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spatialAnticipationNetwork

Requirements

Training:

Evaluation:

Quick Start

  • Prepare Cityscapes dataset: Convert background label 255 to 19
  • Download models and place them inside the 'spatialAnticipationNetwork'-root folder.
  • Adapt the paths in train.py
  • Train the model using python train.py
  • Adapt the paths in eval.py
  • Predict labels on the validation set python eval.py
  • Compute IoU and F1-scores by using ./matlab/evaluateAllResults.m after adapting paths

Acknowledgement

The tensorflow code in this repository was written by modifying a duplicate of DrSleep's-deeplab-tensorflow project. The Matlab evaluation scripts were written by modifying Liang-Chieh Chen's deeplab-public-ver2

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