labels = pickle.load(f) # load test data using Pickle with open(pklfile[:-4]+'_test.pkl', 'rb') as f: class_1 = pickle.load(f) class_2 = pickle.load(f) labels = pickle.load(f) model = knn.KnnClassifier(labels,v
# coding:utf-8 from PIL import Image,ImageEnhance import pytesseract #上面都是导包,只需要下面这一行就能实现图片文字识别 im = Image.open('arial.png') #下面为增强部分 enh_con = ImageEnhance.Contrast(im) contrast = 1.5 image_contrasted = enh_con.enhance(contrast) #image_contrasted.show() #增...
as plt #绘图的包 from osgeo import ogr #矢量操作的包 from osgeo import osr #矢量操作的包 import datetime #计算时间 import random from sklearn.ensemble import RandomForestClassifier from sklearn.metrics import confusion_matrix def read_tif(fileName): ''' 读取栅格数据 ''' dataset_img = ...
(X_test_features) # Train the logistic regression classifier from sklearn.model_selection import GridSearchCV # Define the model clf_logistic = LogisticRegression(solver='liblinear') # Define the parameter grid param_grid = { 'C': [0.1, 0.5, 1, 5, 10], 'max_iter': [100, 500, 1000...
(1,3,1), plot_image(im, 'original') im1 = binary_opening(im, disk(12)) pylab.subplot(1,3,2), plot_image(im1, 'opening with disk size ' + str(12)) im1 = binary_closing(im, disk(6)) pylab.subplot(1,3,3), plot_image(im1, 'closing with disk size ' + str(6)) pylab...
knn=KNeighborsClassifier(n_neighbors=5)knn.fit(X_train,y_train)y_pred=knn.predict(X_test) 模型评价 代码语言:javascript 代码运行次数:0 运行 AI代码解释 from sklearn.metricsimportclassification_report,confusion_matrixprint(confusion_matrix(y_test,y_pred))print(classification_report(y_test,y_pred)...
在本节中,我们将演示如何使用 scikit image 的形态学模块中的函数来实现一些形态学操作,首先对二值图像进行形态学操作,然后对灰度图像进行形态学操作。 二进制运算 让我们从二值图像的形态学操作开始。在调用函数之前,我们需要创建一个二进制输入图像(例如,使用具有固定阈值的简单阈值)。 腐蚀 侵蚀是一种基本的形态...
selecthr = 0.8):# step1: load the face image data ,get the matrix consists of all imageFaceMat = loadImageSet('D:\python/face recongnition\YALE\YALE\unpadded/').T# step2: average the FaceMatavgImg = mean(FaceMat,1)# step3: calculate the difference of avgimg and all image data(...
Updated all .md files to contain newest image Jan 18, 2023 Chrome-Dino-Bot-using-OpenCV-feature-matching Updated all .md files to contain newest image Jan 18, 2023 Classification-with-localization-convert-any-keras-classifier-into-a-detector Updated all .md files to contain newest image Jan 18...
fromIPython.displayimportImage 我们实现了用于二类别分类的Adaline算法,并通过梯度下降优化算法来学习模型的权重系数.训练集上的每一次迭代,我们使用如下更新规则来更新权重向量w: 换句话说,我们基于整个训练数据集来计算梯度,并沿着与梯度▽J(w)相反的方向前进以更新模型的权重.为了找到模型的最优权重,我们将待优化的...