I created siamese model with triplet loss function.
I tested it a little bit and notice that when object are small, like 2/5 of the image space, model is matching images with similar background instead of object.
Some of pictures were taken on the same background what is causing the issue as I think.
Is there any way to maybe extract objects? train model to recognize those object, ignore background?
Shape of each image is (150, 150, 3).
the siamese  model actually deepened on encoded data simply its match between tow encoded feature representation  so it not know your object of intraset you have    extract object  than do the matching between them
for example if the model you built was for face matching
use opencv to extract the faces and than do the matching you want to make
Model is recognizing background better than objects