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Realsense D430 python pointclound

时间:2018-09-26 21:39:33      阅读:762      评论:0      收藏:0      [点我收藏+]

标签:any   python   value   map   pytho   wait   port   eal   _for   

来自:https://github.com/IntelRealSense/librealsense/issues/1231
------------------------------
import pyrealsense2 as rs
pipeline = rs.pipeline()
pipe_profile = pipeline.start()
frames = pipeline.wait_for_frames()
depth_frame = frames.get_depth_frame()
color_frame = frames.get_color_frame()

# Intrinsics & Extrinsics
depth_intrin = depth_frame.profile.as_video_stream_profile().intrinsics
color_intrin = color_frame.profile.as_video_stream_profile().intrinsics
depth_to_color_extrin = depth_frame.profile.get_extrinsics_to(color_frame.profile)

# Depth scale - units of the values inside a depth frame, i.e how to convert the value to units of 1 meter
depth_sensor = pipe_profile.get_device().first_depth_sensor()
depth_scale = depth_sensor.get_depth_scale()

# Map depth to color
depth_pixel = [240, 320]   # Random pixel
depth_point = rs.rs2_deproject_pixel_to_point(depth_intrin, depth_pixel, depth_scale)
color_point = rs.rs2_transform_point_to_point(depth_to_color_extrin, depth_point)
color_pixel = rs.rs2_project_point_to_pixel(color_intrin, color_point)
pipeline.stop()


-----------------------------

pc = rs.pointcloud() frames = pipeline.wait_for_frames() depth = frames.get_depth_frame() color = frames.get_color_frame() img_color = np.asanyarray(color.get_data()) img_depth = np.asanyarray(depth.get_data()) pc.map_to(color) points = pc.calculate(depth) vtx = np.asanyarray(points.get_vertices()) tex = np.asanyarray(points.get_texture_coordinates()) npy_vtx = np.zeros((len(vtx), 3), float) for i in range(len(vtx)): npy_vtx[i][0] = np.float(vtx[i][0]) npy_vtx[i][1] = np.float(vtx[i][1]) npy_vtx[i][2] = np.float(vtx[i][2]) npy_tex = np.zeros((len(tex), 3), float) for i in range(len(tex)): npy_tex[i][0] = np.float(tex[i][0]) npy_tex[i][1] = np.float(tex[i][1])




Realsense D430 python pointclound

标签:any   python   value   map   pytho   wait   port   eal   _for   

原文地址:https://www.cnblogs.com/herd/p/9709638.html

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