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| from itertools import chain | |
| def IOU(pred, label): | |
| sum_ = pred+label | |
| overlap = sum([1 for _, val in enumerate(list(chain(*sum_))) if val==2]) | |
| union = sum([1 for _, val in enumerate(list(chain(*sum_))) if val==1]) | |
| try: | |
| iou = overlap/(union+overlap) | |
| except ZeroDivisionError: | |
| iou = 0 | |
| return iou | |
| def dice_score(pred, label): | |
| sum_ = pred+label | |
| overlap = sum([1 for _, val in enumerate(list(chain(*sum_))) if val==2]) | |
| predAera = sum([1 for _, val in enumerate(list(chain(*pred))) if val==1]) | |
| labelAera = sum([1 for _, val in enumerate(list(chain(*pred))) if val==1]) | |
| try: | |
| ds = (2*overlap)/(predAera+labelAera) | |
| except ZeroDivisionError: | |
| ds = 0 | |
| return ds | |
| def getTargetSegmentation(batch): | |
| # input is 1-channel of values between 0 and 1 | |
| # values are as follows : 0, 0.33333334, 0.6666667 and 0.94117647 | |
| # output is 1 channel of discrete values : 0, 1, 2 and 3 | |
| denom = 0.33333334 # for ACDC this value | |
| return (batch / denom).round().long().squeeze() |