class_docstr: ```
  predicts image classes
  ```
class_docstr_tok: ["``","`","predicts","image","classes","``","`"]
docstr: ```
  Predicts class from filepath to single image file.
  If return_proba is True, returns probabilities of each class.
  ```
docstr_tok: ["``","`","Predicts","class","from","filepath","to","single","image","file",".","If","return_proba","is","True",",","returns","probabilities","of","each","class",".","``","`"]
code: def predict_filename(self, img_path, return_proba=False, verbose=0):
      """
      ```
      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, batch_size=self.batch_size
      )
      return self.predict_generator(
          generator,
          steps=steps,
          return_proba=return_proba,
          verbose=verbose,
      )
  
file_path: ktrain/ktrain/vision/predictor.py
imports: from ..None import utils
  from ..imports import *
  from ..predictor import Predictor
  from .preprocessor import ImagePreprocessor
label_desc: Use image node_id 5 for calling the ImagePredictor obj's underlying member method code with example usage: obj.predict_filename(img_path, return_proba, verbose) and returns: self