compute_dists.py

import argparse
from perceptual_similarity import models
from perceptual_similarity.util import util

parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('-p0','--path0', type=str, default='./imgs/ex_ref.png')
parser.add_argument('-p1','--path1', type=str, default='./imgs/ex_p0.png')
parser.add_argument('--use_gpu', action='store_true', help='turn on flag to use GPU')

opt = parser.parse_args()

## Initializing the model
model = models.PerceptualLoss(model='net-lin',net='alex',use_gpu=opt.use_gpu)

# Load images
img0 = util.im2tensor(util.load_image(opt.path0)) # RGB image from [-1,1]
img1 = util.im2tensor(util.load_image(opt.path1))

if(opt.use_gpu):
	img0 = img0.cuda()
	img1 = img1.cuda()


# Compute distance
dist01 = model.forward(img0,img1)
print('Distance: %.3f'%dist01)