]
+    y = data[:, 1]
+    z = data[:, 2]
+    # 创建一个布尔索引，筛选出在x-y平面内，半径在0.5范围内的点 (z >= 0.00) &
+    mask = (z >=0) & (z <= 0.1) & (x**2 + y**2 <= 0.7**2)
+    # 根据索引，保留符合条件的点
+    filtered_data = data[mask]
+    # 将保留的点云数据保存到新的文件
+    np.savetxt(pidNewPath, filtered_data, delimiter=' ')
+
+
+#计算点云的数据中，脚底和地板的切线位置
+def boxCenter(pid):
+    pidPath = "D:\\xyz\\" + str(pid) + "_point.xyz"
+    pidNewPath = "D:\\xyz\\" + str(pid) + "_new.xyz"
+    dealPointData(pidPath,pidNewPath)
+    
+    pcd = o3d.io.read_point_cloud(pidNewPath)
+    allPoints = np.asarray(pcd.points)
+    if len(allPoints) == 0:
+        print("点云为空，无法计算均值。")
+        return 0
+    
+    # 使用RANSAC算法提取平面
+    plane_model, inliers = pcd.segment_plane(distance_threshold=0.00670, ransac_n=3, num_iterations=1000)
+    inlier_cloud = pcd.select_by_index(inliers)
+    # 获取被染成红色的点的坐标数组
+    red_points = inlier_cloud.points
+    red_points_np = np.asarray(red_points)
+    # 获取 red_points_np 的 z 值数组
+    z_red_values = red_points_np[:, 2]
+    # 计算中位数
+    medianRed = np.median(z_red_values)
+    # 计算中位数向上的平均数
+    meanRedUp = np.mean(z_red_values[z_red_values > medianRed])
+    #计算中位数向下的平均数
+    #meanRedDown = np.mean(z_red_values[z_red_values < medianRed])
+
+    # Exclude ground points from allPoints
+    foot_points_np = np.asarray([point for point in allPoints if point not in red_points_np])
+    if len(foot_points_np) == 0 :
+        print("脚部点云为空。")
+        return 0
+    #过滤掉地板，计算出脚底的点云数据
+    points_np_foot = foot_points_np[(foot_points_np[:, 2] < 0.046) & (foot_points_np[:, 2] > meanRedUp)]
+    # 计算平均值
+    mean = np.mean(points_np_foot[:, 2])
+
+    # 按照 Z 值进行排序
+    sorted_points = points_np_foot[np.argsort(points_np_foot[:, 2])]
+    # 获取 Z 值最低的前十个点
+    if len(sorted_points) == 0:
+        print("脚底板最低的点云为空")
+        return 0
+    try:
+        lowest_points = sorted_points[10:20]
+    except Exception as e:
+        print("获取脚底板最低的倒数第十到20的点出现异常错误")
+        return 0
+    # 计算平均值
+    meanLowEst = np.mean(lowest_points[:, 2]) + 1.05
+    return meanLowEst