measure.py

#!/usr/bin/env python
"""
# > Script for measuring quantitative performances in terms of
#    - Underwater Image Quality Measure (UIQM)
#    - Structural Similarity Metric (SSIM) 
#    - Peak Signal to Noise Ratio (PSNR)
#
# Maintainer: Jahid (email: islam034@umn.edu)
# Interactive Robotics and Vision Lab (http://irvlab.cs.umn.edu/)
# Any part of this repo can be used for academic and educational purposes only
"""
## python libs
import os
import ntpath
import numpy as np
from scipy import misc
## local libs
from utils.data_utils import getPaths
from utils.uqim_utils import getUIQM
from utils.ssm_psnr_utils import getSSIM, getPSNR

## data paths
GTr_im_dir  = '/content/drive/My Drive/USR-248/TEST/hr/' # ground truth im-dir with {f.ext}
GEN_im_dir  = "/content/drive/My Drive/USR/output/p3/" # generated im-dir with {f_gen.png}
GEN_paths = getPaths(GEN_im_dir)

## mesures uqim for all images in a directory
def measure_UIQMs(dir_name):
    paths = getPaths(dir_name)
    uqims = []
    for img_path in paths:
        im = misc.imread(img_path)
        uqims.append(getUIQM(im))
    return np.array(uqims)

## compares avg ssim and psnr 
def measure_SSIM_PSNRs(GT_dir, Gen_dir):
    """
      Assumes:
        * GT_dir contain ground-truths {filename.ext}
        * Gen_dir contain generated images {filename_gen.jpg}
        * Images are of same-size
    """
    GT_paths, Gen_paths = getPaths(GT_dir), getPaths(Gen_dir)
    ssims, psnrs = [], []
    for img_path in GT_paths:
        name_split = ntpath.basename(img_path).split('.')
        gen_path = os.path.join(Gen_dir, name_split[0]+'_gen.jpg') #+name_split[1])
        if (gen_path in Gen_paths):
            r_im = misc.imread(img_path, mode="L")
            g_im = misc.imread(gen_path, mode="L")
            assert (r_im.shape==g_im.shape), "The images should be of same-size"
            ssim = getSSIM(r_im, g_im)
            psnr = getPSNR(r_im, g_im)
            ssims.append(ssim)
            psnrs.append(psnr)
    return np.array(ssims), np.array(psnrs)


### compute SSIM and PSNR
SSIM_measures, PSNR_measures = measure_SSIM_PSNRs(GTr_im_dir, GEN_im_dir)
print ("SSIM >> Mean: {0} std: {1}".format(np.mean(SSIM_measures), np.std(SSIM_measures)))
print ("PSNR >> Mean: {0} std: {1}".format(np.mean(PSNR_measures), np.std(PSNR_measures)))

### compute and compare UIQMs
#g_truth = measure_UIQMs(GTr_im_dir)
#print ("G. Truth UQIM  >> Mean: {0} std: {1}".format(np.mean(g_truth), np.std(g_truth)))
gen_uqims = measure_UIQMs(GEN_im_dir)
print ("Generated UQIM >> Mean: {0} std: {1}".format(np.mean(gen_uqims), np.std(gen_uqims)))