Jetseon TX2 & IntelRealsense D435i & Python

Jetseon TX2 & IntelRealsense D435i & Python & Socket

一、IntelRealsense Python Wrapper

GitHub

1、Installation

pip install pyrealsense2

2、Building From Source

① Ubuntu 14.04/16.04 LTS

a. Ensure apt-get up to date

sudo apt-get update && sudo apt-get upgrade

b. Install Python and its development files(或尝试用conda虚拟python环境)

sudo apt-get install python python-dev  # python2
sudo apt-get install python3 python3-dev  # python3

c. Clone source code from github

git clone https://github.com/IntelRealSense/librealsense.git

d. Run top level CMake command

cd librealsense
mkdir build    
cd build
cmake ../ -DBUILD_PYTHON_BINDINGS:bool=true
make -j4
sudo make install

e. Update PYTHONPATH environment variable to add the pyrealsense library(或者采用e’)

export PYTHONPATH=$PYTHONPATH:/usr/local/lib

e’. Extract ‘librealsense/build/wrappers/python/*’ files. Under the path, run:

python  # activate python enviroment
import pyrealsense2 as rs  #  ...

二、 D435i深度相机

参考

import pyrealsense2 as rs
import numpy as np
import cv2

if __name__=="__main__":
    # configure depth and color streams
    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)
    
    # start streaming
    pipeline.start(config)
    try:
        while True:
            # wait for a coherent pair of frames: depth and color
            frames = 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 arrays
            depth_image = np.asanyarray(depth_frame.get_data())
            color_image = np.asanyarray(color_frame.get_data())
            
            # apply colormap on depth image (image must be convert to 8-bit per pixel first)
            depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)
            
            # stack both images horizontally
            images = np.hstack((color_image, depth_colormap))
            
            # show images
            cv2.nameWindow('Realsense', cv2.WINDOW_AUTOSIZE)
            cv2.imshow('Realsense', images)
            key = cv2.waitKey(1)
            # press 'ESC' or 'q' to close the window
            if key & 0xFF == ord('q') or key == 27:
                cv2.destoryAllWindows()
                break
    finally:
        # stop streaming
        pipeline.stop()

三、Socket TCP数据传输

1、Windows 设置

① 点击右下角网络图标，进入网络和Internet设置

② 设置局域网ip地址

更改适配器选项->右键以太网，点击属性->选择IPv4，属性->勾选使用以下ip地址->设置ip地址->保存完成

③ 关闭Windows防火墙

2、TX2 & Ubuntu 设置

① 进入设置，选择网络设置

② 选中网线->options->IPv4->选择手动设置->Add->设置ip地址(注意与Windows在同一网段)->保存完成

3、联通测试

① Windows中’win + R’ -> 'cmd’打开terminal (输入ipconfig查看本机ip地址)

ping 192.168.10.1 # 假设TX2中ip地址设置为192.168.10.1    

② TX2&Ubuntu中’ctrl+alt+t’打开terminal (输入ifconfig查看本机ip地址)

ping 192.168.10.2 # 假设Windows中ip地址设置为192.168.10.2

4、深度相机图像数据传输

① client端/TX2读取深度图像并打包发送

# -*- coding: UTF-8 -*-
import cv2
import time
import socket
import pyrealsense2 as rs
import numpy as np

HOST = '192.168.10.2'  # server/windows ip地址
PORT = 8080  # server/windows 端口号
Address = (HOST, PORT)

tcpClient = socket.socket(socket.AF_INET, socket.SOCK_STREAM)  # 创建套接字
tcpClient.connect(Address)

# configure depth and color streams
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)

# start streaming
pipeline.start(config)

while True:
    start = time.perf_counter()
    frames = 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
    depth_image = np.asanyarray(depth_frame.get_data())  # (480, 640)
    depth_image = np.asanyarray(depth_image, 2).repeat(3, axis=2)  # (480, 640, 3)
    # depth_colormap = cv2.applyColorMap(cv2.convertScaleAbs(depth_image, alpha=0.03), cv2.COLORMAP_JET)
    color_image = np.asanyarray(color_frame.get_data())  # (480, 640, 3)
    
    # images = np.hstack((color_image, depth_colormap))  # (480, 1280, 3)
    images = np.hstack((color_image, depth_image))
    
    img_encode = cv2.imencode('.jpg', images)[1]
    bytedata = img_encode.tobytes()
    
    flag_data = (str(len(bytedata))).encode() + ",".encode() + " ".encode()
    tcpClient.send(flag_data)
    data = tcpClient.recv(1024)
    if ("ok" == data.decode()):
        tcpClient.send(bytedata)
    data = tcpClient.recv(1024)
    if ("ok" == data.decode()):
        print("延时：" + str(int((time.per_counter() - start) * 1000)) + "ms") 

② sever端/Windows/Ubuntu接收数据并解压可视化

# -*- coding: UTF-8 -*-
import socket
import cv2
import numpy as np
HOST = ''
PORT = 8080
ADDRESS = (HOST, PORT)
tcpServer = socket.socket(socket.AF_INET, socket.SOCK_STREAM)  # 创建一个套接字
tcpServer.bind(ADDRESS)  # 绑定本地ip
tcpServer.listen(5)  # 开始监听

while True:
    print("等待连接……")
    client_socket, client_address = tcpServer.accept()
    print("连接成功！")
    try:
        while True:
            data = client_socket.recv(1024)  # 接收标志数据
            if data:
                client_socket.send(b"ok")  # 通知客户端“已收到标志数据，可以发送图像数据”
                flag = data.decode().split(",")  # 处理标志数据
                total = int(flag[0])  # 图像字节流数据的总长度
                cnt = 0  # 接收到的数据计数
                img_bytes = b""  # 存放接收到的数据

                while cnt < total:
                    data = client_socket.recv(256000)  # 当接收到的数据少于数据总长度时，循环接收图像数据，直到接收完毕
                    img_bytes += data
                    cnt += len(data)
                    print("receive:" + str(cnt) + "/" + flag[0])
                client_socket.send(b"ok")  # 通知客户端“已经接收完毕，可以开始下一帧图像的传输”
                img = np.asarray(bytearray(img_bytes), dtype="uint8")  # 解析接收到的字节流数据，并显示图像
                img = cv2.imdecode(img, cv2.IMREAD_COLOR)
                cv2.imshow("img", img)
                cv2.waitKey(1)
            else:
                print("已断开！")
                break
    finally:
        client_socket.close()

先运行sever端，等待连接，再运行client端进行连接。