An Inception Example in Owl

readme.md

Inception_example

An example showing how to use the InceptionV3 neural network (defined in this gist) to do image classification on Owl, with only a few lines of code. Please refer to this Gist for more details. Enjoy!

inception_example.ml

#!/usr/bin/env owl
open Owl

(* Import InceptionV3 Library *)
#zoo "9428a62a31dbea75511882ab8218076f"

let img = "/path/to/you/image.png";;
let _ = 
  (* Path to your image; here we use the "panda.png" 
   * in this gist as example.
   *)
  let img = Owl_zoo_path.extend_zoo_path "panda.png" in
  (* Image classification *)
  let labels = InceptionV3.infer img in
  (* Get top-5 human-readable output in the format of JSON string, or...*) 
  let top = 5 in 
  let labels_json   = InceptionV3.to_json ~top labels in
  (* an array of tuples. Each tuple contains a category (string) and 
   * its inferred probability (float), ranging from 1 to 100.
   *)
  let labels_tuples = InceptionV3.to_tuples labels in

  (* (Optional) Pretty-print the results *)
  Printf.printf "\nTop %d Predictions:\n" top;
  Array.iteri (fun i x -> 
    let cls, prop = x in 
    Printf.printf "Prediction #%d (%.2f%%) : %s\n" i (prop *. 100.) cls;
  ) labels_tuples

panda.png