cellclass test

Evaluate a trained model against a dataset.

cellclass test [OPTIONS] DATASET.NPZ

Full --help output

Usage: cellclass test [OPTIONS] dataset.npz

  Evaluate a trained model against a dataset.

Options:
  --size INTEGER                  Number of images to use.
  --data-seed INTEGER             [default: 42]
  -d, --device TEXT               [default: cuda]
  --model [densenet121|densenet161|densenet169|densenet201|squeezenet1_0|shufflenet2x1_0|shufflenet2x1_5|shufflenet2x2_0|efficientnetb3|efficientnetb4|efficientnetb3s|efficientnetb4s|resenext50_32x4d|alexnet|alexnet_att|googlenet|googlenet_att|simplegooglenet|simplegooglenet_att|simplegooglenet_ch_att|simplegooglenet_ch_sp_att]
  -n, --name FILE                 Training checkpoint name.
  -w, --weights FILE              Model weights.
  -s, --script FILE               Model script.
  --testing-size FLOAT            [default: 0.2]
  --batch-size INTEGER            [default: 128]
  --num-workers INTEGER           [default: 0]
  --log-level INTEGER             [default: 20]
  --pin-memory / --no-pin-memory
  --reorder INTEGER               Reorder class labels.
  --plot-matrix / --no-plot-matrix
  --matrix-file TEXT              Save the confusion matrix image.
  --matrix-csv TEXT               Save the confusion matrix CSV.
  --help                          Show this message and exit.

Arguments

DATASET.NPZ: FILE

Required.

Options

--size: INTEGER = 0

Number of images to use.

--data-seed: INTEGER = 42

 

-d, --device: TEXT = cuda

 

--model: CHOICE = densenet121

 

-n, --name: FILE

Training checkpoint name.

-w, --weights: FILE

Model weights.

-s, --script: FILE

Model script.

--testing-size: FLOAT = 0.2

 

--batch-size: INTEGER = 128

 

--num-workers: INTEGER = 0

 

--log-level: INTEGER = 20

 

--pin-memory, --no-pin-memory

 

--reorder: INTEGER

Reorder class labels.

--plot-matrix, --no-plot-matrix

 

--matrix-file: TEXT

Save the confusion matrix image.

--matrix-csv: TEXT

Save the confusion matrix CSV.