Returns a path to an image for a label at the given index. Args: image_lists: Dictionary of training images for each label. label_name: Lab

Retrieves or calculates bottleneck values for an image. If a cached version of the bottleneck data exists on-disk, return that, otherwise calcula

Retrieves bottleneck values for cached images. If no distortions are being applied, this function can retrieve the cached bottleneck values direc

Makes sure the folder exists on disk. Args: dir_name: Path string to the folder we want to create.

Iterate over files converting them to a single line then write the set of files to a single output file

Runs inference on an image to extract the 'bottleneck' summary layer. Args: sess: Current active TensorFlow Session. image_data: String of

Attach a lot of summaries to a Tensor (for TensorBoard visualization).

Inserts the operations we need to evaluate the accuracy of our results. Args: result_tensor: The new final node that produces results. grou

Adds a new softmax and fully-connected layer for training. We need to retrain the top layer to identify our new classes, so this function adds th

Creates the operations to apply the specified distortions. During training it can help to improve the results if we run the images through simple

Ensures all the training, testing, and validation bottlenecks are cached. Because we're likely to read the same image multiple times (if there are

Builds a list of training images from the file system. Analyzes the sub folders in the image directory, splits them into stable training, testing

Creates a graph from saved GraphDef file and returns a Graph object. Returns: Graph holding the trained Inception network, and various tensors

Returns a path to a bottleneck file for a label at the given index. Args: image_lists: Dictionary of training images for each label. label_

Retrieves bottleneck values for training images, after distortions. If we're training with distortions like crops, scales, or flips, we have to r

Driver program for a spam filter using Spark and MLLib

Driver program for a spam filter using Spark and MLLib

Download and extract model tar file. If the pretrained model we're using doesn't already exist, this function downloads it from the TensorFlow.or

This produces a dataset 5 times bigger than the original one, by moving the 8x8 images in X around by 1px to left, right, down, up

Whether any distortions are enabled, from the input flags. Args: flip_left_right: Boolean whether to randomly mirror images horizontally. r

Reads list of floats from a given file. Args: file_path: Path to a file where list of floats was stored. Returns: Array of bottleneck val

Writes a given list of floats to a binary file. Args: list_of_floats: List of floats we want to write to a file. file_path: Path to a file