// Copyright 2016 Google LLC

//

// Licensed under the Apache License, Version 2.0 (the "License");

// you may not use this file except in compliance with the License.

// You may obtain a copy of the License at

//

// http://www.apache.org/licenses/LICENSE-2.0

//

// Unless required by applicable law or agreed to in writing, software

// distributed under the License is distributed on an "AS IS" BASIS,

// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

// See the License for the specific language governing permissions and

// limitations under the License.

'use strict';

// [START vision_face_detection_tutorial_imports]

// By default, the client will authenticate using the service account file

// specified by the GOOGLE_APPLICATION_CREDENTIALS environment variable and use

// the project specified by the GCLOUD_PROJECT environment variable. See

// https://googlecloudplatform.github.io/gcloud-node/#/docs/google-cloud/latest/guides/authentication

const vision = require('@google-cloud/vision');

// [END vision_face_detection_tutorial_imports]

// [START vision_face_detection_tutorial_client]

// Creates a client

const client = new vision.ImageAnnotatorClient();

const fs = require('fs');

// [END vision_face_detection_tutorial_client]

/**

* Uses the Vision API to detect faces in the given file.

*/

// [START vision_face_detection_tutorial_send_request]

async function detectFaces(inputFile) {

// Make a call to the Vision API to detect the faces

const request = {image: {source: {filename: inputFile}}};

const results = await client.faceDetection(request);

const faces = results[0].faceAnnotations;

const numFaces = faces.length;

console.log(`Found ${numFaces} face${numFaces === 1 ? '' : 's'}.`);

return faces;

}

// [END vision_face_detection_tutorial_send_request]

/**

* Draws a polygon around the faces, then saves to outputFile.

*/

// [START vision_face_detection_tutorial_process_response]

async function highlightFaces(inputFile, faces, outputFile, PImage) {

// Open the original image

const stream = fs.createReadStream(inputFile);

let promise;

if (inputFile.match(/\.jpg$/)) {

promise = PImage.decodeJPEGFromStream(stream);

} else if (inputFile.match(/\.png$/)) {

promise = PImage.decodePNGFromStream(stream);

} else {

throw new Error(`Unknown filename extension ${inputFile}`);

}

const img = await promise;

const context = img.getContext('2d');

context.drawImage(img, 0, 0, img.width, img.height, 0, 0);

// Now draw boxes around all the faces

context.strokeStyle = 'rgba(0,255,0,0.8)';

context.lineWidth = '5';

faces.forEach(face => {

context.beginPath();

let origX = 0;

let origY = 0;

face.boundingPoly.vertices.forEach((bounds, i) => {

if (i === 0) {

origX = bounds.x;

origY = bounds.y;

context.moveTo(bounds.x, bounds.y);

} else {

context.lineTo(bounds.x, bounds.y);

}

});

context.lineTo(origX, origY);

context.stroke();

});

// Write the result to a file

console.log(`Writing to file ${outputFile}`);

const writeStream = fs.createWriteStream(outputFile);

await PImage.encodePNGToStream(img, writeStream);

}

// [END vision_face_detection_tutorial_process_response]

// Run the example

// [START vision_face_detection_tutorial_run_application]

async function main(inputFile, outputFile) {

const PImage = require('pureimage');

outputFile = outputFile || 'out.png';

const faces = await detectFaces(inputFile);

console.log('Highlighting...');

await highlightFaces(inputFile, faces, outputFile, PImage);

console.log('Finished!');

}

// [END vision_face_detection_tutorial_run_application]

const args = process.argv.slice(2);

main(...args).catch(console.error);