potterhsu / SVHN-TODO.pytorch

SVHN-TODO.pytorch

Requirements

• Python 3.6
• PyTorch 0.4.1

Setup

1. Download SVHN Dataset format 1

2. Extract to data folder, now your folder structure should be like below:

   SVHN-TODO.pytorch
       - data
           - extra
               - 1.png
               - 2.png
               - ...
               - digitStruct.mat
           - test
               - 1.png
               - 2.png
               - ...
               - digitStruct.mat
           - train
               - 1.png
               - 2.png
               - ...
               - digitStruct.mat
   

Usage

1. Train

   $ python train.py -d=./data -c=./checkpoints
   

2. Evaluate

   $ python eval.py ./checkpoint/model-100.pth -d=./data
   

3. Infer

   $ python infer.py ./images/15.png -c=./checkpoints/model-100.pth
   $ python infer.py ./images/62.png -c=./checkpoints/model-100.pth
   

References

• Multi-digit Number Recognition from Street View Imagery using Deep Convolutional Neural Networks
• The Street View House Numbers (SVHN) Dataset