CODEWITHSUNDEEP
computer-visionyolodarknetlabelimg
user13354476
user13354476

Reputation:

about bounded boxes of objects

i'm trying to compose a dataset for the detection of soccer players, ball etc.. in a soccer game, i'm using alexeyAB Darknet framework,

So in the labeling phase in each image there are at least 8 players a ball and other stuff, at some point it is logical to think about the fact that i will have enough instances per player, but not enough for the ball and the goalkeeper for example,

so can i only marking bounded boxes the ball and other things avoiding to do it with the players to not waste time?

Upvotes: 0

Views: 44

Answers (1)

Pe Dro
Pe Dro

Reputation: 3033

If you are training the model on your own dataset, I would recommend limiting the number of labels/classes in your data to what you seek. For example if you only want your model to see balls, goal-posts and Not players, simply keep the classes as balls and goal-posts. (This reminds me of a classification problem where 0 stands for balls and 1 stands for goal-post). P.S you mentioned object detection and Not Localization, which is the purpose of the YOLO models.

Upvotes: 0

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