realsense python 操作摄像头

安装

读图：

获取内参：

同时读取2个摄像头，深度图和rgb图：

同时读取两个摄像头，彩色图：

3维重建：

安装

pip install pyrealsense2

读图：

import pyrealsense2 as rs
import numpy as np
import cv2if __name__ == "__main__":# Configure depth and color streamspipeline = rs.pipeline()config = rs.config()config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)# Start streamingpipeline.start(config)try:while True:# Wait for a coherent pair of frames: depth and colorframes = pipeline.wait_for_frames()depth_frame = frames.get_depth_frame()color_frame = frames.get_color_frame()if not depth_frame or not color_frame:continue# Convert images to numpy arraysdepth_image = np.asanyarray(depth_frame.get_data())color_image = np.asanyarray(color_frame.get_data())# Apply colormap on depth image (image must be converted to 8-bit per pixel first)depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)# Stack both images horizontallyimages = np.hstack((color_image, depth_colormap))# Show imagescv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE)cv2.imshow('RealSense', images)key = cv2.waitKey(1)# Press esc or 'q' to close the image windowif key & 0xFF == ord('q') or key == 27:cv2.destroyAllWindows()breakfinally:# Stop streamingpipeline.stop()

获取内参：

pipeline = rs.pipeline()
config = rs.config()
config.enable_stream(rs.stream.depth, 640, 480, rs.format.z16, 30)
config.enable_stream(rs.stream.color, 640, 480, rs.format.bgr8, 30)pipeline.start(config)# 创建对齐对象（深度对齐颜色）
align = rs.align(rs.stream.color)try:while True:frames = pipeline.wait_for_frames()# 获取对齐帧集aligned_frames = align.process(frames)# 获取对齐后的深度帧和彩色帧aligned_depth_frame = aligned_frames.get_depth_frame()color_frame = aligned_frames.get_color_frame()# 获取颜色帧内参color_profile = color_frame.get_profile()cvsprofile = rs.video_stream_profile(color_profile)color_intrin = cvsprofile.get_intrinsics()color_intrin_part = [color_intrin.ppx, color_intrin.ppy, color_intrin.fx, color_intrin.fy]print(color_intrin_part)# [318.48199462890625, 241.16720581054688, 616.5906372070312, 616.7650146484375]if not aligned_depth_frame or not color_frame:continuefinally:pipeline.stop()

fx、fy为xy轴的焦距。ppx、ppy为xy轴的原理点

开始报错：

Traceback (most recent call last):
File "F:\biadu_down\yolov5-face-master\data\aaa.py", line 17, in <module>
frames = pipeline.wait_for_frames()
RuntimeError: Frame didn't arrive within 5000

后来就好了，结果：

[318.36590576171875, 240.8314208984375, 382.5411682128906, 382.3366394042969]
[318.36590576171875, 240.8314208984375, 382.5411682128906, 382.3366394042969]
[318.36590576171875, 240.8314208984375, 382.5411682128906, 382.3366394042969]
[318.36590576171875, 240.8314208984375, 382.5411682128906, 382.3366394042969]

同时读取2个摄像头，深度图和rgb图：

import pyrealsense2 as rs
import cv2
import numpy as np
import time
import os
import sysif __name__ == '__main__':# 确定图像的输入分辨率与帧率resolution_width = 640  # pixelsresolution_height = 480  # pixelsframe_rate = 30  # fps# 注册数据流，并对其图像align = rs.align(rs.stream.color)rs_config = rs.config()rs_config.enable_stream(rs.stream.depth, resolution_width, resolution_height, rs.format.z16, frame_rate)rs_config.enable_stream(rs.stream.color, resolution_width, resolution_height, rs.format.bgr8, frame_rate)### d435i#rs_config.enable_stream(rs.stream.infrared, 1, 640, 480, rs.format.y8, frame_rate)rs_config.enable_stream(rs.stream.infrared, 2, 640, 480, rs.format.y8, frame_rate)# check相机是不是进来了connect_device = []for d in rs.context().devices:print('Found device: ',d.get_info(rs.camera_info.name), ' ',d.get_info(rs.camera_info.serial_number))if d.get_info(rs.camera_info.name).lower() != 'platform camera':connect_device.append(d.get_info(rs.camera_info.serial_number))if len(connect_device) < 2:print('Registrition needs two camera connected.But got one.')exit()# 确认相机并获取相机的内部参数pipeline1 = rs.pipeline()rs_config.enable_device(connect_device[0])# pipeline_profile1 = pipeline1.start(rs_config)pipeline1.start(rs_config)pipeline2 = rs.pipeline()rs_config.enable_device(connect_device[1])# pipeline_profile2 = pipeline2.start(rs_config)pipeline2.start(rs_config)try:while True:# 等待数据进来frames1 = pipeline1.wait_for_frames()frames2 = pipeline2.wait_for_frames()# 将进来的RGBD数据对齐aligned_frames1 = align.process(frames1)aligned_frames2 = align.process(frames2)# 将对其的RGB—D图取出来color_frame1 = aligned_frames1.get_color_frame()depth_frame1 = aligned_frames1.get_depth_frame()color_frame2 = aligned_frames2.get_color_frame()depth_frame2 = aligned_frames2.get_depth_frame()# --------------------------------------depth_frame1 = frames1.get_depth_frame()color_frame1 = frames1.get_color_frame()depth_frame2 = frames2.get_depth_frame()color_frame2 = frames2.get_color_frame()# 数组化数据便于处理ir_frame_left1 = frames1.get_infrared_frame(1)ir_frame_right1 = frames1.get_infrared_frame(2)if not depth_frame1 or not color_frame1:continueir_frame_left2 = frames2.get_infrared_frame(1)ir_frame_right2 = frames2.get_infrared_frame(2)if not depth_frame2 or not color_frame2:continuecolor_image1 = np.asanyarray(color_frame1.get_data())depth_image1 = np.asanyarray(depth_frame1.get_data())ir_left_image1 = np.asanyarray(ir_frame_left1.get_data())ir_right_image1 = np.asanyarray(ir_frame_right1.get_data())color_image2 = np.asanyarray(color_frame2.get_data())depth_image2 = np.asanyarray(depth_frame2.get_data())ir_left_image2 = np.asanyarray(ir_frame_left2.get_data())ir_right_image2 = np.asanyarray(ir_frame_right2.get_data())depth_colormap1 = cv2.applyColorMap(cv2.convertScaleAbs(depth_image1, alpha=0.03), cv2.COLORMAP_JET)images1 = np.hstack((color_image1, depth_colormap1))depth_colormap2 = cv2.applyColorMap(cv2.convertScaleAbs(depth_image2, alpha=0.03), cv2.COLORMAP_JET)images2 = np.hstack((color_image2, depth_colormap2))cv2.imshow('RealSense1', images1)cv2.imshow('RealSense2', images2)key = cv2.waitKey(1)if key & 0xFF == ord('q') or key == 27:cv2.destroyAllWindows()breakfinally:pipeline1.stop()pipeline2.stop()

同时读取两个摄像头，彩色图：

import pyrealsense2 as rs
import cv2
import numpy as np
import time
import os
import sysclass Realsense2:def __init__(self, camera_id_list=[0], camera_width=1280, camera_height=720, camera_fps=30):self.camera_width = camera_widthself.camera_height = camera_heightself.camera_fps = camera_fpsself.camera_id_list = camera_id_listdef camera_config(self):self.connect_device = []# get all realsense serial numberfor d in rs.context().devices:print('Found device: ',d.get_info(rs.camera_info.name), ' ',d.get_info(rs.camera_info.serial_number))if d.get_info(rs.camera_info.name).lower() != 'platform camera':self.connect_device.append(d.get_info(rs.camera_info.serial_number))# config realsenseself.pipeline_list = [rs.pipeline() for i in range(len(self.camera_id_list))]self.config_list = [rs.config() for i in range(len(self.camera_id_list))]if len(self.camera_id_list) == 1:  # one realsenseself.config_list[0].enable_device(self.connect_device[0])self.config_list[0].enable_stream(rs.stream.depth, self.camera_width, self.camera_height, rs.format.z16,self.camera_fps)self.config_list[0].enable_stream(rs.stream.color, self.camera_width, self.camera_height, rs.format.bgr8,self.camera_fps)self.pipeline_list[0].start(self.config_list[0])elif len(self.camera_id_list) >= 2:  # two realsenseif len(self.connect_device) < 2:print('Registrition needs two camera connected.But got one.Please run realsense-viewer to check your camera status.')exit()# enable configfor n, config in enumerate(self.config_list):config.enable_device(self.connect_device[n])config.enable_stream(rs.stream.depth, self.camera_width, self.camera_height, rs.format.z16,self.camera_fps)config.enable_stream(rs.stream.color, self.camera_width, self.camera_height, rs.format.bgr8,self.camera_fps)# self.config_list[n] = config# start pipelinefor n, pipeline in enumerate(self.pipeline_list):pipeline.start(self.config_list[n])def wait_frames(self, frame_id=None):'''camera_id:@ = camera number , get all frame@ = id , get specific id camera frame'''self.frame_list = [None for i in range(len(self.camera_id_list))]if frame_id != None:  # give a frame idfor n, camera_id in enumerate(self.camera_id_list):self.frame_list[n] = self.pipeline_list[frame_id].wait_for_frames()else:  # get all frameif len(self.camera_id_list) == 1:self.frame_list.append(self.pipeline_list[0].wait_for_frames())else:for n, camera_id in enumerate(self.camera_id_list):self.frame_list[n] = self.pipeline_list[n].wait_for_frames()def rgb_image(self, camera_id=0):color_frame = self.frame_list[camera_id].get_color_frame()color_image = np.asanyarray(color_frame.get_data())return color_imagedef depth_frame(self, frames):depth_frame = frames.get_depth_frame()return depth_framedef stop(self):for pipeline in self.pipeline_list:pipeline.stop()print("camera exit sucessfully.")if __name__ == '__main__':cap = Realsense2(camera_id_list=[0, 1], camera_width=640, camera_height=480)  #cap.camera_config()while True:start = time.time()cap.wait_frames()img0 = cap.rgb_image(0)img1 = cap.rgb_image(1)cv2.imshow("img0", img0)cv2.imshow("img1", img1)# print("FPS:", 1 / (time.time() - start), "f/s")if cv2.waitKey(1) == ord("q"):breakcap.stop()

3维重建：

GitHub - AoLyu/Some-implementions-with-RGBD-camera-RealSense-D435: some personal implementation of 3d object reconstruction, recognition and pose estimation