Closed Ayshine closed 2 years ago
same issue, not sure if it pertains to this https://github.com/matterport/Mask_RCNN/issues/636 ?
I tried the add the lines as suggested on the issue you passed. It didn't work. I am trying baloon tutorial from the reference article on README on the repo. Should it just work fine?
Same here, I am working on getting this all fixed in the hopes to understand how to adapt the Mask RCNN. The broadcasting issue seems to be within the matrix multiplication. https://www.statology.org/operands-could-not-be-broadcast-together-with-shapes/ I will implement it and let you know if that resolves the issue. Besides, see #578 even, so it did not help me.
Have you come across the #2112? That is another one that stomps me right now.
I haven't seen that error. I hope you resolve them both. I would like to learn if you have any suggestions for this issue
Ok now I have the second issue you are facing too.
I found https://github.com/ahmedfgad/Mask-RCNN-TF2 which is seemingly more up to date. Working on something else, atm. Please reach out to me if you gain some insight into the matter.
Thanks for passing the link. Let me try that version and inform you if it works.
I think its a leftover from a change. Before you could specify use_minimask=False.
Mini masks are used during training to minimize the load. A workaround is to specify the config
config.USE_MINI_MASK = False
original_image, image_meta, gt_class_id, gt_bbox, gt_mask = load_image_gt(
self.dataset_val, config, image_id)
@Weber-AILand I tried the repo you suggested. I was able to run training and predictions of the kangaroo example they gave. I'll keep working on that. Thanks!
I am trying to run the cells in
inspect_baloon_data.ipynb
for the Mini Masks cells for the following code I noticed that my masks and images does not match after usingload_image_gt
function. I guess this may be the reason I getValueError: operands could not be broadcast together with shapes (56,56) (1024,1024) (1024,1024)
error when I ranvisualize.display_instances(image, bbox, mask, class_ids, dataset.class_names)
line. My question is how should I resolve this?`