Code for the paper titled "Advancing instance segmentation and WBC classification in peripheral blood smear through domain adaptation: A study on PBC and the novel RV-PBS datasets" published on Elsevier's Expert Systems With Applications (ESWA) journal.
The script is in the Aniket_Mask_RCNN folder. Use dvc pull to get the h5 file. Put the script and the h5 file in the same folder (containing the Mask RCNN library folder). Put all the images in a directory and put the directory where the script is located. Then run mask_rcnn4_generate_json.py directory_where_the_images_are. Make sure the directory only contains images.
The output will be in directory_where_the_images_are/results.json in the following format -
How to run
The script is in the
Aniket_Mask_RCNN
folder. Usedvc pull
to get the h5 file. Put the script and the h5 file in the same folder (containing the Mask RCNN library folder). Put all the images in a directory and put the directory where the script is located. Then runmask_rcnn4_generate_json.py directory_where_the_images_are
. Make sure the directory only contains images.The output will be in
directory_where_the_images_are/results.json
in the following format -