0
$\begingroup$

I have a huge problem using my own created dataset for image segmentation using Tensorflow. The dataset that I've build contain images like the one shown below:

Dataset example

The problem that I have is: How do I use my own dataset specifically for image segmentation? I've looked at the documentation on how to create datasets but all the examples either only use object detection with a single class or classify the entire image. I want to assign every pixel to a class (image segmentation) and use it to train my model.

I've also found examples of image segmentation but they all use existing datasets such as Cityscapes, ADE20k etc. How can I use my own images and data and transform it to a tensorflow dataset so that I can use it for training?

$\endgroup$
0
$\begingroup$

Just having segmented images is probably not enough. The training data for segmentation needs to be in a specific format. Have a look at the coco dataset for image segmentation. Sometimes we need to convert the dataset into that format. I'd suggest reading up a bit on how to train a mask rcnn model on your own dataset. There are a number of articles available online.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.