walden的博客

import random import os def file_name(file_dir): L=[] for root, dirs, files in os.walk(file_dir): for file in files: if os.path.splitext(file)[1] == '.jpg':

a = torch.randn(1,1,3,1) a.expand(2,1,3,1) a.expand(1,2,3,1) a.expand(1,1,6,1)#runtimerror a.expand(1,1,3,2) a.expand(1,1,3,1)#a.expand(1,1,3,1) == a b = torch.randn(1,1,2,2) b.repeat(1,1,1,1)#b.r...

import cv2 import matplotlib.pyplot as plt img = cv2.imread("Fig2.png", 0) img = cv2.medianBlur(img, 5) ret1, th1 = cv2.threshold(img, 127, 225, cv2.THRESH_BINARY) ret2, th_1 = cv2.threshold(img, 0, ...

import cv2 cap=cv2.VideoCapture("C:\\Users\\Walden\\Downloads\\CCTV.mp4") ret,frame=cap.read() count=0 fps = cap.get(cv2.CAP_PROP_FPS) size = (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(ca...

1.报错：TypeError: unorderable types: NoneType() >= str()定位到Anaconda3\Lib\distutils目录下，将distutils.cfg中的[build] compiler=mingw32 替换为[build] compiler=msvc2.该命令会完成编译cpp文件的过程。...

import requests from requests.exceptions import RequestException import re import json from multiprocessing import Process,Manager,Lock,Pool import io headers={'User-Agent':'Mozilla/5.0 '} def get_

import random import os import os.path as osp from PIL import Image import numpy as np dataset = np.genfromtxt('D:\\local_optimization\\uiuc\\all.txt', dtype=str) for idx in dataset:

import numpy as np from PIL import Image import os im = Image.open('D:\\local_optimization\\uiuc\\orignal\\32.png').convert('RGB') im_size = im.size out=np.zeros((im_size)) in_ = np.array(im, dtype...

from PIL import Image from pylab import imshow from pylab import array from pylab import plot from pylab import title # 读取图像到数组中 im = array(Image.open('E:\\imagelocation\\6.jpg')) # 绘制图像 imshow(im) #

对一张图片进行翻转和旋转，最终能得到连原图在内的8张不同的照片 import random import os import os.path as osp from PIL import Image dataset_dir='/home/walden/pytorch/uiuc/data/VOC/demo' def file_name(file_dir): L=[]

import random import os import os.path as osp from PIL import Image dataset_dir='/home/walden/pytorch/uiuc/data/VOC/cls' def file_name(file_dir): L=[] for root, dirs, files in

import matplotlib import torch x = torch.FloatTensor([1,1,1,1,1,2,2,2,2,2,2,3,3,3,3,3,3,3,3,1,1,1,1,1,0,0,1,1,1,1]) #x = torch.FloatTensor([1,1,1,1,1,20,20,20,20,20,20,3,3,3,3,3,3,3,3,1,1,1,1,1,0,0,...