simple unet with NeurIPS'19 topoloss
Commands:
- Make sure to populate
train.json
andtest.json
with appropriate hyprerparameters
Train:
CUDA_VISIBLE_DEVICES=3 python3 main.py --params ./datalists/DRIVE/train.json
- Ensure
crop_size
intrain.json
is divisible by 16
Test/Inference:
CUDA_VISIBLE_DEVICES=4 python3 main.py --params ./datalists/DRIVE/test.json
Compute Evaluation Metrics (Quantitative Results):
python3 compute-eval-metrics.py
Dataset properties:
GT: Foreground should be 255 ; Background should be 0
- First do pretrain (1000-2000 epochs) by setting
"topo_weight": 0
intrain.json
- Then, load the best model from pretrain and train using topoloss by setting
topo_weight
to a non-zero value. Change theoutput_folder
andcheckpoint_restore
intrain.json
too