人工智能-项目实践-信息检索-一个基于vgg16的图像检索系统，带有简单的pythonGUI

import h5py import matplotlib.image as mpimg import matplotlib.pyplot as plt import numpy as np from extract_cnn_vgg16_keras import VGGNet def search(querypath, h5name): # 要搜的原图path，h5文件的name，原数据集的path query = querypath index = 'models/' + h5name + '.h5' result = 'database/' + h5name + '/' h5f = h5py.File(index, 'r') feats = h5f['dataset_1'][:] imgNames = h5f['dataset_2'][:] h5f.close() print("--------------------------------------------------") print(" searching starts ") print("--------------------------------------------------") # read query image queryImg = mpimg.imread(query) # 初始化 VGGNet16 模块 model = VGGNet() #提取query图片的特征 queryVec = model.vgg_extract_feat(query) print('--------------------------') print('--------------------------') scores = np.dot(queryVec, feats.T) rank_ID = np.argsort(scores)[::-1] rank_score = scores[rank_ID] print(rank_score) # 检索出三张相似度最高的图片 maxres = 3 imlist = [] # 输出相似度 for i, index in enumerate(rank_ID[0:maxres]): imlist.append(imgNames[index]) print("image names: " + str(imgNames[index]) + " scores: %f" % rank_score[i]) print("top %d images in order are: " % maxres, imlist) # 输出前三张 for i, im in enumerate(imlist): image = mpimg.imread(result + "/" + str(im, 'utf-8')) plt.title("Result of research %d" % (i + 1)) plt.imshow(image) plt.show()