Adding New Data Transforms¶
Write a new pipeline in any file, e.g.,
my_transform.py
. It takes a dict as input and return a dict.from mmflow.registry import TRANSFORMS @TRANSFORMS.register_module() class MyTransform: def transforms(self, results): results['dummy'] = True return results
Import the new class.
from .my_transform import MyTransform
Use it in config files.
train_pipeline = [ dict(type='LoadImageFromFile'), dict(type='LoadAnnotations'), dict(type='ColorJitter', brightness=0.5, contrast=0.5, saturation=0.5, hue=0.5), dict(type='RandomGamma', gamma_range=(0.7, 1.5)), dict(type='RandomFlip', prob=0.5, direction='horizontal'), dict(type='RandomFlip', prob=0.5, direction='vertical'), dict(type='RandomAffine', global_transform=dict( translates=(0.05, 0.05), zoom=(1.0, 1.5), shear=(0.86, 1.16), rotate=(-10., 10.) ), relative_transform=)dict( translates=(0.00375, 0.00375), zoom=(0.985, 1.015), shear=(1.0, 1.0), rotate=(-1.0, 1.0) ), dict(type='RandomCrop', crop_size=(384, 448)), dict(type='MyTransform'), dict(type='PackFlowInputs')]