Detects ship bounding boxes in a given image strip using a trained CNN classifier to deploy on Protogen-generated region proposals.

Here we run through a sample execution of the ship-detector task. We will find all ships in an image over New York. All of the input data is available in the S3 locations specified below.

1. Within an iPython terminal create a GBDX interface an specify the task input location:

   from gbdxtools import Interface
   from os.path import join
   import uuid
   
   gbdx = Interface()
   
   input_location = 's3://gbd-customer-data/58600248-2927-4523-b44b-5fec3d278c09/platform-stories/ship-detector/'

2. Create a task instance and set the required inputs:

   ship_task = gbdx.Task('ship-detector')
   ship_task.inputs.pan_image = join(input_location, 'pan_image')
   ship_task.inputs.ms_image = join(input_location, 'ms_image')

3. Initialize a workflow and specify where to save the output:

   ship_wf = gbdx.Workflow([ship_task])
   random_str = str(uuid.uuid4())
   output_location = join('platform-stories/trial-runs', random_str)
   
   ship_wf.savedata(ship_task.outputs.results, join(output_location, 'ship_detections'))

4. Execute the workflow:

   ship_wf.execute()

5. Track the status of the workflow as follows:

   ship_wf.status

GBDX input ports can only be of "Directory" or "String" type. Booleans, integers and floats are passed to the task as strings, e.g., "True", "10", "0.001".

You need to install Docker.

Clone the repository:

git clone https://github.com/platformstories/ship-detector

Then build the image locally. Building requires input environment variables for protogen and GBDX AWS credentials. You will need to contact [email protected] for access to Protogen.

cd ship-detector
docker build --build-arg PROTOUSER=<GitHub username> \
    --build-arg PROTOPASSWORD=<GitHub pawwsord> \
    --build-arg AWS_ACCESS_KEY_ID=<AWS access key> \
    --build-arg AWS_SECRET_ACCESS_KEY=<AWS secret key> \
    --build-arg AWS_SESSION_TOKEN=<AWS session token> \
    -t ship-detector .

Create a container in interactive mode and mount the sample input under /mnt/work/input/:

docker run -v full/path/to/sample-input:/mnt/work/input -it ship-detector

Then, within the container:

python /ship-detector.py

Login to Docker Hub:

docker login

Tag your image using your username and push it to DockerHub:

docker tag ship-detector yourusername/ship-detector
docker push yourusername/ship-detector

The image name should be the same as the image name under containerDescriptors in ship-detector.json.

Alternatively, you can link this repository to a Docker automated build. Every time you push a change to the repository, the Docker image gets automatically updated.

In a Python terminal:

from gbdxtools import Interface
gbdx=Interface()
gbdx.task_registry.register(json_filename="ship-detector.json")

Note: If you change the task image, you need to reregister the task with a higher version number in order for the new image to take effect. Keep this in mind especially if you use Docker automated build.