Empty detection results with Faster R-CNN - help!!

I am trying to train a Faster R-CNN 2D but I always get empty detection results...

• I use a pre-trained backbone network on my data (which has an accuracy of around 70%);
• The images have size [512 512 1] and are uint8 (as well as the input size of the network);
• The bounding boxes are approximately between 30x30 to 60x60;
• I have 2 classes of objects;
• 250 epochs (already varied it but the result is the same) with MB size 64;
• I've tried it with a very low positive overlap range ([0.1 1]);
• ROI Mas pooling 7x7
• I used fasterRCNNLayers to create a faster R-CNN object.

(500 images+bounding boxes around objects of two classes to train)

Example of training data table:

imageFilename class1 class2

'image1.tiff' [100, 110, 35, 50] []

'image2.tiff' [] [50,20, 40,30]

1) Is there a problem with the images being grayscale and not in color?

2) Do I have to have bounding boxes from a region other than the object? (as described here: https://www.mathworks.com/matlabcentral/answers/500950-bounding-box-not-drawn-some-variables-are-empty).

I really need some help... I don't understand how it runs without errors and then it can't find any object.

Thank you so so much in advance!!!

[Juanita Londono]

Hi, where you able to solve the problem? Thanks