ktrain/vision/predictor.py
def predict(self, data, return_proba=False):
        """
        Predicts class from image in array format.
        If return_proba is True, returns probabilities of each class.
        """
        if not isinstance(data, np.ndarray):
            raise ValueError('data must be numpy.ndarray')
        (generator, steps) = self.preproc.preprocess(data)
        return self.predict_generator(generator, steps=steps, return_proba=return_proba)

        Predicts class from image in array format.
        If return_proba is True, returns probabilities of each class.
        
Predicts class from image in array format.
If return_proba is True, returns probabilities of each class.
Predicts class from image in array format . If return_proba is True returns probabilities of each class .
def predict(self, data, return_proba=False):
        if not isinstance(data, np.ndarray):
            raise ValueError('data must be numpy.ndarray')
        (generator, steps) = self.preproc.preprocess(data)
        return self.predict_generator(generator, steps=steps, return_proba=return_proba)
def predict ( self , data , return_proba = False ) : if not isinstance ( data , np . ndarray ) : raise ValueError ( 'data must be numpy.ndarray' ) ( generator , steps ) = self . preproc . preprocess ( data ) return self . predict_generator ( generator , steps = steps , return_proba = return_proba )
Predicts class from image in array format.
Predicts class from image in array format .
"""
        Predicts class from image in array format.
        If return_proba is True, returns probabilities of each class.
        """
self
data
return_proba