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Users should be able to add their own annotations, in the same format as the dataset, by using the Create annotation frontend and a folder. Basic support should include pngseq. The required code changes are:
backend/app/app/api/api_v1/endpoints/utils.py:train_unet2d pass annotation filetype to celery task with new param annotation_filetype
frontend
regenerate the code from the backend API as shown in the documentation. This should add the correct file types in the annotation form.
gpu_worker/app/worker.py:train_unet2d
add new param annotation_filetype
app/worker.py:train_unet2d Skip step Convert JSON annotations to .pngs if filetype is not json.
dash_frontend
disable the edit annotation button if the type is not json.
Possible issues:
The string representing location of the annotation will change from only a file annotations.json to either a file or a folder. This can break unknown stuff that depended on this assumption e.g. the annotation tools from the dash_frontend viewer or the folder creation in the gpu_worker.
The text was updated successfully, but these errors were encountered:
Users should be able to add their own annotations, in the same format as the dataset, by using the
Create annotation
frontend and a folder. Basic support should includepngseq
. The required code changes are:backend
schemas/annotation.py:AnnoationFileType
: addpngseq = "pngseq"
backend/app/app/api/api_v1/endpoints/utils.py:train_unet2d
pass annotation filetype to celery task with new paramannotation_filetype
frontend
gpu_worker/app/worker.py:train_unet2d
annotation_filetype
app/worker.py:train_unet2d
Skip stepConvert JSON annotations to .pngs
if filetype is not json.dash_frontend
Possible issues:
annotations.json
to either a file or a folder. This can break unknown stuff that depended on this assumption e.g. the annotation tools from the dash_frontend viewer or the folder creation in the gpu_worker.The text was updated successfully, but these errors were encountered: