opencv图像灰度化-算法优化之前的灰度图像进行处理的时候是浮点型运算，运算时间较长，现在可以对灰度图像进行算法优化，将浮点型运算转换成整型运算。提高运算速度。方法一：import cv2import numpy as npimg1 = cv2.imread(r"C:\Users\lenovo\Desktop\python\python_vision\image.jpg",1)imgInfo =

opencv图像处理图像融合分别提出俩个图像中某一个部分，然后将俩个图像提取的部分相加在一起。import cv2import numpy as npimport randomimg0 = cv2.imread(r"C:\Users\lenovo\Desktop\python\python_vision\image.jpg",1)img1 = cv2.imread(r"C:\Users\lenov

ROS下物体检测和识别功能-find_object_2dhttps://blog.csdn.net/qq_42145185/article/details/105089929?utm_medium=distribute.pc_relevant.none-task-blog-BlogCommendFromMachineLearnPai2-3.nonecase&depth_1-utm_sour

Solidworks2018导出URDF模型位置错乱遇到的问题SLAM学习：Solidworks2018导出小车URDF模型下遇到的问题

moveit问题一：moveit_assistan加载urdf模型问题运行：roslaunch moveit_setup_assistant setup_assistant.launch当新建立的工作空间需要使用moveit进行加载模型崩溃问题，需要讲工作空间路径添加到一下文件中去。打开环境变量gedit ~/.bashrc将下列添加到最后边。source /home/li/ml_ws/devel

opencv图像处理毛玻璃import cv2import numpy as npimport randomimg = cv2.imread(r"C:\Users\lenovo\Desktop\python\python_vision\image.jpg",1)imgInfo = img.shapeheight = imgInfo[0]weight = imgInfo[1]dst = np.zer

opencv边缘检测canny边缘检测时需要先将图像处理成灰度图像。下一步是高斯滤波，后续会讲解。import cv2import numpy as npimport randomimg0 = cv2.imread(r"C:\Users\lenovo\Desktop\python\python_vision\image.jpg",1)imgInfo = img0.shapeheight = img

opencv图像处理浮雕效果浮雕效果是将俩个像素差值加上某一个固定的像素值。import cv2import numpy as npimport randomimport mathimg0 = cv2.imread(r"C:\Users\lenovo\Desktop\python\python_vision\image.jpg",1)imgInfo = img0.shapeheight = img

ROS下Python读取ft_300传感器数据硬件条件：ur3ft_300ros:melodic#!/usr/bin/env python2import rospyfrom geometry_msgs.msg import WrenchStampedimport socketimport timeclass socket_connection:def __init__(self, publishe

opencv图像灰度化方法一：直接在读取的时候进行灰度化。import cv2img0 = cv2.imread(r"C:\Users\lenovo\Desktop\python\python_vision\image.jpg",0)img1 = cv2.imread(r"C:\Users\lenovo\Desktop\python\python_vision\image.jpg",1)print