A. Civit

Hello! Were you able to solve this bug? Thanks!

Hi! @Altimis @KazuhideMimura I did the same changes you proposed in the model.py file, but i got the following error: ValueError: Provided `class_weight` was a list of 3 elements, but...

> @acivit > Hi, I haven't seen such error code, so I just write a change I've made in my code. > > I changed L. 2364-2375 of [model.py](https://github.com/matterport/Mask_RCNN/blob/master/mrcnn/model.py) as...

@KazuhideMimura I define the class_weight in a custom main function where i call the model.train ... take a look: The function get_class_weights returns a dict in form {1: weight1, 2:...

Hi @MahBadran93, I couldn't solve the problem yet, I think I will try to implement the class weights when defining the class_losses in the model.py file directly.

@MahBadran93 If you check the model.py file https://github.com/matterport/Mask_RCNN/blob/master/mrcnn/model.py , at the graph_loss functions (for example at the line 1076) def mrcnn_class_loss_graph(target_class_ids, pred_class_logits, active_class_ids): At the end of the function it...

Hi! Any update? Some days ago I opened an issue aswell: #2535 But still have no answer (neither hope that someones answers with the perfect answer :D)

Hello @MahBadran93 I tested with those changes and both precision and recall for an imbalanced object increased! (The magnitude of the data was: 200k, 200k, 100k, 4k) For the object...

Hi @MahBadran93, exactly, I did those changes :) It is complicated to explain how do I compute the precision and recall, but in the end i just make predictions with...

Hello @MahBadran93, sorry for the late answer. My implementation to compute the precision and recall is done outside the package. I just have a validation dataset (that wasn't use to...