WebOct 10, 2024 · The output feature map after your classification layer gives probabilities. That is every pixel value is the probability if it belongs to that class. And you have N channels where N = number of classes. Thus for each class you get a 2d feature map of probabilities. Thus taking a max gives which pixel belongs to which index. WebReturns:dict[str, float]: COCO style evaluation metric or cityscapes mAP \and AP@50."""eval_results=dict()metrics=metric.copy()ifisinstance(metric,list)else[metric]if'cityscapes'inmetrics:eval_results.update(self._evaluate_cityscapes(results,outfile_prefix,logger))metrics.remove('cityscapes')# left metrics are all coco metriciflen(metrics)>0:# …

Dataset Overview – Cityscapes Dataset

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models/get_dataset_colormap.py at master · tensorflow/models

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