| 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) |
| |
| 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) |
| |
| 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) |
| |
| 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}, |
| ) |
