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# Author: Tobias Plötz, TU Darmstadt ([email protected])
# This file is part of the implementation as described in the CVPR 2017 paper:
# Tobias Plötz and Stefan Roth, Benchmarking Denoising Algorithms with Real Photographs.
# Please see the file LICENSE.txt for the license governing this code.
import numpy as np
import scipy.io as sio
import os
import h5py
def bundle_submissions_raw(submission_folder,session):
'''
Bundles submission data for raw denoising
submission_folder Folder where denoised images reside
Output is written to <submission_folder>/bundled/. Please submit
the content of this folder.
'''
out_folder = os.path.join(submission_folder, session)
# out_folder = os.path.join(submission_folder, "bundled/")
try:
os.mkdir(out_folder)
except:pass
israw = True
eval_version="1.0"
for i in range(50):
Idenoised = np.zeros((20,), dtype=np.object)
for bb in range(20):
filename = '%04d_%02d.mat'%(i+1,bb+1)
s = sio.loadmat(os.path.join(submission_folder,filename))
Idenoised_crop = s["Idenoised_crop"]
Idenoised[bb] = Idenoised_crop
filename = '%04d.mat'%(i+1)
sio.savemat(os.path.join(out_folder, filename),
{"Idenoised": Idenoised,
"israw": israw,
"eval_version": eval_version},
)
def bundle_submissions_srgb(submission_folder,session):
'''
Bundles submission data for sRGB denoising
submission_folder Folder where denoised images reside
Output is written to <submission_folder>/bundled/. Please submit
the content of this folder.
'''
out_folder = os.path.join(submission_folder, session)
# out_folder = os.path.join(submission_folder, "bundled/")
try:
os.mkdir(out_folder)
except:pass
israw = False
eval_version="1.0"
for i in range(50):
Idenoised = np.zeros((20,), dtype=np.object)
for bb in range(20):
filename = '%04d_%02d.mat'%(i+1,bb+1)
s = sio.loadmat(os.path.join(submission_folder,filename))
Idenoised_crop = s["Idenoised_crop"]
Idenoised[bb] = Idenoised_crop
filename = '%04d.mat'%(i+1)
sio.savemat(os.path.join(out_folder, filename),
{"Idenoised": Idenoised,
"israw": israw,
"eval_version": eval_version},
)
def bundle_submissions_srgb_v1(submission_folder,session):
'''
Bundles submission data for sRGB denoising
submission_folder Folder where denoised images reside
Output is written to <submission_folder>/bundled/. Please submit
the content of this folder.
'''
out_folder = os.path.join(submission_folder, session)
# out_folder = os.path.join(submission_folder, "bundled/")
try:
os.mkdir(out_folder)
except:pass
israw = False
eval_version="1.0"
for i in range(50):
Idenoised = np.zeros((20,), dtype=np.object)
for bb in range(20):
filename = '%04d_%d.mat'%(i+1,bb+1)
s = sio.loadmat(os.path.join(submission_folder,filename))
Idenoised_crop = s["Idenoised_crop"]
Idenoised[bb] = Idenoised_crop
filename = '%04d.mat'%(i+1)
sio.savemat(os.path.join(out_folder, filename),
{"Idenoised": Idenoised,
"israw": israw,
"eval_version": eval_version},
) |