Interactively generate/edit segmentation labels using napari
For more details on how to generate and edit annotations please refer to: https://napari.org/tutorials/fundamentals/labels.html
The current implementation has been developed in Python 3.
In order to avoid any changes to the local packages, install in a virtual environment (optional).
$ conda create --name annotate_napari python $ conda activate annotate_napari To clone the repository run the following from the terminal.
$ git clone https://github.com/SaradhaVenkatachalapathy/annotate_images.git Then install requirements and run the setup from the repository directory
$ pip install -r requirements.txt $ python setup.py install To manually generate annotations, run the following.
$ python annotate_images.py --datadir <path/to/image/directory> --savedir <path/to/output/directory> --large_image <yes/no> --anno_img_depth <depth_of_annotated_image --downsize_factor <scaling_factor_for_large_images> To correct existing annotations, first perform segmentation(optional) and correct segmented labels.
$ python perform_simple_segmentation.py --datadir <path/to/image/directory> --savedir <path/to/output/directory> $ python correct_annotation.py --datadir <path/to/image/directory> --annodir <path/to/annotated/image/directory> --userannodir <path/to/output/directory> --large_image <yes/no> --anno_img_depth <depth_of_annotated_image --downsize_factor <scaling_factor_for_large_images> TO DO: add functions for model based instace segmentation