ktrain/vision/predictor.py
def predict_folder(self, folder, return_proba=False):
        """
        Predicts the classes of all images in a folder.
        If return_proba is True, returns probabilities of each class.
        
        """
        if not os.path.isdir(folder): raise ValueError('folder must be valid directory')
        (generator, steps) = self.preproc.preprocess(folder)
        result = self.predict_generator(generator, steps=steps, return_proba=return_proba)
        if len(result) != len(generator.filenames): 
            raise Exception('number of results does not equal number of filenames')
        return list(zip(generator.filenames, result))

        Predicts the classes of all images in a folder.
        If return_proba is True, returns probabilities of each class.
        
        
Predicts the classes of all images in a folder.
If return_proba is True, returns probabilities of each class.
Predicts the classes of all images in a folder . If return_proba is True returns probabilities of each class .
def predict_folder(self, folder, return_proba=False):
        if not os.path.isdir(folder): raise ValueError('folder must be valid directory')
        (generator, steps) = self.preproc.preprocess(folder)
        result = self.predict_generator(generator, steps=steps, return_proba=return_proba)
        if len(result) != len(generator.filenames): 
            raise Exception('number of results does not equal number of filenames')
        return list(zip(generator.filenames, result))
def predict_folder ( self , folder , return_proba = False ) : if not os . path . isdir ( folder ) : raise ValueError ( 'folder must be valid directory' ) ( generator , steps ) = self . preproc . preprocess ( folder ) result = self . predict_generator ( generator , steps = steps , return_proba = return_proba ) if len ( result ) != len ( generator . filenames ) : raise Exception ( 'number of results does not equal number of filenames' ) return list ( zip ( generator . filenames , result ) )
Predicts the classes of all images in a folder.
Predicts the classes of all images in a folder .
"""
        Predicts the classes of all images in a folder.
        If return_proba is True, returns probabilities of each class.
        
        """
self
folder
return_proba