parsing_rcnn_model.py
def find_last(self):
        """Finds the last checkpoint file of the last trained model in the
        model directory.
        Returns:
            log_dir: The directory where events and weights are saved
            checkpoint_path: the path to the last checkpoint file
        """
        # Get directory names. Each directory corresponds to a model
        dir_names = next(os.walk(self.model_dir))[1]
        key = self.config.NAME.lower()
        dir_names = filter(lambda f: f.startswith(key), dir_names)
        dir_names = sorted(dir_names)
        if not dir_names:
            return None, None
        # Pick last directory
        dir_name = os.path.join(self.model_dir, dir_names[-1])
        # Find the last checkpoint
        checkpoints = next(os.walk(dir_name))[2]
        checkpoints = filter(lambda f: f.startswith("parsing_rcnn"), checkpoints)
        checkpoints = sorted(checkpoints)
        if not checkpoints:
            return dir_name, None
        checkpoint = os.path.join(dir_name, checkpoints[-1])
        return dir_name, checkpoint
Finds the last checkpoint file of the last trained model in the
        model directory.
        Returns:
            log_dir: The directory where events and weights are saved
            checkpoint_path: the path to the last checkpoint file
        
Finds the last checkpoint file of the last trained model in the
model directory.
Finds the last checkpoint file of the last trained model in the model directory .
def find_last(self):
        dir_names = next(os.walk(self.model_dir))[1]
        key = self.config.NAME.lower()
        dir_names = filter(lambda f: f.startswith(key), dir_names)
        dir_names = sorted(dir_names)
        if not dir_names:
            return None, None
        dir_name = os.path.join(self.model_dir, dir_names[-1])
        checkpoints = next(os.walk(dir_name))[2]
        checkpoints = filter(lambda f: f.startswith("parsing_rcnn"), checkpoints)
        checkpoints = sorted(checkpoints)
        if not checkpoints:
            return dir_name, None
        checkpoint = os.path.join(dir_name, checkpoints[-1])
        return dir_name, checkpoint
def find_last ( self ) : dir_names = next ( os . walk ( self . model_dir ) ) [ 1 ] key = self . config . NAME . lower ( ) dir_names = filter ( lambda f : f . startswith ( key ) , dir_names ) dir_names = sorted ( dir_names ) if not dir_names : return None , None dir_name = os . path . join ( self . model_dir , dir_names [ - 1 ] ) checkpoints = next ( os . walk ( dir_name ) ) [ 2 ] checkpoints = filter ( lambda f : f . startswith ( "parsing_rcnn" ) , checkpoints ) checkpoints = sorted ( checkpoints ) if not checkpoints : return dir_name , None checkpoint = os . path . join ( dir_name , checkpoints [ - 1 ] ) return dir_name , checkpoint
Finds the last checkpoint file of the last trained model in the
model directory.
Finds the last checkpoint file of the last trained model in the model directory .
"""Finds the last checkpoint file of the last trained model in the
        model directory.
        Returns:
            log_dir: The directory where events and weights are saved
            checkpoint_path: the path to the last checkpoint file
        """ # Get directory names. Each directory corresponds to a model # Pick last directory # Find the last checkpoint
The directory where events and weights are saved
checkpoint_path: the path to the last checkpoint file
The directory where events and weights are saved checkpoint_path : the path to the last checkpoint file
log_dir
self