Predicting film genres from their posters with Tensorflow.js
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"use strict";
import path from 'path';
import CliParser from 'applause-cli';
import train from './subcommands/train/train.mjs';
import predict from './subcommands/predict/predict.mjs';
const __dirname = import.meta.url.slice(7, import.meta.url.lastIndexOf("/"));
export default async function () {
let cli = new CliParser(path.resolve(__dirname, "../package.json"));
cli.subcommand("train", "Trains a new AI")
.argument("input", "The input directory containing the training data", null, "string")
.argument("output", "Path to the output directory to save the trained AI to");
cli.subcommand("predict", "Predicts the genres of the specified image")
.argument("input", "Path to the input image")
.argument("ai-model", "Path to the saved AI model to load");
let settings = cli.parse(process.argv.slice(2));
if(cli.current_subcommand == null) {
cli.write_help_exit();
return;
}
switch(cli.current_subcommand) {
case "train":
await train(settings);
break;
case "predict":
await predict(settings);
break;
default:
console.error(`Error: Unknown subcommand '${cli.current_subcommand}' (try --help for usage information)`);
process.exit(1);
break;
}
}