Generates predictions for the input samples from a data generator.

The generator should return the same kind of data as accepted by predict_on_batch().

predict_generator(object, generator, steps, max_queue_size = 10,
  workers = 1, verbose = 0)

Arguments

object	Keras model object
generator	Generator yielding batches of input samples.
steps	Total number of steps (batches of samples) to yield from generator before stopping.
max_queue_size	Maximum size for the generator queue. If unspecified, max_queue_size will default to 10.
workers	Maximum number of threads to use for parallel processing. Note that parallel processing will only be performed for native Keras generators (e.g. flow_images_from_directory()) as R based generators must run on the main thread.
verbose	verbosity mode, 0 or 1.

Value

Numpy array(s) of predictions.

Raises

ValueError: In case the generator yields data in an invalid format.

See also

Other model functions: compile.keras.engine.training.Model, evaluate.keras.engine.training.Model, evaluate_generator, fit.keras.engine.training.Model, fit_generator, get_config, get_layer, keras_model_sequential, keras_model, multi_gpu_model, pop_layer, predict.keras.engine.training.Model, predict_on_batch, predict_proba, summary.keras.engine.training.Model, train_on_batch