Comments (7)
According to this SO post, you should be able to pass verbose=0
in the args to model.predict()
, which this library passes via the predict_args
arg of classify()
, e.g.
predict.classify(classify(model, input_paths, predict_args={verbose: 0})
If that works for you, please confirm and close this issue!
from nsfw_model.
Uh...
TypeError: classify() got an unexpected keyword argument 'predict_args'
My code:
result = predict.classify(model_nsfw, file_path, predict_args={verbose: 0})
And "verbose" is not defined.
from nsfw_model.
Idk... but after reading code of predict.py, I don't understand how these arguments are passed to keras, and why in your example, after predict.classify, there is another classify in parentheses
According to this SO post, you should be able to pass
verbose=0
in the args tomodel.predict()
, which this library passes via thepredict_args
arg ofclassify()
, e.g.predict.classify(classify(model, input_paths, predict_args={verbose: 0})If that works for you, please confirm and close this issue!
It seems that the classify() function does not accept a predict_args parameter ๐ฃ
from nsfw_model.
why in your example, after predict.classify, there is another classify in parentheses
Probably a copy paste error. Take out the second function call
from nsfw_model.
predict.classify(model_nsfw, file_path, predict_args={verbose: 0})
This right?
from nsfw_model.
Looks to be, I can't try it right now
from nsfw_model.
Waiting for dev's answer..
from nsfw_model.
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