feature_extractor.py 文件源码

def _preproc_image_batch(self, batch_size, num_threads=1):
        '''
        This function is only used for queue input pipeline. It reads a filename
        from the filename queue, decodes the image, pushes it through a pre-processing
        function and then uses tf.train.batch to generate batches.

        :param batch_size: int, batch size
        :param num_threads: int, number of input threads (default=1)
        :return: tf.Tensor, batch of pre-processed input images
        '''

        if ("resnet_v2" in self._network_name) and (self._preproc_func_name is None):
            raise ValueError("When using ResNet, please perform the pre-processing "
                            "function manually. See here for details: " 
                            "https://github.com/tensorflow/models/tree/master/slim")

        # Read image file from disk and decode JPEG
        reader = tf.WholeFileReader()
        image_filename, image_raw = reader.read(self._filename_queue)
        image = tf.image.decode_jpeg(image_raw, channels=3)
        # Image preprocessing
        preproc_func_name = self._network_name if self._preproc_func_name is None else self._preproc_func_name
        image_preproc_fn = preprocessing_factory.get_preprocessing(preproc_func_name, is_training=False)
        image_preproc = image_preproc_fn(image, self.image_size, self.image_size)
        # Read a batch of preprocessing images from queue
        image_batch = tf.train.batch(
            [image_preproc, image_filename], batch_size, num_threads=num_threads,
            allow_smaller_final_batch=True)
        return image_batch