CODEWITHSUNDEEP
pythondeep-learningcomputer-visionobject-detectionyolo
mchd
mchd

Reputation: 3163

YOLOv4 annotations saves dimensions in a [0,1] float interval

This is from an annotations file for an image:

0 0.6142131979695431 0.336 0.467005076142132 0.392

The first 0 is the class label. 0.6142131979695431 and 0.336 are the x and y coordinates of the bounding box. 0.467005076142132 and 0.392 are the width and the height of the bounding box. However, what I don't understand is why the x, y, width and height are in a [0,1] float interval. Someone told me that it is a percentage, but a percentage relative to what?

For example, I am writing software that builds a synthetic dataset. This is one training image that I have produced. It has the bounding boxes around the objects that I want to detect.

enter image description here

The bounding boxes wrap the Wizards and Ubuntu logos perfectly. So, how can I annotate them like the format above?

Upvotes: 2

Views: 5388

Answers (1)

Abhi25t
Abhi25t

Reputation: 4693

The width/height in YOLO format is the fraction of total width/height of the entire image. So the top-left corner is always (0,0) and bottom-right corner is always (1,1) irrespective of the size of the image.

See this question for the conversion of bounding box (x1, y1, x2, y2) to YOLO style (x, y, w, h).

enter image description here

Upvotes: 6

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