<p>You can use OpenCV's <a href="https://docs.opencv.org/2.4/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html?highlight=minarearect#minarearect" rel="nofollow noreferrer">cv2.minAreaRect()</a> to detect oriented/rotated rectangular bounding boxes. Below's an example result from <a href="https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_contours/py_contour_features/py_contour_features.html#b-rotated-rectangle" rel="nofollow noreferrer">OpenCV-Python-tutorials</a>:</p>

<p><a href="https://i.sstatic.net/V9LKp.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/V9LKp.png" alt="Using cv2.minAreaRect()"></a></p>

<p>Alternatively, you could train a supervised object detection model to output 8 co-ordinate values (x0,y0,x1,y1,x2,y2,x3,y3) of the quadrilateral by training with a labeled oriented-bounding-box dataset. You could also create the bounding box labels yourself for the same by using tools such as <a href="http://www.robots.ox.ac.uk/~vgg/software/via/via_demo.html" rel="nofollow noreferrer">VGG Annotator Tool</a> among others.</p>

CC BY-SA 4.0
2020-01-04T07:58:14.283Z
2020-01-04T07:58:14.283Z
Balraj Ashwath
<p>Is there some established Object Detection algorithm that is able to detect the four corners of an arbitrary quadrilateral  (x0,y0,x1,y1,x2,y2,x3,y3) as opposed to the more typical perpendicular rectangular (x,y,w,h) ?</p>

<object-detection>
Object Detection Algorithm that detects four corners of arbitrary quadrilateral, not just perpendicular rectangular
Loop
# Object Detection Algorithm that detects four corners of arbitrary quadrilateral, not just perpendicular rectangular

(Asked by: username_0 on 2020-01-03)

Is there some established Object Detection algorithm that is able to detect the four corners of an arbitrary quadrilateral (x0,y0,x1,y1,x2,y2,x3,y3) as opposed to the more typical perpendicular rectangular (x,y,w,h) ?

**Tags:** object-detection


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## 1 answers

### Answer by username_1 on 2020-01-04. Score: 1

You can use OpenCV's [cv2.minAreaRect()](https://docs.opencv.org/2.4/modules/imgproc/doc/structural_analysis_and_shape_descriptors.html?highlight=minarearect#minarearect) to detect oriented/rotated rectangular bounding boxes. Below's an example result from [OpenCV-Python-tutorials](https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_contours/py_contour_features/py_contour_features.html#b-rotated-rectangle):

[![Using cv2.minAreaRect()](https://i.sstatic.net/V9LKp.png)](https://i.sstatic.net/V9LKp.png)

Alternatively, you could train a supervised object detection model to output 8 co-ordinate values (x0,y0,x1,y1,x2,y2,x3,y3) of the quadrilateral by training with a labeled oriented-bounding-box dataset. You could also create the bounding box labels yourself for the same by using tools such as [VGG Annotator Tool](http://www.robots.ox.ac.uk/~vgg/software/via/via_demo.html) among others.


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