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YAML

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)