ATLAS is a spot detection method. The spots size is automatically selected and the detection threshold adapts to the local image dynamics.

ATLAS relies on the Laplacian of Gaussian (LoG) filter, which both reduces noise and enhances spots. A multiscale representation of the image is built to automatically select the optimal LoG variance. Then, local statistics of the LoG image are estimated in a Gaussian window, and the detection threshold is pointwise inferred from a probability of false alarm (PFA). Hence, the user only has to specify:

1. the standart deviation of the Gaussian window,
2. the PFA value.

The Gaussian window must be about the size of the background structures. Increasing the PFA increases the number of detections.

In order to run a job you need to be identified or register a new account.

The following curl command will create a job:

# create a job for this app with the ID 1007
curl -H 'Authorization: Token token=<your private_token>' -X POST
  -F 'job[webapp_id]=1007'
  -F 'job[param]='
  -F 'job[queue]=standard'
  -F 'files[0]=@test.txt'
  -F 'files[1]=@test2.csv'
  -F 'job[file_url]=<my_file_url>'
  -F 'job[dataset]=<my_dataset_name>'

Checkout the result:

curl -H 'Authorization: Token token=<your private_token>' '<job_id>'