python多图拼接并利用resnet提取特征

代码功能：

1、将多张图拼接成一张大图；

2、基于resnet提取大图的特征。

import torch import torch.nn as nn from torchvision import models, transforms from torch.autograd import Variable import numpy as np from PIL import Image from os import listdir #resnet50提取图像特征 transform1 = transforms.Compose([transforms.Scale(256),transforms.CenterCrop(224),transforms.ToTensor()]) resnet50_feature_extractor = models.resnet50(pretrained = True) resnet50_feature_extractor.fc = nn.Linear(2048, 2048) torch.nn.init.eye(resnet50_feature_extractor.fc.weight) for param in resnet50_feature_extractor.parameters():param.requires_grad = Falseimages = [Image.open(fn) for fn in listdir() if fn.endswith('.png')] #多图拼接成一张长图 if len(images)>0:width,height=images[0].sizefor image in images:w,h = image.sizeif w>width:width=wif h>height: height=hlongImg = Image.new(images[0].mode,(width,height*len(images)))for i,im in enumerate(images):longImg.paste(im,box=(0,i*height))#拼接#长图向量化 imgarr = np.array(longImg)if imgarr.shape[2] == 4: #四通道转为三通道img1 = img.convert("RGB")#img = Image.fromarray(img.astype('uint8')).convert('RGB')img2 = transform1(img1)x = Variable(torch.unsqueeze(img2, dim=0).float(), requires_grad=False)y = resnet50_feature_extractor(x)y = y.data.numpy()print (y.shape)

 

总结

以上是生活随笔为你收集整理的python多图拼接并利用resnet提取特征的全部内容，希望文章能够帮你解决所遇到的问题。

如果觉得生活随笔网站内容还不错，欢迎将生活随笔推荐给好友。