我需要使用Python 2从磁盘读取单通道32位整数TIFF图像来执行一些图像分析。我尝试从matplotlib image.imread但是我无法使代码工作，因为数据被读取为4通道8位整数图像：
* {
margin: 0;
}
body {
background-color: gray;
}
html,
body {
height: 100%;
}
.left {
display: flex;
flex-flow: row wrap;
align-items: center;
justify-content: space-around;
order: 1;
width: 30%;
}
.middle {
display: flex;
flex-flow: column wrap;
order: 2;
width: 50%;
height: 99%;
}
.scienceBox {
width: 100%;
background-color: gray;
-radius: 5px;
margin-bottom: 2%;
}
.scienceBox p {
text-align: center;
font-size: 19px;
background-color: green;
padding: 0;
color: white;
}
.scienceBox li {
color: black;
font-size: 17px;
list-style-type: square;
}
.scienceBox special{
list-style-type: circle;
}
.container {
display: flex;
position: relative;
flex-wrap: wrap;
justify-content: space-between;
align-items: stretch;
padding-bottom: 2%;
min-height: 70vh;
width: 70%;
margin: 5% auto 8% auto;
background-color: white;
}
.container p {
margin-bottom: 12%;
}
.container img {
margin-bottom: 10%;
}
.container img:first-child{
margin-top: 5%;
}
.box1 {
text-align: center;
font-size: 20px;
}
.box h2{
color: orange;
text-align: center;
}
.right {
display: flex;
position: relative;
flex-flow: row wrap;
align-content: flex-start;
justify-content: center;
order: 3;
width: 20%;
height:100%;
}
.right div{
height: 25%;
}
.right .list{
height: auto;
text-align: center;
}
.list ul{
list-style: none;
padding: 0;
}
.list a{
text-decoration: none;
color: inherit;
}
.headbox h3{
color: orange;
text-align: center;
}
.sactive { /* s for sidebar */
font-weight: bold;
}
a {
color: orange;
text-decoration: none;
}
.hundredw {
position: relative;
width: 100%;
height: 10%;
text-align: center;
}
.papajohns{
position: absolute;
top: 60%;
right: 0;
left: 0;
margin: auto
}
.papajohns p {
margin: 0 1%;
}
ul.square li {
list-style-type: square;
margin-bottom: 2%;
}
.mtop {
margin-top: 3.5%;
}
@media all and (max-width: 900px) {
#nav {
flex-direction: column; /*updated*/
margin-bottom: 7%;
}
#nav ul {
padding-left: 0; /*added*/
}
#nav li {
flex: 1 1 100%; /*updated*/
padding: 5px;
-top: 1px solid black;
-bottom: 1px solid black;
}
#nav li a{
text-align: center;
padding: 5px;
margin: 5px;
}
#bigwrap {
width: 100%;
}
.container {
flex-flow: row wrap;
min-height: 100vh;
width: 100%;
}
.sarpinos{
top:56%;
}
.left {
align-content: flex-start;
height: 50%;
margin-bottom: 3%;
}
.middle {
height: 40%;
}
.left, .right {
flex: 1 100%;
}
.middle {
flex-flow: row wrap;
flex-grow: 1;
flex-shrink: 1;
justify-content: center;
align-content: flex-start;
}
.box {
width: 70%;
text-align: center;
}
#header2{
justify-content: space-around;
}
}
@media (min-width: 900px) and (max-width: 1100px) {
#nav{
justify-content: space-around;
}
.container {
width: 100%;
}
}问题：是否可以使用matplotlib读取单通道32位整数图像？
我知道有其他方法可以在Python中读取这样的图像，例如使用PIL中的Image.open：
<script src="https://ajax.googleapis.com/ajax/libs/jquery/1.11.1/jquery.min.js"></script>
<script src="https://code.jquery.com/mobile/1.4.5/jquery.mobile-1.4.5.min.js"></script>
<div class="container">
<div class="left">
<img src="http://placehold.it/50x50" width="50" height="50" alt="Picture of void" />
<img src="http://placehold.it/50x50" width="50" height="50" alt="Picture of void" />
<img src="http://placehold.it/50x50" width="50" height="50" alt="Picture of void" />
<img src="http://placehold.it/50x50" width="50" height="50" alt="Picture of void" />
<img src="http://placehold.it/50x50" width="50" height="50" alt="Picture of void" />
<img src="http://placehold.it/50x50" width="50" height="50" alt="Picture of void" />
<div class="hundredw">
<img src="http://placehold.it/50x50" width="50" height="50" alt="Picture of void" />
<div class="papajohns">
<p>file</p>
<p>files</p>
<p>files</p>
<p><i>files</i></p>
</div>
</div>
</div>
<div class="middle">
<div class="box">
<h2> Sample <h2>
</div>
<div class="box">
<p>
This is a sample sentence. This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence. This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence. This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence. This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence. This is a sample sentence. This is a sample sentence. This is a sample sentence.
</p>
<ul class="square">
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<ul>
</div>
<div class="box mtop">
<p>
This is a sample sentence. This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence.This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence. This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence. This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence. This is a sample sentence. This is a sample sentence. This is a sample sentence.
</p>
</div>
<div class="scienceBox">
<p>This is a sample sentence.</p>
<ul>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
</ul>
</div>
<div class="scienceBox">
<p>This is a sample sentence.</p>
<ul>
<li>This is a sample sentence.?
<ul class="special">
<li>This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence. This is a sample sentence. This is a sample sentence.
</li>
</ul>
</li>
<li>This is a sample sentence.?
<ul class="special">
<li>This is a sample sentence.
</li>
</ul>
</li>
<li>Is This is a sample sentence.?
<ul class="special">
<li>This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence. This is a sample sentence.
</li>
</ul>
</li>
<liThis is a sample sentence.?
<ul class="special">
<li>This is a sample sentence. This is a sample sentence. This is a sample sentence.
This is a sample sentence. This is a sample sentence. This is a sample sentence.
</li>
</ul>
</li>
</ul>
</div>
</div>
<div class="right">
<div class="headbox">
<h3>This is a sample sentence.</h3>
</div>
<div class="list">
<ul>
<li><a class="sactive" href="#">This is a sample sentence.</a></li>
<li><a href="#">This is a sample sentence.</a></li>
</ul>
</div>
<div class="headbox">
<h3>Important Informaiton</h3>
</div>
<div class="list2">
<ul>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
</ul>
<ul>
<li>Address</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
</ul>
<ul>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
<li>This is a sample sentence.</li>
</ul>
</div>
</div>
</div>另一种可能性是使用来自scikit-learn的io.imread：
>>> import numpy as np
>>> import matplotlib.image as mpimg
>>> img = mpimg.imread('my_image.tif')
>>> img.shape
(52, 80, 4)
>>> img[0:2, 0:2]
array([[[255, 255, 255, 255],
[255, 255, 255, 255]],
[[255, 255, 255, 255],
[255, 255, 255, 255]]], dtype=uint8)
另一种方法是利用OpenCV中的imread函数。但在这种情况下，数据必须转换为32位整数：
>>> from PIL import Image
>>> img = np.asarray(Image.open('my_image.tif'))
>>> img.dtype
dtype('int32')
>>> img.shape
(52, 80)
>>> img[0:2, 0:2]
array([[8745, 8917],
[8918, 9479]])
答案 0 :(得分：2)
SciPy no longer supports imread (versions 1.3.0+)
相反，您可以将 imageio 用于科学图像：
import imageio
im = imageio.imread('imageio:astronaut.png')
im.shape # im is a numpy array
答案 1 :(得分：1)
根据this tutorial，使用matplotlib无法读取32位整数图像：
Matplotlib绘图可以处理float32和uint8，但是除PNG以外的任何格式的图像读/写都限于uint8数据。
作为参考，我发现了一个基于SciPy ndimage.imread的解决方法：
from scipy import ndimage
img = ndimage.imread('my_image.tif', mode='I')
基于tifffile的方法（@Warren Weckesser建议）也可以正常使用：
from tifffile import TiffFile
with TiffFile('my_image.tif') as tif:
img = tif.asarray()