Daniel Franco-Barranco
Daniel Franco-Barranco
The idea is to have more options apart from ``DATA.TRAIN.MINIMUM_FOREGROUND_PER``. Intensity based measurements seem to be useful for users, e.g. mean, min/max, std (see [forum.sc thread](https://forum.image.sc/t/neuron-cell-detection-biapy/94198/10)).
[imgaug ](https://github.com/aleju/imgaug) project is not being updated. We should implement the transformations used through imgaug to remove its dependecy completely. The transformations are these: - [x] #63 - [x] Random...
Add the option to retrain BMZ models, not just to do inference. There are two options we can do: - Use Torchscript directly loaded models and work with that (possible...
We need to implement `after_merge_patches_by_chunks_proccess_patch` function ([here](https://github.com/danifranco/BiaPy/blob/97603fbf4b94a22112c6504105fd13cb06d9a954/engine/instance_seg.py#L373)). Instance creation needs to be done by patches and then merge. Example in [cellpose code](https://github.com/MouseLand/cellpose/blob/main/cellpose/contrib/distributed_segmentation.py).
Add support for reading `.nii.gz` data. Something was done in [load_ct_data_from_dir](https://github.com/danifranco/BiaPy/blob/befef89d03043489b80dc3b2f4da7d0645248836/utils/util.py#L980) function. Need to incorporate it to `load_data_from_dir` and `load_3d_images_from_dir` function for reading 2D and 3D images respectively. We can...
We need to rethink how the final prediction is reconstructed using inference by chunks, as right now we are using so much disk (and time) with the mask that needs...
It could be nice to create a CSV file with the calculated metrics for each test sample. Also, at this point I think we need to unify the names of...
Now the detection masks are not created by chunks as it is done in the instance segmentation workflow. The whole image is loaded in memory and then dumped into the...
Now the dataset is replicated for each worker that is spawned. We should split the dataset as it is done in "by chunks" inference in order to save memory when...
Useful for finetunning just a part of the model.