本文介绍了在python中将图像转换为2D数组的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

我想将图像转换为具有5列的2D数组,其中每行的格式为[r, g, b, x, y]. x,y是像素的位置,r,g,b是像素值. (我将使用此数组作为机器学习模型的输入).在python中有比这更有效的实现吗?

I want to convert an image to 2D array with 5 columns where each row is of the form [r, g, b, x, y]. x, y is the position of the pixel and r,g,b are the pixel values. (I will be using this array as input to a machine learning model). Is there a more efficient implementation than this in python?

import Image
import numpy as np

im = Image.open("farm.jpg")
col,row =  im.size
data = np.zeros((row*col, 5))
pixels = im.load()
for i in range(row):
    for j in range(col):
        r,g,b =  pixels[i,j]
        data[i*col + j,:] = r,g,b,i,j

推荐答案

我最近不得不写这篇文章并以

I had to write this recently and ended up with

indices = np.dstack(np.indices(im.shape[:2]))
data = np.concatenate((im, indices), axis=-1)

im是一个numpy数组.您可能最好用

Where im is a numpy array. You are probably better off reading the images straight into numpy arrays with

from scipy.misc import imread
im = imread("farm.jpg")

或者,如果您已安装Scikit映像,则更好

Or, better still if you have Scikit Image installed

from skimage.io import imread
im = imread("farm.jpg")

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08-04 07:48
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