Problem with custom dataset about siamese-mask-rcnn

[michaelisc]

Which config file did you use? It looks like it could simply be a mismatch between the small and large model.

[TuanNguyenSKKU]

Thank you for your response.
I have used the default config.py from the Siamese model and used it in the shapesConfig class as below.

`class shapesConfig(siamese_config.Config):

NAME = "shapes"  # Override in sub-classes
EXPERIMENT = 'example'
# NUMBER OF GPUs to use. For CPU training, use 1
# GPU_COUNT = 2
IMAGES_PER_GPU = 1
STEPS_PER_EPOCH = 100
NUM_CLASSES = 1 + 3  # For background + my_classes
DETECTION_MIN_CONFIDENCE = 0.9
MASK_SHAPE = [56, 56]
USE_MINI_MASK = False

`

config.zip

[michaelisc]

Have you tried using 2 classes (1 + 1)? Because this model is Siamese and uses an example of the class instead of class labels there is just one foreground class that covers the others implicitly.

[TuanNguyenSKKU]

I have never tried it before. Do you have any solutions for class labels? Because I think someone can also implement this repository with many class labels.
Thank you.

[michaelisc]

Yes that is correct but it would defy the idea of the task and model. If you want to use multiple class labels you should probably use a standard object detection model from a toolbox like mmdetection or detectron2.

[TuanNguyenSKKU]

Thank you for your suggestions.

sir in Siamese how can we only use two image and pretrain model to detect the output ?.. sir can you make a page to explain every part of code ... i am facing problem understanding it .. i am a beginner to this field

[F2Wang]

I am slight confused by this thread of discussion, I understand that the network can only output binary labels, but should it be trained that way too (Only bg and instance)? If that's the case if you provide a reference image of people, shouldn't it consider all coco classes it has been trained on as an instance, given that people, apples, bicycles were all trained as the same class?