Cellpose model for Digital Phase Contrast images

<strong>Name: </strong>Cellpose model for Digital Phase Contrast images <strong>Data type: </strong>Cellpose model, trained via transfer learning from ‘cyto’ model. <strong>Training Dataset: </strong>Light microscopy (Digital Phase Contrast) and Manual annotations (<em>10.5281/zenodo.5996883</em>) <strong>Training Procedure: </strong>Model was trained using a Cellpose version 0.6.5 with GPU support (NVIDIA GeForce RTX 2080) using default settings as per the Cellpose documentation python -m cellpose --train --dir <em>TRAINING/DATASET/PATH/</em>train --test_dir <em>TRAINING/DATASET/PATH/</em>test --pretrained_model cyto --chan 0 --chan2 0 The model file (MODEL NAME) in this repository is the result of this training. <strong>Prediction Procedure: </strong>Using this model, a label image can be obtained from new unseen images in a given folder with python -m cellpose --dir <em>NEW/DATASET/PATH</em> --pretrained_model <em>FULL_MODEL_PATH</em> --chan 0 --chan2 0 --save_tif --no_npy