Cell Segmentation (Fluorescent Images)

Download data and pretrained models weights

Download the processed data

IMPORTANT: Note that the raw data is from TissueNet, this processed data is for demo purpose ONLY!

Download data/example_tissuenet.zip from the Drive and put it in the data folder. Then unzip it.

cd data
unzip example_tissuenet.zip
cd ..

Download COCO pretrained models weights (optional)

Download models/maskdino_swinl_50ep_300q_hid2048_3sd1_instance_maskenhanced_mask52.3ap_box59.0ap.pth from the Drive and put it in the cellotype/models folder.

Train model

Note: If you want to train the model using multi-channel images with a number of channels other than 3, you can modify the cfg.MODEL.IN_CHANS setting in the train_tissuenet.py script.

python train_tissuenet.py --num-gpus 4

The parameters are optimized for 4*A100 (40GB) environment, if your machine does not have enough GPU memory, you can reduce the batch size by changing the IMS_PER_BATCH in configs/Base-COCO-InstanceSegmentation.yaml.

Test model and visualize results

For reference, our trained weights models/tissuenet_model_0019999.pth can be downloaded from the Drive folder.

python test_tissuenet.py --num-gpus 1

The example prediction saved in the output/tissuenet folder.