YahamaTarGe的博客

pth 模型转 onnx时出错参考 up3 = F.interpolate(output3, size=[output2.size(2), output2.size(3)], mode="nearest") # errorup3 = F.interpolate(output3, size=[32, 32], mode="nearest") ...

import torchx = torch.linspace(1, 8, steps=8).view(4, 2)print(x)area1=(x[:,0]>5.5)&(x[:,1]>5.5)c=x[:,0]*x[:,1]area2=c>25area=area1|area2print(x[area])if 0:# index=torch.max(area,...

start = time.time()result = model(input)end = time.time()torch.cuda.synchronize()start = time.time()result = model(input)torch.cuda.synchronize()end = time.time()一共上述两种测试时间的方式，正确的方式是第二种，为什么是...

torchvision.transforms.Normalize()中的mean和std参数做什么用呢？疑问1：按照我的理解，归一化就是要把图片3个通道中的数据整理到[-1, 1]区间。x = (x - mean(x))/stddev(x)只要输入数据集x确定了，mean(x)和stddev(x)也就是确定的数值了，为什么Normalize()函数还需要输入mean和std的数值呢？疑问...

import osimport numpy as npimport cv2 ims_path = r'E:\Datasets/' # Path to Images#ims_list = os.listdir(ims_path)g = os.walk(ims_path)ims_list = ['%s\\%s' % (i[0], j) for i in g if i[0].ends...

转载自 https://blog.youkuaiyun.com/Hansry/article/details/84071316一.torchvision.transformsTransfoms 是很常用的图片变换方式，可以通过compose将各个变换串联起来**1. class torchvision.transforms.Compose (transforms) **这个类将多个变换方式结合在一起...