猫头军师兵书

图像填充函数用法速查

参数速查

boxes

np.fft.fft

cv2.line

彩色和灰度图像明暗调节解决方案

假设k张图片序列存在数组（张量）frames：512×512×3×k，如何制作成视频，并另存为avi?import cv2videoWriter = cv2.VideoWriter('MySaveVideo.avi', cv2.VideoWriter_fourcc('I', '4', '2', '0'), 20, (512,512))for i in range(20): temp = frames[:,:,:,i] cv2.imshow('a',temp) v

图像聚类一般是灰度值的聚类。import numpy as npimport cv2img = cv2.imread('differential geometry.jpeg')img2 = img.reshape((-1,3))# convert to np.float32img2 = np.float32(img2)# define criteria, number of...

import numpy as npX = np.mgrid[-5:5:5]X1 = np.mgrid[-5:5:5j]Y1,Y2 = np.mgrid[-5:5,10:17]Z1,Z2,Z3 = np.mgrid[-5:5,10:17,1:3]print(X)print(X1)print(Y1,Y2)输出：[-5 0][-5. -2.5 0. 2.5...

用for else语句。import matplotlib.pyplot as pltfig, ax = plt.subplots()for i in range(10): for j in range(10): ax.plot(i, j,'o') if i == 5 and j == 3: break else:...

目录tf.argmax() tf.reduce_mean()tf.argmax(), 自带降低一维import tensorflow as tfimport numpy as npx = np.ones((2,3,3,1))z = tf.argmax(x,axis = 3)print(z.get_shape())with tf.Session() as sess: ...

二值化 cv2.thresholdimport cv2import numpy as npimg = cv2.imread('Hydrogen_Density_Plots.png',0)threshold = 10maxvalue = 157print(np.amax(img))ret_otsu,thresh1 = cv2.threshold(img,threshold,maxv...

tf.tile( input, multiples, name=None)Args:input: ATensor. 1-D or higher. multiples: ATensor. Must be one of the following types:int32,int64. 1-D. Length must be the same as the ...

import cv2tile = cv2.resize(tile,(int(Ximageorg/256),int(Yimageorg/256)),interpolation=cv2.INTER_CUBIC) import scipy from keras.preprocessing import image import matplotlib.pyplot as pltim...

convert()convert()是图像实例对象的一个方法，接受一个 mode 参数，用以指定一种色彩模式1 ------------------（1位像素，黑白，每字节一个像素存储）L ------------------（8位像素，黑白）P ------------------（8位像素，使用调色板映射到任何其他模式）RGB------------------（3x8位像素，真彩色）RG...

from keras.preprocessing import image import matplotlib.pyplot as pltimport cv2import numpy as npimg_path = '/Parthenon.jpg'im2 = image.load_img(img_path, target_size=(224, 224))img = image....

张量积 一般指的是Kronecker product a⊗b很显然，该运算不遵守交换律。import numpy as npa = np.eye(3)b = np.ones((3,2,3))c = np.kron(a,b)aarray([[ 1., 0., 0.], [ 0., 1., 0.], [ 0., 0., 1.]])...

纺射+插值

import numpy as npimport matplotlib.pyplot as pltimport nibabel as nibimport cv2ds = nib.load(image_path)img2 = ds.get_fdata()plt.figure()plt.imshow(img2,'gray')plt.title('scr')#rotateh...

import cv2img = cv2.imread('wintercome.jpeg')rows,cols,_ = img.shapeh = min(rows,cols)img = img[0:h,0:h]mat = cv2.getRotationMatrix2D((h/2,h/2),90,1)dst = cv2.warpAffine(img,mat,(h,h))cv2.i...

目录numpy核心对象是多维数组 方括号的深度 numpy数组怎么index 举例：高频函数画图numpy核心对象是多维数组numpy 可以说并没有矩阵的概念，它的核心思维方式是多维数组。>>> np.zeros((256,256)) #产生一个256×256的全0矩阵需要两个括号，行列均需赋值。或>>> np.zeros([256...

画直线from mpl_toolkits.axisartist.axislines import SubplotZeroimport matplotlib.pyplot as pltimport numpy as npfig = plt.figure(1)ax = SubplotZero(fig, 111)fig.add_subplot(ax)for direction in...

参数问题

左上角是原点

numpy.vstackStack arrays in sequence vertically (row wise).numpy.dstackStack arrays in sequence depth wise (along third axis).stackJoin a sequence of arrays along a new axis.vstackStack ...

两幅图size、channel、归一化格式都相同，那么import cv2import numpy as npimg1 = cv2.imread('lena.jpeg')img2 = cv2.imread('monalisa.jpg')w,h,channel = np.shape(img1)img2 = cv2.resize(img2,(h,w),interpolation...

从RGB空间说起所谓RGB空间就是red，green和blue颜色3个向量张成的空间，正好类似于3维欧氏空间。如图所示，3个向量均归一化了，其中(0，0，0)处为黑色，（1，1，1）处为白色。这种映射关系和光学棱镜色散和叠加相对应。实际应用常用的在[0, 255]区间编码。简单的例子：RGB空间（0，0，255）为纯蓝色，（255，0，0）为纯红色。举栗import cv...

Stacks a list of rank-Rtensors into one rank-(R+1)tensor.import tensorflow as tfa = tf.constant([[1,2,3],[4,5,6]]) b = tf.constant([[7,8,9],[10,11,12]])ab1 = tf.stack([a,b],axis=0)ab2 = tf.st...

import tensorflow as tfimport numpy as npparams = np.arange(23)a = tf.gather(params,1)with tf.Session() as sess: print(sess.run(a)) params = np.arange(24).reshape(2,-1)a = tf.gather(pa...

In mathematics, a fractal is a detailed, recursive, and infinitely self-similar mathematical set. import tensorflow as tfimport numpy as np# 导入可视化库import PIL.Imagefrom cStringIO import Strin...

二维数组情形例1mu = np.mean(features,axis=0)features为M×N, 那么mu为(N,)或记1×N例2X_input = np.concatenate((features,intercept_feature),axis=1)features为M×N，那么X_input为M ×（N+1）例3>>> a = n...