Generic Discriminator for pairs of images

Code based on Facial Similarity with Siamese Networks in Pytorch repository. You can find the related article here.

Pytorch Version

This project is updated to be compatible with Pytorch 1.0.1-1.1.0

How to run

Example 1:

$ python3 main.py

Example 2:

$ python3 main.py --dataset cifar-10 --n_epochs 5000

Example 3:

$ python3 main.py --dataset mnist --b_size 512

Example 4:

$ python3 main.py --dataset faces --b_size 128 --n_epochs 120

Usage

usage: main.py [-h] [--training_dir TRAINING_DIR] [--testing_dir TESTING_DIR]
               [--dataset DATASET] [--b_size B_SIZE] [--n_epochs N_EPOCHS]
               [--resume]

optional arguments:
  -h, --help            show this help message and exit
  --training_dir    TR  folder where data to train is
  --testing_dir     TS  folder where data to test is
  --dataset         D   dataset to run experiments (faces, cifar-10 or mnist)
  --b_size          B   batch size
  --epochs          N   number of total epochs to run, default is 500
  --resume              resume from saved in TRAINING_DIR/model folder