SAE,SAEHD,Converter:

added sot-m color transfer

Converter:
removed seamless2 mode

imagelib/color_transfer.py

@@ -1,10 +1,62 @@
 import cv2
 import numpy as np
+from numpy import linalg as npla
 
 import scipy as sp
 import scipy.sparse
 from scipy.sparse.linalg import spsolve
 
+def color_transfer_sot(src,trg, steps=10, batch_size=5, reg_sigmaXY=16.0, reg_sigmaV=5.0):
+    """
+    Color Transform via Sliced Optimal Transfer
+    ported by @iperov from https://github.com/dcoeurjo/OTColorTransfer 
+
+    src         - any float range any channel image
+    dst         - any float range any channel image, same shape as src
+    steps       - number of solver steps
+    batch_size  - solver batch size
+    reg_sigmaXY - apply regularization and sigmaXY of filter, otherwise set to 0.0
+    reg_sigmaV  - sigmaV of filter
+    
+    return value - clip it manually
+    """
+    if not np.issubdtype(src.dtype, np.floating):
+        raise ValueError("src value must be float")
+    if not np.issubdtype(trg.dtype, np.floating):
+        raise ValueError("trg value must be float")
+
+    if len(src.shape) != 3:
+        raise ValueError("src shape must have rank 3 (h,w,c)")
+    
+    if src.shape != trg.shape:
+        raise ValueError("src and trg shapes must be equal")    
+
+    src_dtype = src.dtype        
+    h,w,c = src.shape
+    new_src = src.copy()
+
+    for step in range (steps):
+        advect = np.zeros ( (h*w,c), dtype=src_dtype )
+        for batch in range (batch_size):
+            dir = np.random.normal(size=c).astype(src_dtype)
+            dir /= npla.norm(dir)
+
+            projsource = np.sum( new_src*dir, axis=-1).reshape ((h*w))
+            projtarget = np.sum( trg*dir, axis=-1).reshape ((h*w))
+
+            idSource = np.argsort (projsource)
+            idTarget = np.argsort (projtarget)
+
+            a = projtarget[idTarget]-projsource[idSource]
+            for i_c in range(c):
+                advect[idSource,i_c] += a * dir[i_c]
+        new_src += advect.reshape( (h,w,c) ) / batch_size
+
+    if reg_sigmaXY != 0.0:
+        src_diff = new_src-src
+        new_src = src + cv2.bilateralFilter (src_diff, 0, reg_sigmaV, reg_sigmaXY )
+    return new_src
+        
 def color_transfer_mkl(x0, x1):
     eps = np.finfo(float).eps