ktrain/vision/predictor.py
def predict_filename(self, img_path, return_proba=False):
        """
        Predicts class from filepath to single image file.
        If return_proba is True, returns probabilities of each class.
        """
        if not os.path.isfile(img_path): raise ValueError('img_path must be valid file')
        (generator, steps) = self.preproc.preprocess(img_path)
        return self.predict_generator(generator, steps=steps, return_proba=return_proba)

        Predicts class from filepath to single image file.
        If return_proba is True, returns probabilities of each class.
        
Predicts class from filepath to single image file.
If return_proba is True, returns probabilities of each class.
Predicts class from filepath to single image file . If return_proba is True returns probabilities of each class .
def predict_filename(self, img_path, return_proba=False):
        if not os.path.isfile(img_path): raise ValueError('img_path must be valid file')
        (generator, steps) = self.preproc.preprocess(img_path)
        return self.predict_generator(generator, steps=steps, return_proba=return_proba)
def predict_filename ( self , img_path , return_proba = False ) : if not os . path . isfile ( img_path ) : raise ValueError ( 'img_path must be valid file' ) ( generator , steps ) = self . preproc . preprocess ( img_path ) return self . predict_generator ( generator , steps = steps , return_proba = return_proba )
Predicts class from filepath to single image file.
Predicts class from filepath to single image file .
"""
        Predicts class from filepath to single image file.
        If return_proba is True, returns probabilities of each class.
        """
self
img_path
return_proba