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Read Tiff Images
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Read Non Tiff Images
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Write Data Transformers and Loaders
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Write functional model plus scripts
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Modify model weights/layers
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Read stacked tiff images/videos
cellseg
is a PyTorch (torch
) based deep learning package aimed at multiclass cell segmentation.
pip install cellseg
Or if you want to build from source
git clone git@github.com:Nelson-Gon/cellseg.git
cd cellseg
python setup.py install
View images
python -m cellseg -d data/train -t "image" -n 4 -s 512
To get help
python -m cellseg --help
#usage: __main__.py [-h] -d IMAGE_DIRECTORY -s IMAGE_SIZE -t TARGET -n NUMBER
#
#optional arguments:
# -h, --help show this help message and exit
# -d IMAGE_DIRECTORY, --image-directory IMAGE_DIRECTORY
# Path to image directory containing images and
# masks/labels
# -s IMAGE_SIZE, --image-size IMAGE_SIZE
# Size of images
# -t TARGET, --target TARGET
# Target images to show
# -n NUMBER, --number NUMBER
# Number of images to show
Importing relevant modules
from cellseg.data import DataProcessor
from cellseg.model import CellNet
from cellseg.utils import DataProcessor, show_images
Creating a a model object
my_model = CellNet()
Load training data
train_data = DataProcessor(image_dir="data/train/images", label_dir="data/train/images", image_suffix="tif")
View loaded images or masks
show_images(train_data, number = 8, target="image")
Training