CAREamist API#
The CAREamist API is the recommended way to use CAREamics, it is a two stage process, in which users first define a configuration and then use a the CAREamist to run their training and prediction. The applications section provides examples.
Basic CAREamics usage
import numpy as np
from careamics import CAREamist
from careamics.config import create_n2v_configuration
# create a configuration
config = create_n2v_configuration(
experiment_name="n2v_2D",
data_type="array",
axes="YX",
patch_size=[64, 64],
batch_size=1,
num_epochs=1, # (1)!
)
# instantiate a careamist
careamist = CAREamist(config)
# train the model
train_data = np.random.randint(0, 255, (256, 256)).astype(np.float32) # (2)!
careamist.train(train_source=train_data)
# once trained, predict
pred_data = np.random.randint(0, 255, (128, 128)).astype(np.float32)
predction = careamist.predict(source=pred_data)
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Obviously, one should choose a more realistic number of epochs for training.
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One should use real data for training!