breadcake / PFNet-pytorch

PyTorch implementation of 'Rethinking Planar Homography Estimation Using Perspective Fields'

PFNet-pytorch

PyTorch implementation for reproducing Perspective Network (PFNet) results in the paper Rethinking Planar Homography Estimation Using Perspective Fields by Rui Zeng, Simon Denman, Sridha Sridharan, Clinton Fookes.

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COCO Dataset

• Download the COCO 2014 dataset used in the paper.

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Trained Weights.

• Download our trained weights from Baidu Cloud(Extraction code: enkv) and put it in the root directory

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Dependencies

• Python 3.6
• Pytorch 1.8.0

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Training

• Train a PFNet model on the COCO dataset from scratch:
  • python train.py --dataset=/path/to/COCO

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Evaluation

• Evaluate the model checkpoint
  • python evaluate.py --dataset=/path/to/COCO --model=./pfnet_0200.pth

Current Performance

MACE: 1.21

results

Reference

https://github.com/ruizengalways/PFNet