Mask RCNN custom data training. Problem with JSON to mat conversion

18 views (last 30 days)
Hi,
I will be really very grateful if somebody can help me here. I am stuck for more than 6 months :(
So, I am trying to train mask RCNN using custom data set. I am following the MATLAB Mask RCNN example here: https://www.mathworks.com/help/vision/ug/example-InstanceSegmentationUsingMaskRCNNDeepLearningExample.html#PerformInstanceSegmentationUsingMaskRCNNExample-1
I have used image labeler to annotate the images and then used this exportgtruthtoJSON program https://www.mathworks.com/help/vision/ug/export-ground-truth-object-to-custom-and-coco-json-files.html.
However, when I am using this as an input for the Mask RCNN, 'Extract the COCO annotations to MAT files using the unpackAnnotations helper function is not working'. The command window shows the processing is done. but in reatlity the 'annotations_unpacked' folder remains empty.
Please help, if you know how to solve this issue.
Thank you!

Answers (1)

Debraj Maji
Debraj Maji on 1 Nov 2023
Hi @Sam
I see that you have labelled data from the COCO dataset as your ground truth using the Image Labeler and exported it to JSON file. You are then using it as an input to a masked RCNN network for training/inference.
As per the documentation, this is a limitation of the current Iimage Labeller as the JSON file exported by the “exportGroundTruthToJSON” helper function cannot be imported back into MATLAB as a ground truth object.
Possible solutions include:
  • Using a separate pre-trained network to annotate the images and export the annotations to JSON format.
  • Using the COCO API for MATLAB as found here: coco API-MATLAB
You may go through the following MathWorks documentation link to learn more about exporting ground truth objects to custom and COCO JSON files:

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!