config/config.yaml

data_dir: data
image_dir: images
saliency_dir: saliency
repo_id: "MarcoParola/saliency-evaluation"

gui:
  max_img_examples: 16

experiments: exp1

results:
  save_dir: results
  exp1_dir: exp1
  exp2_dir: exp2

dataset: 
  name: intel_image
  path: data
  intel_image:
    n_classes: 6
    class_names: ['BUILDING', 'FOREST', 'GLACIER', 'MOUNTAIN', 'SEA', 'STREET']
  imagenette:
    n_classes: 10
    class_names: ['tench', 'English springer', 'cassette player', 'chain saw', 'church', 'French horn', 'garbage truck', 'gas pump', 'golf ball', 'parachute']

saliency_methods:
  - gradcam
  - lime
  - sidu
  - rise