facilitates implementing deep neural-network backbones, data augmentations, optimizers and learning schedulers. backbones loss functions augumentation styles optimizers schedulers data types visualizations Refer to docs/installation.md for installion of general_backbone package. Model backone Currently, general_backbone supports more than 70 type of resnet models such as: resnet18, resnet34, resnet50, resnet101, resnet152, resnext50. All models is supported can be found in general_backbone.list_models() function: import general_backbone general_backbone.list_models() Results {‘resnet’: [‘resnet18’, ‘resnet18d’, ‘resnet34’, ‘resnet34d’, ‘resnet26’, ‘resnet26d’, ‘resnet26t’, ‘resnet50’, ‘resnet50d’, ‘resnet50t’, ‘resnet101’, ‘resnet101d’, ‘resnet152’, ‘resnet152d’, ‘resnet200’, ‘resnet200d’, […]
Read more