brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils module

class brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils.AverageMeter

Bases: object

Computes and stores the average and current value

add(val, weight)

average()

initialize(val, weight)

update(val, weight=1)

value()

exception brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils.NotSupportedCliException: Bases: Exception

brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils.accuracy(preds, label)

brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils.colorEncode(labelmap, colors, mode='RGB')

brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils.find_recursive(root_dir, ext='.jpg')

brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils.intersectionAndUnion(imPred, imLab, numClass)

brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils.parse_devices(input_devices): Parse user’s devices input str to standard format. e.g. [gpu0, gpu1, …]

brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils.process_range(xpu, inp)

brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils.setup_logger(distributed_rank=0, filename='log.txt')

brails.processors.FoundationClassifier.csail_segmentation_tool.csail_seg.utils.unique(ar, return_index=False, return_inverse=False, return_counts=False)