Interpretation of object detection bounding box coordinates for YOLO | Object detection using Python

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In this video, we are going to understand the correct way to interpret the bounding boxes in YOLO. We are also going to use an example to demonstrate the process of calculating the bounding box coordinates.

There are many formats of bounding boxes that are available for object detection and YOLO also has one for itself. YOLO's format is based on the COCO dataset. It focuses on the center coordinate of the bounding boxes and also the height and width of the bounding boxes. Lastly, it also uses normalization of the values which is also explained in the video.

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I think you accidentally label both Normalized coordinates as x. One of them should be y. 1:54

MrSkyydude

so yolo uses midpoint for detection but for other algorithms use corner for box format?

unamattina

How can I calculate the length and width of the bounding box

CuongLeTrung-hfuv

how to stream height and width like 'dog intro video'?
i need code

-moeurnsoklin

what's the motive of doing normalization for a predicted output? and does confidence score have any connection with normalization?please reply bro

vijiviji-wdid

jb code ni tha dena to video dene ki kia zrurat thi?

saverahanif

Interpretation of object detection bounding box coordinates for YOLO | Object detection using Python

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