pcnaDeep
pcnaDeep.predictor
pcnaDeep.refiner
pcnaDeep.resolver
pcnaDeep.tracker
pcnaDeep.evaluate
- class pcnaDeep.evaluate.pcna_ctcEvaluator(root, dt_id, digit_num=3, t_base=0, path_ctc_software=None, init_dir=True)[source]
Bases:
object- __init__(root, dt_id, digit_num=3, t_base=0, path_ctc_software=None, init_dir=True)[source]
Evaluation of tracking output
- set_evSoft(path_ctc_software)[source]
Set evaluation software path
- Parameters:
path_ctc_software (str) – path to CTC evaluation software
- generate_raw(stack)[source]
Save raw images by slice
- Parameters:
stack (numpy.ndarray) – raw image
- generate_ctc(mask, track, mode='RES')[source]
Generate standard format for Cell Tracking Challenge Evaluation, for RES or GT.
- Parameters:
mask (numpy.ndarray) – mask output, no need to have cell cycle labeled
track (pandas.DataFrame) – tracked object table, can have gaped tracks
mode (str) – either “RES” or “GT”.