(row, column) or (column, row) ?

I am new to this, so this question may sound dumb.

As far as what I know, here are some different notations for a point (1, 100)

0/0---column--->
 |   --------------**.** (1,100)
 |
row
 |
 |
 v
(matrix)

0/0---X--->
 |
 |
 Y
 |
 | **.** (1,100)
 v
 (opencv and plt)

So if I use my custom dataset, I believe I should go with the matrix one and do “xmin, ymin, xmas, ymax”, since all the internal operations are on matrices. But in keras-retinanet/examples/ResNet50RetinaNet - COCO 2017.ipynb, I see cv2.rectangle(draw, (b[0], b[1]), (b[2], b[3]), ... for both detections and annotations. Aren’t those inverted (should be (b[1], b[0]), (b[3], b[2])?), or is there anything I missed?

Thanks in advance.

[hgaiser]

Yeah that’s right. All image coordinates and boxes follow the (xmin, ymin, xmax, ymax).

[de-vri-es]

“xmin, ymin, xmas, ymax”

I see what you did there 😉

Anyway, for numpy matrices you’re right that the first coordinate is the row index. In an image however, we say that the X axis points to the right and the Y axis points down. I’ve never seen a different convention. This doesn’t match with each other, but opencv deals with the difference internally.

Long story short: when specifying an opencv point or rectangle, you should use image coordinates, not matrix indices.