Today, we are introducing the new /digitalocean/store Robot, which allows you to export your Assembly results to DigitalOcean's Spaces Object Storage. This adds another option to the list of file exporting providers we already support, like Amazon S3, Rackspace Cloud Files and Dropbox. Check out the full list in our docs.

The /digitalocean/store Robot

You can use the /digitalocean/store Robot to upload your files or Assembly results to DigitalOcean Spaces for long and short term storage. Your files can set to be publicly available or private to your account.

/digitalocean/store Robot

Built upon the open source Ceph storage system, Spaces support most of the features Amazon S3 offers, which means that if you already use our /s3/store Robot, the API should look very familiar.

In this blog post, we're guiding you through the process of setting up a DigitalOcean Spaces account, transcoding your files and exporting the results to your Spaces account. If you just want to look at the Robot's API and play with it yourself, check out its docs and the example Assembly Instructions below:

  "steps": {
    "store": {
      "robot": "/digitalocean/store",
      "credentials": "spaces-store-demo",
      "space": "spaces-store-demo",
      "acl": "public-read"

Setting up DigitalOcean Spaces

The first step is to create a DigitalOcean account, if you haven't already done so. Head over to to get started.

Next, navigate to the Spaces tab to create a new Space, which we're going to call spaces-store-demo. Select the datacenter region closest to where you're going to fetch the data from. Here, we've selected fra1 / Frankfurt.

Creating a Space on DigitalOcean in Frankfurt, with 'Restrict File Listing' selected.

Once created, we have an empty Spaces account to which we can start exporting files:

The newly created space with no files being stored.

In order for our Robot to be able to talk to the DigitalOcean Spaces API, we also need to create a pair of Spaces access keys. You can do so in the API section of your DigitalOcean account. Best keep this tab open for now, as we're going to need the public and private secret keys in the following steps. Never share these credentials with anyone you don't want to have write access to your Space.

The Applications and API page, with the API key at the bottom

Creating Template Credentials

We're done with DigitalOcean for now, so let's head over to and create a free account! The Sandbox plan comes with 2 GB of transcoding volume and two priority job slots, so it's all you're going to need to get started with our Robots.

To allow better security and easier re-use, Transloadit offers you to create Template Credentials and store the secrets for you. Once logged in, navigate to your account and select Template Credentials. Choose the third party service Digital Ocean Spaces and enter your Space credentials as follows, replacing space name, region, key id and secret access key as required:

The Transloadit Template Credentials page, where a new DigitalOcean Credential is being made.

Hit save and you're done! The Template Credentials name — spaces-store-demo in this case — is what we're going to use in the next step.

Detecting faces

Let's get to finally submitting some files to a new Assembly! Our example is going to use the /image/facedetect and /digitalocean/store Robots. Once we're done, you'll be able to upload image files in which all human faces are going to be detected and separately uploaded to your DigitalOcean Space.

For the purpose of this guide, we're using the curl(1) command line tool to interact with the Transloadit API, which is most likely already installed on your computer. If you are on Windows, check out the official curl for Windows instructions.

First, another preparatory step: head over to the API settings in your Transloadit account and please copy the Auth Key.

Copying the Auth key from the Transloadit Credentials page

(Don't worry, we regenerated our Secret after taking this screenshot 😄)

Then, create a file with these Assembly Instructions, which we're going to call params.json. Replace the auth.key with your personal Auth Key.

  "auth": {
    "key": "3ba3ac15473f4ce89a279db977248d29"
  "steps": {
    "face-detect": {
      "use": ":original",
      "robot": "/image/facedetect",
      "crop": true,
      "faces": "each"
    "store": {
      "use": "face-detect",
      "robot": "/digitalocean/store",
      "credentials": "spaces-store-demo",
      "space": "spaces-store-demo",
      "acl": "public-read"

The Assembly consists of two Steps:

  1. Detect faces and extract each detected face as a cropped image
  2. Upload the extracted faces to your DigitalOcean Space, using public-read permissions, so the files are publicly accessible

Testing the Assembly

Now there is just one piece missing, and that's to kick off the whole machinery using a single command!

You're going to need an image with some faces on it to test your Assembly. Here's one you can grab if you don't have one readily available:

A stock photo of two people looking towards the camera in a wooded area.

Issue the following curl(1) command in your terminal, in the same folder where params.json and the source image (here group.jpg) are stored. Pipe to json_pp(1) in order to get a nicely formatted JSON output.

curl \
  -s \
  -XPOST \
  -F params="$(< params.json)" \
  -F original=@group.jpg \ \
  | json_pp

If you're curious why the curl(1) command looks as it does:

  • -s instructs curl(1) to be quiet, so we only see the HTTP response body
  • -XPOST in order to make this a POST request
  • -F ... Transloadit uses HTTP multipart formposts, so that the client can submit both the Assembly Instructions and the files, all in one request (and so that our API can be integrated with plain old <form>s). Here we use -F to submit both params.json and group.jpg.

Head over to your Transloadit account's Assemblies page and click on the topmost row to see the results!

The Assembly Results page

As you can see, in our case two faces were detected. Click on the OPEN buttons to the side of each result to see the cropped faces, served from your newly created DigitalOcean Space!

A cropped version of the earlier stock photo focused on the face on the right
A cropped version of the earlier stock photo focused on the face on the left


That's it! We hope you liked this blog post and are looking forward to the next one. And if you'd like to try this, sign up for a free Transloadit account today!