Try out an algorithm
There are several ways to start an algorithm job.
The easiest way to start a job is by navigating clicking on the Try-out Algorithm option from the side menu or from the Results page
On this page, you can simply drag and drop your inputs or images, and then click on the Save button to start the job.
Connect an Algorithm to an Archive
Another way to run an algorithm job is to connect an Algorithm to an Archive. Go to your Archive → Update Settings → select an Algorithm.
The third way to run algorithm jobs is to use the Grand Challenge API Client to start an algorithm job through Python.
Each method will require you to provide all the inputs defined for the algorithm. After submitting the inputs, the algorithm job will be queued and the job will be visible on the Results page.
To try out your own algorithm, you will have to wait until your algorithm container is uploaded and . You can check the status of your container by clicking on Containers. Normally, it takes about 20 minutes for your new container to be validated by grand-challenge.org and to become active.
To view the results of your jobs, click on the Results page and then click on your result to view the outputs, or click Open Result in Viewer to view your image with one of our image viewers.
When you click you Open Result in Viewer, you will be redirected to a CIRRUS viewer that will display the outputs of the algorithm like in this example from the CORADS-AI algorithm.
💳 An algorithm editor can choose to ask for credits from users who want to try out the algorithm. These can be set by the editor in the algorithm settings. A credit of 0 means users can run the algorithm an unlimited number of times. If a credit value above 0 is set, these will be deducted from the users' credits whenever they submit a file to run the algorithm on. A user has 1000 credits per month at their disposal.
Job execution times
⚠️ The algorithm jobs are executed on AWS ECS and rely on spot instances. This means that the job will only be executed when a spot instance becomes available, a job will remain in the Executing status while waiting for a spot instance. There is no way to predict how long it will take before a spot becomes available (might take more than a day) or to move a job further up in the queue.