小编use*_*264的帖子

我有一些代码试图确定代码块的执行时间.

#include <time.h>
#include <stdio.h>

int main()
{
   clock_t start_t, end_t, total_t;
   int i;

   start_t = clock(); //clock start
   printf("Starting of the program, start_t = %ld\n", start_t);

   printf("Going to scan a big loop, start_t = %ld\n", start_t);
   for(i=0; i< 10000000; i++)  //trying to determine execution time of this block
   {
   }
   end_t = clock(); //clock stopped
   printf("End of the big loop, end_t = %ld\n", end_t);

   total_t = (long int)(end_t - start_t);
   printf("Total time taken by CPU: %lu\n", total_t  );

   return(0); …

我正在使用Python与PIL和SciPy.我想从网络摄像头捕获图像,然后使用numpy和Scipy进一步处理它.有人可以帮我解决问题.

这里的代码有一个预定义的图像"lena",但我希望使用我自己捕获的图像而不是"lena"图像.我对代码做了哪些更改？

from scipy import misc
lena = misc.lena()
lx, ly = lena.shape
import matplotlib.pyplot as plt
crop_lena = lena[lx / 4: - lx / 4, ly / 4: - ly / 4]
plt.imshow(crop_lena)

另一个例子

import scipy
from scipy import ndimage
import matplotlib.pyplot as plt
import numpy as np
l = scipy.misc.lena()
plt.figure(figsize=(10, 3.6))
plt.subplot(131)
plt.imshow(l, cmap=plt.cm.gray)
plt.show()

我试图在python中实现自适应直方图均衡.我拍摄一张图像并将其分割成较小的区域,然后将传统的直方图均衡应用于它.然后我将较小的图像合并为一个并获得最终的合成图像.最终图像在性质上看起来非常块状,并且对于每个单独的区域具有不同的对比度水平.有没有办法可以保持每个单独图像的均匀对比度,使其看起来像单个图像而不是缝合在一起的较小图像.

import cv2
import numpy as np
from matplotlib import pyplot as plt
from scipy.misc import imsave
from scipy import ndimage
from scipy import misc
import scipy.misc
import scipy

import image_slicer
from image_slicer import join
from PIL import Image

img = 'watch.png'
num_tiles = 25
tiles = image_slicer.slice(img, num_tiles)


for tile in tiles:
    img = scipy.misc.imread(tile.filename)
    hist,bins = np.histogram(img.flatten(),256,[0,256])
    cdf = hist.cumsum()
    cdf_normalized = cdf *hist.max()/ cdf.max()  
    plt.plot(cdf_normalized, color = 'g')
    plt.hist(img.flatten(),256,[0,256], color = 'g')
    plt.xlim([0,256])
    plt.legend(('cdf','histogram'), loc = 'upper …

我正在使用Debian Linux和python 2.7.
我正在阅读图像并尝试处理它但我显示以下错误.有人可以告诉我我做错了什么吗？

import Image
import scipy
from scipy import ndimage
import matplotlib.pyplot as plt
import numpy as np
from scipy import misc
import scipy.misc

img = scipy.misc.imread("/home/subhradeep/Desktop/test.jpg")
array=np.asarray(img)
plt.figure(figsize=(10, 3.6))

plt.subplot(131)
plt.imshow(array, cmap=plt.cm.gray)

plt.subplot(132)
plt.imshow(array, cmap=plt.cm.gray, vmin=10, vmax=100)
plt.axis('off')

plt.subplot(133)
plt.imshow(array, cmap=plt.cm.gray)
plt.contour(array, [160, 211])
plt.axis('off')

plt.subplots_adjust(wspace=0, hspace=0., top=0.99, bottom=0.01, left=0.05,right=0.99)
plt.show()

我收到以下错误消息

Traceback (most recent call last):
  File "1saveimg.py", line 22, in <module>
    plt.contour(array, [160, 211])
  File "/usr/lib/pymodules/python2.7/matplotlib/pyplot.py", line 2632, in contour
    ret = ax.contour(*args, **kwargs)
  File …

我正在尝试使用 python 中的图像切片器分割图像，然后对每个图像应用直方图均衡化并将它们组合回来。我能够将图像分成更小的块，我可以看到它们正在更新，但在将它们拼接在一起后，我最终得到了与原始图像相同的图像。有人可以指出我做错了什么。文件名为 watch.png

import cv2
import numpy as np
from matplotlib import pyplot as plt
from scipy.misc import imsave
# import scipy
from scipy import ndimage
from scipy import misc
import scipy.misc
import scipy

import sys
import argparse
import image_slicer
from image_slicer import join


img = 'watch.png'
num_tiles = 64
tiles = image_slicer.slice(img, num_tiles)



file = "watch"
k = 0
filelist =[]
for i in range(1,9):
    for j in range(1,9):
        filelist.insert(k, file+"_"+str(i).zfill(2)+"_"+str(j).zfill(2)+".png")
        k=k+1

for i in range(0,num_tiles):
    img = …