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dataset:
urls:
# USER: adapt this path the root of your custom dataset
- "/path/to/data"
pipeline_config:
shardshuffle: 10000
sample_shuffle: 1000 # USER: you might wanna adapt depending on your available RAM
decoders:
- "pil"
postprocessors:
- target: sdata.mappers.TorchVisionImageTransforms
params:
key: 'jpg' # USER: you might wanna adapt this for your custom dataset
transforms:
- target: torchvision.transforms.Resize
params:
size: 256
interpolation: 3
- target: torchvision.transforms.ToTensor
- target: sdata.mappers.Rescaler
- target: sdata.mappers.AddOriginalImageSizeAsTupleAndCropToSquare
params:
h_key: height # USER: you might wanna adapt this for your custom dataset
w_key: width # USER: you might wanna adapt this for your custom dataset
loader:
batch_size: 64
num_workers: 6 |