release v1

.gitignore

@@ -56,3 +56,7 @@ docs/_build/
 
 # PyBuilder
 target/
+
+\.idea/
+
+\.DS_Store

README.md

@@ -1 +1,20 @@
-prnu-python
+# Python porting of PRNU extractor and helper functions
+
+## Authors
+- Luca Bondi (luca.bondi@polimi.it)
+- Paolo Bestagini (paolo.bestagini@polimi.it)
+- Nicolò Bonettini (nicolo.bonettini@polimi.it)
+
+## Usage
+See *example.py*
+
+## Test
+```bash
+python -m unittest test
+```
+Tested with Python 3.6
+
+## Credits
+Reference MATLAB implementation by Binghamton university: 
+http://dde.binghamton.edu/download/camera_fingerprint/
+

example.py

@@ -0,0 +1,90 @@
+# -*- coding: UTF-8 -*-
+"""
+@author: Luca Bondi (luca.bondi@polimi.it)
+@author: Paolo Bestagini (paolo.bestagini@polimi.it)
+@author: Nicolò Bonettini (nicolo.bonettini@polimi.it)
+Politecnico di Milano 2018
+"""
+
+import os
+from glob import glob
+from multiprocessing import cpu_count, Pool
+
+import numpy as np
+from PIL import Image
+
+import prnu
+
+
+def main():
+    """
+    Main example script. Load a subset of flatfield and natural images from Dresden.
+    For each device compute the fingerprint from all the flatfield images.
+    For each natural image compute the noise residual.
+    Check the detection performance obtained with cross-correlation and PCE
+    :return:
+    """
+    ff_dirlist = np.array(sorted(glob('test/data/ff-jpg/*.JPG')))
+    ff_device = np.array([os.path.split(i)[1].rsplit('_', 1)[0] for i in ff_dirlist])
+
+    nat_dirlist = np.array(sorted(glob('test/data/nat-jpg/*.JPG')))
+    nat_device = np.array([os.path.split(i)[1].rsplit('_', 1)[0] for i in nat_dirlist])
+
+    print('Computing fingerprints')
+    fingerprint_device = sorted(np.unique(ff_device))
+    k = []
+    for device in fingerprint_device:
+        imgs = []
+        for img_path in ff_dirlist[ff_device == device]:
+            im = Image.open(img_path)
+            im_arr = np.asarray(im)
+            if im_arr.dtype != np.uint8:
+                print('Error while reading image: {}'.format(img_path))
+                continue
+            if im_arr.ndim != 3:
+                print('Image is not RGB: {}'.format(img_path))
+                continue
+            im_cut = prnu.cut_ctr(im_arr, (512, 512, 3))
+            imgs += [im_cut]
+        k += [prnu.extract_multiple_aligned(imgs, processes=cpu_count())]
+
+    k = np.stack(k, 0)
+
+    print('Computing residuals')
+
+    imgs = []
+    for img_path in nat_dirlist:
+        imgs += [prnu.cut_ctr(np.asarray(Image.open(img_path)), (512, 512, 3))]
+
+    pool = Pool(cpu_count())
+    w = pool.map(prnu.extract_single, imgs)
+    pool.close()
+
+    w = np.stack(w, 0)
+
+    # Computing Ground Truth
+    gt = prnu.gt(fingerprint_device, nat_device)
+
+    print('Computing cross correlation')
+    cc_aligned_rot = prnu.aligned_cc(k, w)['cc']
+
+    print('Computing statistics cross correlation')
+    stats_cc = prnu.stats(cc_aligned_rot, gt)
+
+    print('Computing PCE')
+    pce_rot = np.zeros((len(fingerprint_device), len(nat_device)))
+
+    for fingerprint_idx, fingerprint_k in enumerate(k):
+        for natural_idx, natural_w in enumerate(w):
+            cc2d = prnu.crosscorr_2d(fingerprint_k, natural_w)
+            pce_rot[fingerprint_idx, natural_idx] = prnu.pce(cc2d)['pce']
+
+    print('Computing statistics on PCE')
+    stats_pce = prnu.stats(pce_rot, gt)
+
+    print('AUC on CC {:.2f}, expected {:.2f}'.format(stats_cc['auc'], 0.98))
+    print('AUC on PCE {:.2f}, expected {:.2f}'.format(stats_pce['auc'], 0.83))
+
+
+if __name__ == '__main__':
+    main()

prnu/__init__.py

@@ -0,0 +1,8 @@
+# -*- coding: UTF-8 -*-
+"""
+@author: Luca Bondi (luca.bondi@polimi.it)
+@author: Paolo Bestagini (paolo.bestagini@polimi.it)
+@author: Nicolò Bonettini (nicolo.bonettini@polimi.it)
+Politecnico di Milano 2018
+"""
+from .functions import *