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179 lines
7.2 KiB
179 lines
7.2 KiB
import os |
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import time |
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import open3d as o3d |
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import numpy as np |
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def make_near_dict(base_dir,compact_dir): |
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"""""" |
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# 用于存储结果的字典 |
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results = {} |
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# 遍历目录中的所有 .ply 文件 |
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for ply_file in os.listdir(base_dir): |
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# 检查文件是否为 .ply 格式 |
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if ply_file.endswith('.ply'): |
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ply_path = os.path.join(base_dir, ply_file) |
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compact_ply_path = os.path.join(compact_dir, ply_file) |
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if os.path.exists(compact_ply_path): |
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ply_read_path = compact_ply_path |
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else: |
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ply_read_path = ply_path |
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# 读取点云 |
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pcd = o3d.io.read_point_cloud(ply_read_path) |
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# 获取点云的点数据 |
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points = np.asarray(pcd.points) |
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# 计算质心 |
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centroid = np.mean(points, axis=0) |
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# 计算 Y 轴最小值 |
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min_y_value = np.min(points[:, 1]) # Y 轴最小值 |
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max_y_value = np.max(points[:, 1]) |
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# 计算 X 轴最小值 |
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min_x_value = np.min(points[:, 0]) # X 轴最小值 |
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max_x_value = np.max(points[:, 0]) # X 轴最小值 |
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#ply_pid = ply_file.split("_")[0] |
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# 将结果存入字典 |
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results[ply_file] = { |
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"centroid": centroid, |
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"min_x_value": min_x_value, |
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"min_y_value": min_y_value, |
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"max_x_value": max_x_value, |
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"max_y_value": max_y_value, |
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} |
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# 打印结果 |
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# for ply_file, values in results.items(): |
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# print(f"文件: {ply_file}") |
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# print(f" 质心: {values['centroid']}") |
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# print(f" X 轴最小值: {values['min_x_value']}") |
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# print(f" Y 轴最小值: {values['min_y_value']}") |
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# 计算每个ply需要触碰检测的 |
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check_touch_dict = {} |
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for ply_file in results.keys(): |
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print(ply_file) |
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#ply_pid = ply_file.split("_")[0] |
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#print(ply_pid) |
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bounds_min_x = results[ply_file]["min_x_value"] |
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bounds_min_y = results[ply_file]["min_y_value"] |
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#bounds_center = results[ply_file]["centroid"] |
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need_check_list = [] |
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need_values_dict = {} |
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for ply_file_near in results.keys(): |
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#print(ply_file_near) |
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if ply_file!= ply_file_near: |
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bounds_max_x = results[ply_file_near]["max_x_value"] |
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bounds_max_y = results[ply_file_near]["max_y_value"] |
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# if ply_file == "151140_9cm_x1=30.578+41.705+90.753.ply": |
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# print("-"*50) |
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# print("主：：",ply_file) |
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# print("从：：",ply_file_near) |
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# print(f"center_x{bounds_center[0]}") |
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# print(f"center_y{bounds_center[1]}") |
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# print(f"bounds_max_x{bounds_max_x}") |
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# print(f"bounds_max_y{bounds_max_y}") |
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# time.sleep(3) |
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# 235605_12cm_x1=33.774+30.837+120.344.ply |
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# if bounds_center[0]<bounds_max_x and bounds_center[1]<bounds_max_y: |
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# print("添加",ply_file_near) |
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# need_check_list.append(ply_file_near) |
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#if bounds_near_center[0]>bounds_min_x and bounds_near_center[1]>bounds_min_y: |
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#print("-"*50) |
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# print(f"bounds_min_x{bounds_min_x}") |
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# print(f"bounds_max_x{bounds_max_x}") |
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x_dis = bounds_min_x - bounds_max_x |
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y_dis = bounds_min_y - bounds_max_y |
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#print(f"x_dis=={x_dis}") |
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#print(f"y_dis=={y_dis}") |
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#if ply_file=="158040_15cm_x1=80.682+89.345+152.468.ply": |
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#if ply_file == "235547_4.8cm_x1=29.339+39.528+57.63.ply": |
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# print("主：：",ply_file) |
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# print("从：：",ply_file_near) |
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#if ply_file == "158040_15cm_x1=80.682+89.345+152.468.ply": |
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#if ply_file == "151140_9cm_x1=30.578+41.705+90.753.ply": |
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# print("主：：", ply_file) |
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# print("临近：：", ply_file_near) |
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# time.sleep(3) |
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if x_dis<-10 and y_dis<-10: |
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need_check_list.append(ply_file_near) |
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need_values_dict["need_check_list"] = need_check_list |
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# need_values_dict["max_x_value"] = bounds_max_x |
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# need_values_dict["max_y_value"] = bounds_max_y |
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check_touch_dict[ply_file] = need_values_dict |
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# print(check_touch_dict) |
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# print("开始要计算触碰检测的数据") |
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# for ply_file, values in check_touch_dict.items(): |
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# print("*"*50) |
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# print(ply_file) |
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# print(values) |
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# 去掉离比较远的数据 |
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for check_touch_key,check_touch_values in check_touch_dict.items(): |
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print("-"*50) |
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#print(check_touch_key) |
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#print(check_touch_values["need_check_list"]) |
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need_check_list= check_touch_values["need_check_list"] |
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#print(len(need_check_list)) |
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if len(need_check_list)>2: |
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ply_A_path = os.path.join(base_dir, check_touch_key) |
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compact_ply_path = os.path.join(compact_dir, check_touch_key) |
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if os.path.exists(compact_ply_path): |
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ply_read_path = compact_ply_path |
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else: |
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ply_read_path = ply_A_path |
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pcd_A = o3d.io.read_point_cloud(ply_read_path) |
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points_A = np.asarray(pcd_A.points) |
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distances = [] |
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for i, check_touch in enumerate(need_check_list): |
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point = results[check_touch]['centroid'] |
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ply_path = os.path.join(base_dir, check_touch) |
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# 读取当前点云 |
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pcd = o3d.io.read_point_cloud(ply_path) |
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points = np.asarray(pcd.points) |
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# 计算点云之间最小点对距离（brute-force） |
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diff = points_A[:, np.newaxis, :] - points[np.newaxis, :, :] # (N, M, 3) |
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dists = np.linalg.norm(diff, axis=2) # (N, M) |
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min_distance = np.min(dists) |
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#print(f"check_touch: {check_touch}, centroid: {point}, min_distance: {min_distance:.4f}") |
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distances.append((i, point, min_distance, check_touch)) |
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distances.sort(key=lambda x: x[2]) |
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# 提取最近的 3 个点 |
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nearest_points = distances[:5] |
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last_elements = [item[-1] for item in nearest_points] |
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# print(f"nearest_points---------{nearest_points}") |
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# print(f"check_touch_key--------{check_touch_key}") |
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# print(f"last_elements--------{last_elements}") |
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check_touch_dict[check_touch_key]["need_check_list"] = last_elements |
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return check_touch_dict |
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# for check_touch_key,check_touch_values in check_touch_dict.items(): |
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# print("*"*50) |
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# print(check_touch_key) |
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# print(check_touch_values) |
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if __name__ == '__main__': |
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bounds_fix_out_dir = "/data/datasets_20t/type_setting_test_data/print_bounds_fix_data/" |
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check_touch_dict=make_near_dict(bounds_fix_out_dir) |
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print(f"check_touch_dict--------------{check_touch_dict}") |
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""" |
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{'need_check_list': ['131508_18cm_x1=51.412+87.921+181.446.ply', '239617_12cm_x1=43.987+54.233+120.691.ply']}, |
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""" |
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