├── .firebaserc
├── .gitignore
├── CONTRIBUTING.md
├── LICENSE
├── README.md
├── firebase.json
├── firestore.indexes.json
├── firestore.rules
├── functions
├── index.js
└── package.json
├── public
├── index.html
├── main.css
└── main.js
└── screenshots
├── cloud-demo.gif
├── firebase-cli.png
├── firestore.png
└── starter-demo-page.png
/.firebaserc:
--------------------------------------------------------------------------------
1 | {
2 | "projects": {
3 | "default": "YOUR_FIREBASE_PROJECT"
4 | }
5 | }
6 |
--------------------------------------------------------------------------------
/.gitignore:
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1 | *-lock.json
2 | *node_modules/
3 | .DS_Store
--------------------------------------------------------------------------------
/CONTRIBUTING.md:
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1 | # How to Contribute
2 |
3 | We'd love to accept your patches and contributions to this project. There are
4 | just a few small guidelines you need to follow.
5 |
6 | ## Contributor License Agreement
7 |
8 | Contributions to this project must be accompanied by a Contributor License
9 | Agreement. You (or your employer) retain the copyright to your contribution;
10 | this simply gives us permission to use and redistribute your contributions as
11 | part of the project. Head over to to see
12 | your current agreements on file or to sign a new one.
13 |
14 | You generally only need to submit a CLA once, so if you've already submitted one
15 | (even if it was for a different project), you probably don't need to do it
16 | again.
17 |
18 | ## Code reviews
19 |
20 | All submissions, including submissions by project members, require review. We
21 | use GitHub pull requests for this purpose. Consult
22 | [GitHub Help](https://help.github.com/articles/about-pull-requests/) for more
23 | information on using pull requests.
24 |
25 | ## Community Guidelines
26 |
27 | This project follows
28 | [Google's Open Source Community Guidelines](https://opensource.google.com/conduct/).
29 |
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
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/README.md:
--------------------------------------------------------------------------------
1 | **This is not an official Google product**
2 |
3 | # Demo: querying a custom AutoML model from a web app
4 |
5 | This demo shows how to call a custom AutoML model from a web app using the [AutoML API](https://cloud.google.com/vision/automl/docs/reference/rest/). It queries an [AutoML Vision](https://cloud.google.com/vision/automl/docs/) model, but the code can easily be adapted for [AutoML Natural Language](https://cloud.google.com/natural-language/automl/docs/) since the API is the same for both. The model I'm using for this predicts the type of cloud in an image:
6 |
7 | 
8 |
9 | *For more details on this specific vision model, check out the AutoML section of my [Cloud Next '18 talk](https://youtu.be/QU7_eU8HzAQ?t=16m12s).*
10 |
11 | ## Pre-requisites
12 |
13 | * You've built and trained a model with [Cloud AutoML](http://cloud.google.com/automl).
14 | * You've enabled the AutoML API in your Cloud project
15 | * You've created a project in the Firebase console and associated it with the same project where you trained your AutoML model. Using the [Firebase CLI](https://firebase.google.com/docs/cli/), make sure to initialize your project with Firestore, Functions, Hosting, and Storage:
16 |
17 | 
18 |
19 | ## Deploying the function
20 |
21 | From within the `functions/` directory, run `npm install` to install the Node packages listed in `functions/package.json`. The `functions/index.js` file includes the functions code to call the custom AutoML model.
22 |
23 | First, replace the 3 placeholder strings at the top of the file with info for your own project and AutoML model:
24 |
25 | ```javascript
26 | const project = 'YOUR_PROJECT_NAME';
27 | const region = 'YOUR_PROJECT_REGION';
28 | const automl_model = 'YOUR_AUTOML_MODEL_ID';
29 | ```
30 |
31 | Now you're ready to deploy the function. From the root directory of this project, run the command:
32 |
33 | ```bash
34 | firebase deploy --only functions
35 | ```
36 |
37 | Once your function deploys successfully you can test it by uploading a photo to the Firebase Storage bucket in your project. Then check your Firestore database. You should see the prediction data for that image:
38 |
39 | 
40 |
41 | ## Deploying the frontend
42 |
43 | The frontend code for this app is all in the `public/` directory and uses good old jQuery :) In `public/main.js`, a photo is uploaded to the Firebase Storage bucket for your project which triggers the function calling the AutoML API. First, try it out by serving the frontend locally. Run `firebase serve` from the root directory of this project, navigate to `localhost:5000`, and you should see this:
44 |
45 | 
46 |
47 | If the frontend is working correctly you're ready to deploy it. Run the command:
48 |
49 | ```bash
50 | firebase deploy --only hosting
51 | ```
52 |
53 | Now your app should be deployed to a firebaseapp.com domain, woohoo!
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/firebase.json:
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1 | {
2 | "firestore": {
3 | "rules": "firestore.rules",
4 | "indexes": "firestore.indexes.json"
5 | },
6 | "hosting": {
7 | "public": "public",
8 | "ignore": [
9 | "firebase.json",
10 | "**/.*",
11 | "**/node_modules/**"
12 | ],
13 | "rewrites": [
14 | {
15 | "source": "**",
16 | "destination": "/index.html"
17 | }
18 | ]
19 | }
20 | }
21 |
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/firestore.indexes.json:
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1 | {
2 | // Example:
3 | //
4 | // "indexes": [
5 | // {
6 | // "collectionId": "widgets",
7 | // "fields": [
8 | // { "fieldPath": "foo", "mode": "ASCENDING" },
9 | // { "fieldPath": "bar", "mode": "DESCENDING" }
10 | // ]
11 | // }
12 | // ]
13 | "indexes": []
14 | }
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/firestore.rules:
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1 | service cloud.firestore {
2 | match /databases/{database}/documents {
3 | match /{document=**} {
4 | allow read, write;
5 | }
6 | }
7 | }
8 |
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/functions/index.js:
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1 | // Copyright 2018 Google LLC
2 |
3 | // Licensed under the Apache License, Version 2.0 (the "License");
4 | // you may not use this file except in compliance with the License.
5 | // You may obtain a copy of the License at
6 |
7 | // https://www.apache.org/licenses/LICENSE-2.0
8 |
9 | // Unless required by applicable law or agreed to in writing, software
10 | // distributed under the License is distributed on an "AS IS" BASIS,
11 | // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12 | // See the License for the specific language governing permissions and
13 | // limitations under the License.
14 |
15 | // Replace the strings below with your own project & model info
16 | const project = 'YOUR_PROJECT_NAME';
17 | const region = 'YOUR_PROJECT_REGION';
18 | const automl_model = 'YOUR_AUTOML_MODEL_ID';
19 |
20 | const sizeOf = require('image-size');
21 | const fs = require('fs');
22 | const exec = require('child_process').exec;
23 |
24 | // GCP libraries
25 | const gcs = require('@google-cloud/storage');
26 | const gcsClient = new gcs();
27 | const automl = require('@google-cloud/automl');
28 | const predictionClient = new automl.PredictionServiceClient();
29 |
30 | // Firebase libraries
31 | const functions = require('firebase-functions');
32 | const admin = require('firebase-admin');
33 | const db = admin.firestore();
34 | admin.initializeApp(functions.config().firebase);
35 |
36 | function resizeImg(filepath) {
37 | return new Promise((resolve, reject) => {
38 | exec(`convert ${filepath} -resize 600x ${filepath}`, (err) => {
39 | if (err) {
40 | console.error('Failed to resize image', err);
41 | reject(err);
42 | } else {
43 | console.log('resized image successfully');
44 | resolve(filepath);
45 | }
46 | });
47 | });
48 | }
49 |
50 | function callAutoMLAPI(b64img) {
51 | return new Promise((resolve, reject) => {
52 | const payload = {
53 | "image": {
54 | "imageBytes": b64img
55 | }
56 | }
57 | const reqBody = {
58 | name: predictionClient.modelPath(project, region, automl_model),
59 | payload: payload
60 | }
61 | predictionClient.predict(reqBody)
62 | .then(responses => {
63 | console.log('Got a prediction from AutoML API!', JSON.stringify(responses));
64 | resolve(responses);
65 | })
66 | .catch(err => {
67 | console.log('AutoML API Error: ',err);
68 | reject(err);
69 | });
70 | });
71 |
72 | }
73 |
74 | exports.callCustomModel = functions.storage.object().onFinalize(event => {
75 | const file = gcsClient.bucket(event.bucket).file(event.name);
76 | let destination = '/tmp/' + event.name.replace(/\s/g, '');
77 | return file.download({destination: destination})
78 | .then(() => {
79 | if(sizeOf(destination).width > 600) {
80 | console.log('scaling image down...');
81 | return resizeImg(destination);
82 | } else {
83 | return destination;
84 | }
85 | })
86 | .then(() => {
87 | let bitmap = fs.readFileSync(destination);
88 | let data = new Buffer(bitmap).toString('base64');
89 | return callAutoMLAPI(data);
90 | })
91 | .then((response) => {
92 | let predictions = {};
93 |
94 | // Get only the first prediction response
95 | let data = response[0]['payload'];
96 | predictions[data[0].displayName] = data[0].classification.score;
97 |
98 | if (Object.keys(predictions).length === 0) {
99 | predictions = {"predictionErr": "No high confidence predictions found"};
100 | }
101 | return db.collection('images').doc(event.name).set(predictions);
102 | })
103 | .then(() => {
104 | // Delete tmp image file to clean up resources
105 | return new Promise((resolve, reject) => {
106 | fs.unlinkSync(destination, (err) => {
107 | if (err) {
108 | reject(err);
109 | } else {
110 | resolve();
111 | }
112 | });
113 | });
114 | })
115 | .catch((err) => {
116 | console.log('error occurred', err);
117 | });
118 | });
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/functions/package.json:
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1 | {
2 | "name": "functions",
3 | "description": "Cloud Functions for Firebase",
4 | "dependencies": {
5 | "@google-cloud/automl": "^0.1.1",
6 | "@google-cloud/storage": "^1.7.0",
7 | "firebase-admin": "^6.0.0",
8 | "firebase-functions": "^2.0.5",
9 | "image-size": "^0.6.3"
10 | },
11 | "private": true
12 | }
13 |
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/public/index.html:
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1 |
2 |
3 |
4 |
5 |
6 | Cloud Detector
7 |
8 |
9 |
10 |
11 |
12 |
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16 |
17 |
18 |
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20 |
21 |
22 |
23 |
24 |