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+Using the batch execution tool
+==============================
+
+The batch execution tool (`tflite_accuracy`) can be used to run experiments
+where execution time and accuracy are to be measured on a test set.
+`tflite_accuracy` reads a neural network model from a file and a series of
+input images from a directory, runs each image through the network,
+and collect statistics, such as execution time and accuracy.
+
+In order to run this tool, you'll need:
+
+* a model in `.tflite` format;
+* a set of preprocessed input images in binary format, properly named
+(see below).
+
+`tflite_accuracy` expects all the input images to be located in the same directory
+in the file system. Each image file is the binary dump of the network's
+input tensor. So, if the network's input tensor is a `float32` tensor of 
+format (1, 224, 224, 3) containing 1 image of height 224, width 224, and
+3 channels, each image file is expected to be a series of 224 * 224 * 3 
+`float32` values.
+
+`tflite_accuracy` does **not** perform any preprocessing on the input tensor
+(e.g., subtraction of mean or division by standard deviation). Each image 
+file is treated as the final value of the input tensor, so all the
+necessary preprocessing should be done prior to invoking the tool.
+
+In order to calculate accuracy on the image set, `tflite_accuracy` needs to know
+the correct label corresponding to each image. This information is
+extracted from the file's name: the first four characters in the name are
+assumed to be the numerical code of the image's class. So, a file named
+`0123_0123456789.bin` is assumed to represent an image belonging to class
+`123`. The remainder of the name (`0123456789` in the example) is assumed 
+to be an identifier of the image itself.
+
+The width and height each image can be informed via the command line
+argument `--imgsize`, whose default value is 224.
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