Jamesaonier的博客

图片的几何变换《06仿射变换》代码import cv2import numpy as npimg = cv2.imread('1.jpg',1)cv2.imshow('src',img)imgInfo = img.shapeheight = imgInfo[0]width = imgInfo[1]matSrc=np.float32([[0,0],[0,height-1],[wid...

图片的几何变换《07图片旋转》代码import cv2import numpy as npimg = cv2.imread('1.jpg',1)cv2.imshow('src',img)imgInfo = img.shapeheight = imgInfo[0]width = imgInfo[1]'''我们使用getRotationMatrix2D()函数来完成图片的旋转操作...

图片的几何变换《05图片缩放》代码import cv2import numpy as npimg = cv2.imread('1.jpg',1)cv2.imshow('source',img)imgInfo = img.shapeheight = imgInfo[0]width = imgInfo[1]# matScale缩放矩阵matScale = np.float32([...

图片的几何变换《04图片的镜像》代码import cv2import numpy as npimg = cv2.imread('1.jpg',1)cv2.imshow('src', img)imgInfo = img.shapeheight = imgInfo[0]width = imgInfo[1]deep = imgInfo[2]newImgInfo = (height*...

图片的几何变换《03图片的移位：原理实现》代码import cv2import numpy as npimg = cv2.imread('1.jpg',1)cv2.imshow('src', img)imgInfo = img.shapeheight = imgInfo[0]width = imgInfo[1]dst = np.zeros(img.shape, np.uint8...

图片的几何变换《03图片的移位》## 代码import cv2import numpy as npimg = cv2.imread('1.jpg',1)cv2.imshow('src', img)imgInfo = img.shapeheight = imgInfo[0]width = imgInfo[1]# 移位矩阵matShift = np.float32([[1,0,1...

图片的几何变换《02图片剪切》代码import cv2import numpy as npimg =cv2.imread('1.jpg',1)cv2.imshow('OriginalPicture', img)imginfo = img.shapeprint(imginfo)dst=img[150:300,300:500]cv2.imshow('dst',dst)cv2.wai...

图片的几何变换《01图片的缩放》代码# import cv2## # 读入原图片# img = cv2.imread('1.jpg')# # 打印出图片尺寸# imgInfo=img.shape# print(imgInfo)# height=imgInfo[0]# wirth=imgInfo[1]# mode=imgInfo[2] #图像的通道数## dstHeigt...

tensorflow基本操作《06神经网络逼近股票收盘均价》代码layer1：激励函数+乘加运算import tensorflow as tfimport numpy as npimport matplotlib.pyplot as pltdate = np.linspace(1,15,15)endPrice = np.array([2511.90,2538.26,2510.68,2...

figure语法及操作(1)figure语法说明figure(num=None, figsize=None, dpi=None, facecolor=None, edgecolor=None, frameon=True)num:图像编号或名称，数字为编号 ，字符串为名称figsize:指定figure的宽和高，单位为英寸；dpi参数指定绘图对象的分辨率，即每英寸多少个像素，缺省值为80 ...

tensorflow基本操作《06神经网络逼近股票收盘均价》代码#神经网络逼近股票收盘均价 手动输入数据import tensorflow as tfimport numpy as npimport matplotlib.pyplot as plt # 绘图模块date = np.linspace(1,15,15) # linspace 线性增长定义日期 1增长到15 一共15个数据...

tensorflow基本操作《matplotlib的使用》代码import numpy as npimport matplotlib.pyplot as pltx=np.array([1,2,3,4,5,6,7,8])y=np.array([3,5,8,4,2,6,5,4])plt.plot(x,y,'r') #折线图 1.x 2.y 3.color lw=10 :宽度#...

tensorflow基本操作《04numpy的使用》代码import numpy as npdata1=np.array([1,2,3,4,5])print(data1)data2=np.array([[1,2],[3,4]])print(data2)#矩阵维度print(data1.shape,data2.shape)#zero onesprint(np.zeros([2,3...

tensorflow基本操作《03矩阵基础》补充代码import tensorflow as tfmat0=tf.constant([[0,0,0],[0,0,0]])mat1=tf.zeros([2,3])mat2=tf.ones([3,2])mat3=tf.fill([3,2],15)mat=tf.constant([[4],[5],[6]])mat4=tf.zeros_lik...

tensorflow基本操作《03矩阵基础》代码'''# placeholdimport tensorflow as tfdata1=tf.placeholder(tf.float32)data2=tf.placeholder(tf.float32)dataAdd=tf.add(data1,data2)with tf.Session() as sess: print(se...

tensorflow基本操作《02四则运算》代码import tensorflow as tfdata1=tf.constant(6)# data2=tf.constant(2)data2=tf.Variable(2,name='var1')dataAdd=tf.add(data1,data2)dataCopy=tf.assign(data2,dataAdd) #dataAdd ...

tensorflow基本操作《01常量变量》代码import tensorflow as tfdata1=tf.constant(2,dtype=tf.int32)data2=tf.Variable(20,name='var1')print(data1)print(data2)# 所有的操作必须使用session会话来执行'''sess = tf.Session()prin...

opencv+tensorflow 《04 像素操作》代码import cv2img = cv2.imread("t.jpg",1)(b,g,r)=img[100,100]print(b,g,r) # bgr# 10 100 -》110 100for i in range(0,100): img[10+i,100]=(255,0,0)cv2.imshow("image...

opencv+tensorflow 《03 图片质量》代码import cv2img = cv2.imread("t.jpg",1) #读取图片 第二个参数0：为灰度图片 1：为彩色图片# cv2.imwrite("write1.jpg",img,[cv2.IMWRITE_JPEG_QUALITY,0])# jpg：0压缩比高 0-100 有损压缩，以牺牲图片质量为代价# jp...

原创 opencv+tensorflow 《01 图片读取与展示》代码：import cv2img = cv2.imread("t.jpg",1) #读取图片 第二个参数0：为灰度图片 1：为彩色图片cv2.imwrite("write.jpg",img) # 1.name 2.data(解码之后的数据）...

opencv+tensorflow 《01 图片读取与展示》opencv+tensorflow 《01 图片读取与展示》代码如下opencv+tensorflow 《01 图片读取与展示》代码如下import cv2img = cv2.imread("t.jpg",1) #读取图片 第二个参数0：为灰度图片 1：为彩色图片cv2.imshow("image",img) #1.窗体...

霍夫变换​霍夫变换（Hough Transform）是在1959年由气泡室（Bubble Chamber）照片的机器分析而发明，发明者Paul Hough在1962年获得美国专利，被命名为Method and Means for Recognizing Complex Patterns（用于识别复杂图案的方法和手段）。该专利对直线采用斜截距参数化，但由于斜率可能变成无穷大，这有可能导致无限变换空...