blocks|key|524613|text|你必须计算主轴(它是基于PCA的)。它将给你一个主要方向的好主意，然后你可以相应地旋转你的图像。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|524614|由于它是作为注释指向的，现在您必须测试薄的部分是否在图像的右侧，为此，您使用质心/重心:如果质心位于边界框的左侧，则机翼方向正确。|524615|下面是完整的算法：|524616|524617|计算主方向(主轴，用主成分分析计算)|unordered-list-item|524618|根据主轴和边界框旋转你的图像，质心在左边，那么你的图像定向良好，否则旋转大约180°。|524619|524620|这是结果。|524621|📷|atomic|offset|length|524622|524623|524624|524625|​|524626|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/bc2404e9fd1df5ec3064b830320de84d.png|imageAlt|1|https://ask.qcloudimg.com/http-save/yehe-900000/9da421950e064c1a0da76f86cde9e417.png|2|https://ask.qcloudimg.com/http-save/yehe-900000/88382852eb6706547539d80b4bd13eda.png|3|https://ask.qcloudimg.com/http-save/yehe-900000/09d95bf56f0eb5370efac2e5a1079adf.png^0|0|0|0|0|0|0|0|0|0|1|0|0|0|1|1|0|0|1|2|0|0|1|3|0|0^^$0|@$1|2|3|4|5|6|7|1D|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|1E|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|1F|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|1G|8|@]|9|@]|A|$]]|$1|G|3|H|5|I|7|1H|8|@]|9|@]|A|$]]|$1|J|3|K|5|I|7|1I|8|@]|9|@]|A|$]]|$1|L|3|-4|5|6|7|1J|8|@]|9|@]|A|$]]|$1|M|3|N|5|6|7|1K|8|@]|9|@]|A|$]]|$1|O|3|P|5|Q|7|1L|8|@]|9|@$R|1M|S|1N|1|1O]]|A|$]]|$1|T|3|P|5|Q|7|1P|8|@]|9|@$R|1Q|S|1R|1|1S]]|A|$]]|$1|U|3|P|5|Q|7|1T|8|@]|9|@$R|1U|S|1V|1|1W]]|A|$]]|$1|V|3|P|5|Q|7|1X|8|@]|9|@$R|1Y|S|1Z|1|20]]|A|$]]|$1|W|3|X|5|6|7|21|8|@]|9|@]|A|$]]|$1|Y|3|-4|5|6|7|22|8|@]|9|@]|A|$]]]|Z|$10|$5|11|12|13|A|$14|15|16|-4]]|17|$5|11|12|13|A|$14|18|16|-4]]|19|$5|11|12|13|A|$14|1A|16|-4]]|1B|$5|11|12|13|A|$14|1C|16|-4]]]]

You have to compute the main axis (it is based on PCA). It will give you a good idea of the main orientation, then you can rotate your image accordingly.

As it was pointed as a comment, you now have to test that the thin part is on the right side of the image, and for that you use the centroid/barycenter: if the centroid is on the left of the bounding box, then the wing is well oriented.

Here is the complete algorithm:

<ul>
<li>Compute the main orientation (main axis, computed with PCA)</li>
<li>Rotate your image according to the main axis orientation.</li>
<li>Compute the bounding box and centroid/barycenter</li>
<li>If the centroid is on the left, then your image is well oriented, else rotate it about 180°.</li>
</ul>

Here are the results...
<a href="https://i.stack.imgur.com/etL0b.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/etL0b.png" alt="enter image description here"></a>
<a href="https://i.stack.imgur.com/fJCey.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/fJCey.png" alt="enter image description here"></a>
<a href="https://i.stack.imgur.com/L6Cbj.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/L6Cbj.png" alt="enter image description here"></a>
<a href="https://i.stack.imgur.com/zzgi7.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/zzgi7.png" alt="enter image description here"></a>

blocks|key|788693|text|以下是Python/OpenCV中的一种方法。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|788694|788695|读取图像|unordered-list-item|788696|788697|788698|转换为灰度|788699|788700|788701|Threshold|788702|788703|788704|获取外轮廓|788705|788706|788707|从外轮廓获取minAreaRect点和角度|788708|788709|788710|获取旋转矩形的顶点|788711|788712|788713|绘制旋转的矩形|788714|788715|788716|根据需要更正角度|788717|788718|788719|打印角度|788720|788721|788722|将图像与绘制在其上的旋转矩形一起保存|788723|788724|​|788725|输入：|788726|788727|📷|atomic|offset|length|788728|788729|import+cv2
import+numpy+as+np

#+load+image+as+HSV+and+select+saturation
img+=+cv2.imread("wing2.png")
hh,+ww,+cc+=+img.shape

#+convert+to+gray
gray+=+cv2.cvtColor(img,+cv2.COLOR_BGR2GRAY)

#+threshold+the+grayscale+image
ret,+thresh+=+cv2.threshold(gray,0,255,0)

#+find+outer+contour
cntrs+=+cv2.findContours(thresh,+cv2.RETR_EXTERNAL,+cv2.CHAIN_APPROX_SIMPLE)
cntrs+=+cntrs[0]+if+len(cntrs)+==+2+else+cntrs[1]

#+get+rotated+rectangle+from+outer+contour
rotrect+=+cv2.minAreaRect(cntrs[0])
box+=+cv2.boxPoints(rotrect)
box+=+np.int0(box)

#+draw+rotated+rectangle+on+copy+of+img+as+result
result+=+img.copy()
cv2.drawContours(result,[box],0,(0,0,255),2)

#+get+angle+from+rotated+rectangle
angle+=+rotrect[-1]

#+from+https://www.pyimagesearch.com/2017/02/20/text-skew-correction-opencv-python/
#+the+`cv2.minAreaRect`+function+returns+values+in+the
#+range+[-90,+0);+as+the+rectangle+rotates+clockwise+the
#+returned+angle+trends+to+0+--+in+this+special+case+we
#+need+to+add+90+degrees+to+the+angle
if+angle+<+-45:
++++angle+=+-(90+%2B+angle)
+
#+otherwise,+just+take+the+inverse+of+the+angle+to+make
#+it+positive
else:
++++angle+=+-angle

print(angle,"deg")

#+write+result+to+disk
cv2.imwrite("wing2_rotrect.png",+result)

cv2.imshow("THRESH",+thresh)
cv2.imshow("RESULT",+result)
cv2.waitKey(0)
cv2.destroyAllWindows()|code-block|syntax|javascript|788730|788731|返回角度:+0.8814040422439575度|788732|带旋转矩形的图像：|788733|788734|788735|788736|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/865bdfe18c978ca4e646d8d7adc226ee.png|imageAlt|1|https://ask.qcloudimg.com/http-save/yehe-900000/4830030a9d6dd215d3d70f8d4b4bcf72.png^0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|1|1|0|0^^$0|@$1|2|3|4|5|6|7|2F|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|2G|8|@]|9|@]|A|$]]|$1|C|3|D|5|E|7|2H|8|@]|9|@]|A|$]]|$1|F|3|-4|5|6|7|2I|8|@]|9|@]|A|$]]|$1|G|3|-4|5|6|7|2J|8|@]|9|@]|A|$]]|$1|H|3|I|5|E|7|2K|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|2L|8|@]|9|@]|A|$]]|$1|K|3|-4|5|6|7|2M|8|@]|9|@]|A|$]]|$1|L|3|M|5|E|7|2N|8|@]|9|@]|A|$]]|$1|N|3|-4|5|6|7|2O|8|@]|9|@]|A|$]]|$1|O|3|-4|5|6|7|2P|8|@]|9|@]|A|$]]|$1|P|3|Q|5|E|7|2Q|8|@]|9|@]|A|$]]|$1|R|3|-4|5|6|7|2R|8|@]|9|@]|A|$]]|$1|S|3|-4|5|6|7|2S|8|@]|9|@]|A|$]]|$1|T|3|U|5|E|7|2T|8|@]|9|@]|A|$]]|$1|V|3|-4|5|6|7|2U|8|@]|9|@]|A|$]]|$1|W|3|-4|5|6|7|2V|8|@]|9|@]|A|$]]|$1|X|3|Y|5|E|7|2W|8|@]|9|@]|A|$]]|$1|Z|3|-4|5|6|7|2X|8|@]|9|@]|A|$]]|$1|10|3|-4|5|6|7|2Y|8|@]|9|@]|A|$]]|$1|11|3|12|5|E|7|2Z|8|@]|9|@]|A|$]]|$1|13|3|-4|5|6|7|30|8|@]|9|@]|A|$]]|$1|14|3|-4|5|6|7|31|8|@]|9|@]|A|$]]|$1|15|3|16|5|E|7|32|8|@]|9|@]|A|$]]|$1|17|3|-4|5|6|7|33|8|@]|9|@]|A|$]]|$1|18|3|-4|5|6|7|34|8|@]|9|@]|A|$]]|$1|19|3|1A|5|E|7|35|8|@]|9|@]|A|$]]|$1|1B|3|-4|5|6|7|36|8|@]|9|@]|A|$]]|$1|1C|3|-4|5|6|7|37|8|@]|9|@]|A|$]]|$1|1D|3|1E|5|E|7|38|8|@]|9|@]|A|$]]|$1|1F|3|-4|5|6|7|39|8|@]|9|@]|A|$]]|$1|1G|3|1H|5|6|7|3A|8|@]|9|@]|A|$]]|$1|1I|3|1J|5|6|7|3B|8|@]|9|@]|A|$]]|$1|1K|3|1H|5|6|7|3C|8|@]|9|@]|A|$]]|$1|1L|3|1M|5|1N|7|3D|8|@]|9|@$1O|3E|1P|3F|1|3G]]|A|$]]|$1|1Q|3|1H|5|6|7|3H|8|@]|9|@]|A|$]]|$1|1R|3|1S|5|1T|7|3I|8|@]|9|@]|A|$1U|1V]]|$1|1W|3|1H|5|6|7|3J|8|@]|9|@]|A|$]]|$1|1X|3|1Y|5|6|7|3K|8|@]|9|@]|A|$]]|$1|1Z|3|20|5|6|7|3L|8|@]|9|@]|A|$]]|$1|21|3|1H|5|6|7|3M|8|@]|9|@]|A|$]]|$1|22|3|1M|5|1N|7|3N|8|@]|9|@$1O|3O|1P|3P|1|3Q]]|A|$]]|$1|23|3|1H|5|6|7|3R|8|@]|9|@]|A|$]]|$1|24|3|-4|5|6|7|3S|8|@]|9|@]|A|$]]]|25|$26|$5|27|28|29|A|$2A|2B|2C|-4]]|2D|$5|27|28|29|A|$2A|2E|2C|-4]]]]

Here is one way in Python/OpenCV.
<ul>
<li>Read the image
</li>
<li>Convert to grayscale
</li>
<li>Threshold
</li>
<li>Get outer contour
</li>
<li>Get minAreaRect points and angle from outer contour
</li>
<li>Get vertices of rotated rectangle
</li>
<li>Draw the rotated rectangle
</li>
<li>Correct the angle as needed
</li>
<li>Print the angle
</li>
<li>Save the image with the rotated rectangle drawn on it
</li>
</ul>
 
Input:
<a href="https://i.stack.imgur.com/iDvsy.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/iDvsy.png" alt="enter image description here" /></a>
<pre><code>import cv2
import numpy as np

# load image as HSV and select saturation
img = cv2.imread(&quot;wing2.png&quot;)
hh, ww, cc = img.shape

# convert to gray
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

# threshold the grayscale image
ret, thresh = cv2.threshold(gray,0,255,0)

# find outer contour
cntrs = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
cntrs = cntrs[0] if len(cntrs) == 2 else cntrs[1]

# get rotated rectangle from outer contour
rotrect = cv2.minAreaRect(cntrs[0])
box = cv2.boxPoints(rotrect)
box = np.int0(box)

# draw rotated rectangle on copy of img as result
result = img.copy()
cv2.drawContours(result,[box],0,(0,0,255),2)

# get angle from rotated rectangle
angle = rotrect[-1]

# from https://www.pyimagesearch.com/2017/02/20/text-skew-correction-opencv-python/
# the `cv2.minAreaRect` function returns values in the
# range [-90, 0); as the rectangle rotates clockwise the
# returned angle trends to 0 -- in this special case we
# need to add 90 degrees to the angle
if angle &lt; -45:
 angle = -(90 + angle)
 
# otherwise, just take the inverse of the angle to make
# it positive
else:
 angle = -angle

print(angle,&quot;deg&quot;)

# write result to disk
cv2.imwrite(&quot;wing2_rotrect.png&quot;, result)

cv2.imshow(&quot;THRESH&quot;, thresh)
cv2.imshow(&quot;RESULT&quot;, result)
cv2.waitKey(0)
cv2.destroyAllWindows()
</code></pre>
 
Angle Returned: 0.8814040422439575 deg
Image with Rotated Rectangle:
<a href="https://i.stack.imgur.com/aljDm.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/aljDm.png" alt="enter image description here" /></a>

blocks|key|788753|text|对于类似的任务，我多次使用这个python+library进行面向对象的检测。这是一个可训练的神经网络，检测物体的位置和方向。知道方向角度后，可以使用opencv将对象旋转到所需的角度。您将需要标记一些图像来训练网络。|type|unstyled|depth|inlineStyleRanges|entityRanges|offset|length|data|788754|entityMap|0|LINK|mutability|MUTABLE|url|https://github.com/ivan-alles/localizer^0|F|E|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@$A|M|B|N|1|O]]|C|$]]|$1|D|3|-4|5|6|7|P|8|@]|9|@]|C|$]]]|E|$F|$5|G|H|I|C|$J|K]]]]

I used this <a href="https://github.com/ivan-alles/localizer" rel="nofollow noreferrer">python library</a> for oriented object detection many times for similar tasks. This is a trainable neural network detecting the positions and orientations of objects. When you know the orientation angle, you can rotate the object to the desired angle using opencv. You will need to label some images to train the network.

My images are always like this:
<a href="https://i.stack.imgur.com/NxVRE.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/NxVRE.png" alt="Original images"></a>

<a href="https://i.stack.imgur.com/Sjief.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Sjief.png" alt="Original images"></a>

But I need to rotate them to be like this:
<a href="https://i.stack.imgur.com/6WeWT.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/6WeWT.png" alt="rotated image"></a>
<a href="https://i.stack.imgur.com/la0yx.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/la0yx.png" alt="rotated image"></a>

But to do that, I need to find the orientation of the object, knowing that the thinner part of the object has to be on the left side.
In summary, the images are wings and the start of the wing has to be on the left side and the end of the wing has to be on the right side.

I hope someone can give me a suggestion, I've tried a bunch of different strategies but with no good result so far.

How to find the orientation of an object (shape)? - Python Opencv

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

文章

问答

视频

学习中心

腾讯云实验室

直播

竞赛

腾讯云代码分析专区

腾讯iOA零信任安全管理系统专区

腾讯云架构师技术同盟交流圈

腾讯云数据库专区

腾讯云顾问专区

腾讯云原生专区

腾讯混元专区

腾讯云TCE专区

腾讯云Lighthouse专区

腾讯云HAI专区

腾讯云Edgeone专区

腾讯云存储专区

腾讯云智能专区

腾讯轻联专区 

腾讯云开发专区

TAPD专区

腾讯轻量云游戏服专区

腾讯云最具价值专家

腾讯云架构师技术同盟

腾讯云创作之星

腾讯云开发者先锋

腾讯云代码助手

云原生构建

TAPD 敏捷项目管理

Cloud Studio

SDK中心

API中心

命令行工具

涵盖代码开发、场景应用、自动测试全流程，助你从零构建专属AI助手

一站式MCP教程库，解锁AI应用新玩法

我的图片总是这样的：​​​但我需要像这样旋转它们：​但要做到这一点，我需要找到对象的方向，知道对象的较薄部分必须在左侧。总而言之，图像是机翼，机翼的起点必须在左侧，机翼的末端必须在右侧。我希望有人能给我一个建议，我已经尝试了一堆不同的策略，但到目前为止都没有好的效果。

问如何找到对象(形状)的方向？- Python Opencv
EN

Stack Overflow用户

社区

活动

圈层

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问如何找到对象(形状)的方向？- Python OpencvEN