--- a/color_deconvolution.py	Mon Jul 22 04:55:58 2019 -0400
+++ b/color_deconvolution.py	Thu Mar 06 18:12:13 2025 +0000
@@ -1,87 +1,115 @@
 import argparse
 import sys
 import warnings
+
+import giatools.io
 import numpy as np
-import skimage.io
 import skimage.color
+import skimage.io
 import skimage.util
-from sklearn.decomposition import PCA, NMF, FastICA, FactorAnalysis
+import tifffile
+from sklearn.decomposition import FactorAnalysis, FastICA, NMF, PCA
+
+# Stain separation matrix for H&E color deconvolution, extracted from ImageJ/FIJI
+rgb_from_he = np.array([
+    [0.64431860, 0.7166757, 0.26688856],
+    [0.09283128, 0.9545457, 0.28324000],
+    [0.63595444, 0.0010000, 0.77172660],
+])
 
 convOptions = {
-           'hed2rgb' : lambda img_raw: skimage.color.hed2rgb(img_raw),
-           'hsv2rgb' : lambda img_raw: skimage.color.hsv2rgb(img_raw),
-           'lab2lch' : lambda img_raw: skimage.color.lab2lch(img_raw),
-           'lab2rgb' : lambda img_raw: skimage.color.lab2rgb(img_raw),
-           'lab2xyz' : lambda img_raw: skimage.color.lab2xyz(img_raw),
-           'lch2lab' : lambda img_raw: skimage.color.lch2lab(img_raw),
-           'luv2rgb' : lambda img_raw: skimage.color.luv2rgb(img_raw),
-           'luv2xyz' : lambda img_raw: skimage.color.luv2xyz(img_raw),
-           'rgb2hed' : lambda img_raw: skimage.color.rgb2hed(img_raw),
-           'rgb2hsv' : lambda img_raw: skimage.color.rgb2hsv(img_raw),
-           'rgb2lab' : lambda img_raw: skimage.color.rgb2lab(img_raw),
-           'rgb2luv' : lambda img_raw: skimage.color.rgb2luv(img_raw),
-           'rgb2rgbcie' : lambda img_raw: skimage.color.rgb2rgbcie(img_raw),
-           'rgb2xyz' : lambda img_raw: skimage.color.rgb2xyz(img_raw),
-           #'rgb2ycbcr' : lambda img_raw: skimage.color.rgb2ycbcr(img_raw),
-           #'rgb2yiq' : lambda img_raw: skimage.color.rgb2yiq(img_raw),
-           #'rgb2ypbpr' : lambda img_raw: skimage.color.rgb2ypbpr(img_raw),
-           #'rgb2yuv' : lambda img_raw: skimage.color.rgb2yuv(img_raw),
-           #'rgba2rgb' : lambda img_raw: skimage.color.rgba2rgb(img_raw),
-           'rgbcie2rgb' : lambda img_raw: skimage.color.rgbcie2rgb(img_raw),
-           'xyz2lab' : lambda img_raw: skimage.color.xyz2lab(img_raw),
-           'xyz2luv' : lambda img_raw: skimage.color.xyz2luv(img_raw),
-           'xyz2rgb' : lambda img_raw: skimage.color.xyz2rgb(img_raw),
-           #'ycbcr2rgb' : lambda img_raw: skimage.color.ycbcr2rgb(img_raw),
-           #'yiq2rgb' : lambda img_raw: skimage.color.yiq2rgb(img_raw),
-           #'ypbpr2rgb' : lambda img_raw: skimage.color.ypbpr2rgb(img_raw),
-           #'yuv2rgb' : lambda img_raw: skimage.color.yuv2rgb(img_raw),    
-    
-           'rgb_from_hed' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hed),
-           'rgb_from_hdx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hdx),
-           'rgb_from_fgx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_fgx),
-           'rgb_from_bex' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_bex),
-           'rgb_from_rbd' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_rbd),
-           'rgb_from_gdx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_gdx),
-           'rgb_from_hax' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hax),
-           'rgb_from_bro' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_bro),
-           'rgb_from_bpx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_bpx),
-           'rgb_from_ahx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_ahx),
-           'rgb_from_hpx' : lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hpx),
-    
-           'hed_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hed_from_rgb),
-           'hdx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hdx_from_rgb),
-           'fgx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.fgx_from_rgb),
-           'bex_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bex_from_rgb),
-           'rbd_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.rbd_from_rgb),
-           'gdx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.gdx_from_rgb),
-           'hax_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hax_from_rgb),
-           'bro_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bro_from_rgb),
-           'bpx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bpx_from_rgb),
-           'ahx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.ahx_from_rgb),
-           'hpx_from_rgb' : lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hpx_from_rgb),    
-    
-           'pca' : lambda img_raw: np.reshape(PCA(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])), 
-                              [img_raw.shape[0],img_raw.shape[1],-1]),    
-           'nmf' : lambda img_raw: np.reshape(NMF(n_components=3, init='nndsvda').fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])), 
-                              [img_raw.shape[0],img_raw.shape[1],-1]),
-           'ica' : lambda img_raw: np.reshape(FastICA(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])), 
-                              [img_raw.shape[0],img_raw.shape[1],-1]),
-           'fa' : lambda img_raw: np.reshape(FactorAnalysis(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])), 
-                              [img_raw.shape[0],img_raw.shape[1],-1])
+    # General color space conversion operations
+    'hed2rgb': lambda img_raw: skimage.color.hed2rgb(img_raw),
+    'hsv2rgb': lambda img_raw: skimage.color.hsv2rgb(img_raw),
+    'lab2lch': lambda img_raw: skimage.color.lab2lch(img_raw),
+    'lab2rgb': lambda img_raw: skimage.color.lab2rgb(img_raw),
+    'lab2xyz': lambda img_raw: skimage.color.lab2xyz(img_raw),
+    'lch2lab': lambda img_raw: skimage.color.lch2lab(img_raw),
+    'luv2rgb': lambda img_raw: skimage.color.luv2rgb(img_raw),
+    'luv2xyz': lambda img_raw: skimage.color.luv2xyz(img_raw),
+    'rgb2hed': lambda img_raw: skimage.color.rgb2hed(img_raw),
+    'rgb2hsv': lambda img_raw: skimage.color.rgb2hsv(img_raw),
+    'rgb2lab': lambda img_raw: skimage.color.rgb2lab(img_raw),
+    'rgb2luv': lambda img_raw: skimage.color.rgb2luv(img_raw),
+    'rgb2rgbcie': lambda img_raw: skimage.color.rgb2rgbcie(img_raw),
+    'rgb2xyz': lambda img_raw: skimage.color.rgb2xyz(img_raw),
+    'rgbcie2rgb': lambda img_raw: skimage.color.rgbcie2rgb(img_raw),
+    'xyz2lab': lambda img_raw: skimage.color.xyz2lab(img_raw),
+    'xyz2luv': lambda img_raw: skimage.color.xyz2luv(img_raw),
+    'xyz2rgb': lambda img_raw: skimage.color.xyz2rgb(img_raw),
+
+    # Color deconvolution operations
+    'hed_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hed_from_rgb),
+    'hdx_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hdx_from_rgb),
+    'fgx_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.fgx_from_rgb),
+    'bex_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bex_from_rgb),
+    'rbd_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.rbd_from_rgb),
+    'gdx_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.gdx_from_rgb),
+    'hax_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hax_from_rgb),
+    'bro_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bro_from_rgb),
+    'bpx_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.bpx_from_rgb),
+    'ahx_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.ahx_from_rgb),
+    'hpx_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, skimage.color.hpx_from_rgb),
+
+    # Recomposition operations (reverse color deconvolution)
+    'rgb_from_hed': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hed),
+    'rgb_from_hdx': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hdx),
+    'rgb_from_fgx': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_fgx),
+    'rgb_from_bex': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_bex),
+    'rgb_from_rbd': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_rbd),
+    'rgb_from_gdx': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_gdx),
+    'rgb_from_hax': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hax),
+    'rgb_from_bro': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_bro),
+    'rgb_from_bpx': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_bpx),
+    'rgb_from_ahx': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_ahx),
+    'rgb_from_hpx': lambda img_raw: skimage.color.combine_stains(img_raw, skimage.color.rgb_from_hpx),
+
+    # Custom color deconvolution and recomposition operations
+    'rgb_from_he': lambda img_raw: skimage.color.combine_stains(img_raw, rgb_from_he),
+    'he_from_rgb': lambda img_raw: skimage.color.separate_stains(img_raw, np.linalg.inv(rgb_from_he)),
+
+    # Unsupervised machine learning-based operations
+    'pca': lambda img_raw: np.reshape(PCA(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])),
+                                      [img_raw.shape[0], img_raw.shape[1], -1]),
+    'nmf': lambda img_raw: np.reshape(NMF(n_components=3, init='nndsvda').fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])),
+                                      [img_raw.shape[0], img_raw.shape[1], -1]),
+    'ica': lambda img_raw: np.reshape(FastICA(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])),
+                                      [img_raw.shape[0], img_raw.shape[1], -1]),
+    'fa': lambda img_raw: np.reshape(FactorAnalysis(n_components=3).fit_transform(np.reshape(img_raw, [-1, img_raw.shape[2]])),
+                                     [img_raw.shape[0], img_raw.shape[1], -1])
 }
 
 parser = argparse.ArgumentParser()
 parser.add_argument('input_file', type=argparse.FileType('r'), default=sys.stdin, help='input file')
 parser.add_argument('out_file', type=argparse.FileType('w'), default=sys.stdin, help='out file (TIFF)')
 parser.add_argument('conv_type', choices=convOptions.keys(), help='conversion type')
-args = parser.parse_args() 
+parser.add_argument('--isolate_channel', type=int, help='set all other channels to zero (1-3)', default=0)
+args = parser.parse_args()
+
+# Read and normalize the input image as TZYXC
+img_in = giatools.io.imread(args.input_file.name)
+
+# Verify input image
+assert img_in.shape[0] == 1, f'Image must have 1 frame (it has {img_in.shape[0]} frames)'
+assert img_in.shape[1] == 1, f'Image must have 1 slice (it has {img_in.shape[1]} slices)'
+assert img_in.shape[4] == 3, f'Image must have 3 channels (it has {img_in.shape[4]} channels)'
 
-img_in = skimage.io.imread(args.input_file.name)[:,:,0:3]
-res = convOptions[args.conv_type](img_in)
-res[res<-1]=-1
-res[res>1]=1
+# Normalize the image from TZYXC to YXC
+img_in = img_in.squeeze()
+assert img_in.ndim == 3
+
+# Apply channel isolation
+if args.isolate_channel:
+    for ch in range(3):
+        if ch + 1 != args.isolate_channel:
+            img_in[:, :, ch] = 0
+
+result = convOptions[args.conv_type](img_in)
+
+# It is sufficient to store 32bit floating point data, the precision loss is tolerable
+if result.dtype == np.float64:
+    result = result.astype(np.float32)
 
 with warnings.catch_warnings():
-	warnings.simplefilter("ignore")
-	res = skimage.util.img_as_uint(res) #Attention: precision loss
-	skimage.io.imsave(args.out_file.name, res, plugin='tifffile')
+    warnings.simplefilter('ignore')
+    tifffile.imwrite(args.out_file.name, result)