launcher:
  framework: pytorch
  module: samplenet.SampLeNet
  python_path: '.'
  checkpoint: 'samplenet.pth'

# launcher returns raw result, so it should be converted
# to an appropriate representation with adapter
adapter:
  type: classification
  labels:
    - label1
    - label2
    - label3
    - label4
    - label5
    - label6
    - label7
    - label8
    - label9
    - label10

# list of preprocessing, applied to each image during validation
# order of entries matters
preprocessing:
  # resize input image to topology input size
  # you may specify size to which image should be resized
  # via dst_width, dst_height fields
  - type: resize
    size: 32
  # topology is trained on RGB images, but Datumaro reads in BGR
  # so it must be converted to RGB
  - type: bgr_to_rgb
  # dataset mean and standard deviation
  - type: normalization
    mean: (125.307, 122.961, 113.8575)
    std: (51.5865, 50.847, 51.255)