Simple Image Processing

Introduction

In this example tutorial, we will show you how to use Bacalhau to process images on a Landsat dataset.

Bacalhau has the unique capability of operating at a massive scale in a distributed environment. This is made possible because data is naturally sharded across the IPFS network amongst many providers. We can take advantage of this to process images in parallel.

Prerequisite​

To get started, you need to install the Bacalhau client, see more information here

Running a Bacalhau Job​

To submit a workload to Bacalhau, we will use the bacalhau docker run command. This command allows to pass input data volume with a -i ipfs://CID:path argument just like Docker, except the left-hand side of the argument is a content identifier (CID). This results in Bacalhau mounting a data volume inside the container. By default, Bacalhau mounts the input volume at the path /inputs inside the container.

Bacalhau also mounts a data volume to store output data. The bacalhau docker run command creates an output data volume mounted at /outputs. This is a convenient location to store the results of your job.

export JOB_ID=$(bacalhau docker run \
    --wait \
    --wait-timeout-secs 100 \
    --id-only \
    -i src=s3://landsat-image-processing/*,dst=/input_images,opt=region=us-east-1 \
    --publisher ipfs \
    --entrypoint mogrify \
    dpokidov/imagemagick:7.1.0-47-ubuntu \
    -- -resize 100x100 -quality 100 -path /outputs '/input_images/*.jpg')

Structure of the command​

Let's look closely at the command above:

1. bacalhau docker run: call to Bacalhau

2. -i src=s3://landsat-image-processing/*,dst=/input_images,opt=region=us-east-1: Specifies the input data, which is stored in the S3 storage.

3. --entrypoint mogrify: Overrides the default ENTRYPOINT of the image, indicating that the mogrify utility from the ImageMagick package will be used instead of the default entry.

4. dpokidov/imagemagick:7.1.0-47-ubuntu: The name and the tag of the docker image we are using

5. -- -resize 100x100 -quality 100 -path /outputs '/input_images/*.jpg': These arguments are passed to mogrify and specify operations on the images: resizing to 100x100 pixels, setting quality to 100, and saving the results to the /outputs folder.

When a job is submitted, Bacalhau prints out the related job_id. We store that in an environment variable so that we can reuse it later on.

Declarative job description​

The same job can be presented in the declarative format. In this case, the description will look like this:

name: Simple Image Processing
type: batch
count: 1
tasks:
  - name: My main task
    Engine:
      type: docker
      params:
        Image: dpokidov/imagemagick:7.1.0-47-ubuntu
        Entrypoint:
          - /bin/bash
        Parameters:
          - -c
          - magick mogrify -resize 100x100 -quality 100 -path /outputs '/input_images/*.jpg'
    Publisher:
      Type: ipfs
    ResultPaths:
      - Name: outputs
        Path: /outputs
    InputSources:
    - Target: "/input_images"
      Source:
        Type: "s3"
        Params:
          Bucket: "landsat-image-processing"
          Key: "*"
          Region: "us-east-1"

The job description should be saved in .yaml format, e.g. image.yaml, and then run with the command:

bacalhau job run image.yaml

Checking the State of your Jobs​

Job status: You can check the status of the job using bacalhau job list:

bacalhau job list --id-filter ${JOB_ID}

When it says Completed, that means the job is done, and we can get the results.

Job information: You can find out more information about your job by using bacalhau job describe:

bacalhau job describe ${JOB_ID}

Job download: You can download your job results directly by using bacalhau job get. Alternatively, you can choose to create a directory to store your results. In the command below, we created a directory and downloaded our job output to be stored in that directory.

rm -rf results && mkdir results
bacalhau job get ${JOB_ID} --output-dir results

Display the image​

To view the images, open the results/outputs/ folder:

Support​

If you have questions or need support or guidance, please reach out to the Bacalhau team via Slack (#general channel).