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lets train YOLO V8 instant segmentation models hey there welcome to learn opencv in this video we will check out the trashcan data set and train the ultralytics yellow V8 segmentation models on it the data set consists of underwater imagery to detect and segment trash in and around the ocean floor well be using the material version of the data set as it has fewer classes it is made up of 6008 images in the train split and 1204 Mages in the validation split and is made up of 16 classes the annotations were originally in Json format but we have cleaned and converted them to YOLO format a yellow box label is represented by class label X Center y center width and height of the bounding box in a normalized format but how do we represent mask labels lets understand with an example the first five numbers still encode the class label and the Box information but from the six number onwards each subsequent pair represents a pair of space separated X Y coordinates forming the boundary points o
