Update crf.py

napari_cellseg3d/code_models/crf.py

@@ -1,4 +1,4 @@
-"""Implements the CRF post-processing step for the WNet3D.
+"""Implements the CRF post-processing step for WNet3D.
 
 The CRF requires the following parameters:
 
@@ -16,7 +16,8 @@
 Philipp Krähenbühl and Vladlen Koltun
 NIPS 2011
 
-Implemented using the pydense library available at https://github.com/lucasb-eyer/pydensecrf.
+Implemented using the pydensecrf library available at https://github.com/lucasb-eyer/pydensecrf.
+However, this is not maintained, thus we maintain this pacakge at https://github.com/AdaptiveMotorControlLab/pydensecrf.
 """
 
 import importlib
@@ -37,33 +38,11 @@
         unary_from_softmax,
     )
 
-__author__ = "Yves Paychère, Colin Hofmann, Cyril Achard"
-__credits__ = [
-    "Yves Paychère",
-    "Colin Hofmann",
-    "Cyril Achard",
-    "Philipp Krähenbühl",
-    "Vladlen Koltun",
-    "Liang-Chieh Chen",
-    "George Papandreou",
-    "Iasonas Kokkinos",
-    "Kevin Murphy",
-    "Alan L. Yuille",
-    "Xide Xia",
-    "Brian Kulis",
-    "Lucas Beyer",
-]
-
-
 def correct_shape_for_crf(image, desired_dims=4):
     """Corrects the shape of the image to be compatible with the CRF post-processing step."""
     logger.debug(f"Correcting shape for CRF, desired_dims={desired_dims}")
     logger.debug(f"Image shape: {image.shape}")
     if len(image.shape) > desired_dims:
-        # if image.shape[0] > 1:
-        #     raise ValueError(
-        #         f"Image shape {image.shape} might have several channels"
-        #     )
         image = np.squeeze(image, axis=0)
     elif len(image.shape) < desired_dims:
         image = np.expand_dims(image, axis=0)
@@ -72,7 +51,7 @@ def correct_shape_for_crf(image, desired_dims=4):
 
 
 def crf_batch(images, probs, sa, sb, sg, w1, w2, n_iter=5):
-    """CRF post-processing step for the W-Net, applied to a batch of images.
+    """CRF post-processing step for the WNet3D, applied to a batch of images.
 
     Args:
         images (np.ndarray): Array of shape (N, C, H, W, D) containing the input images.
@@ -100,7 +79,7 @@ def crf_batch(images, probs, sa, sb, sg, w1, w2, n_iter=5):
 
 
 def crf(image, prob, sa, sb, sg, w1, w2, n_iter=5):
-    """Implements the CRF post-processing step for the W-Net.
+    """Implements the CRF post-processing step for the WNet3D.
 
     Inspired by https://arxiv.org/abs/1210.5644, https://arxiv.org/abs/1606.00915 and https://arxiv.org/abs/1711.08506.
     Implemented using the pydensecrf library.
@@ -120,18 +99,14 @@ def crf(image, prob, sa, sb, sg, w1, w2, n_iter=5):
     """
     if not CRF_INSTALLED:
         logger.info(
-            "pydensecrf not installed, CRF post-processing will not be available. "
-            "Please install by running : pip install pydensecrf@git+https://github.com/lucasb-eyer/pydensecrf.git#egg=master"
-            "This is not a hard requirement, you do not need it to install it unless you want to use the CRF post-processing step."
+            "pydensecrf not installed, therefore CRF post-processing will not be available! Please install the package. "
+            "Please install by running: pip install pydensecrf2 "
         )
         return None
 
     d = dcrf.DenseCRF(
         image.shape[1] * image.shape[2] * image.shape[3], prob.shape[0]
     )
-    # print(f"Image shape : {image.shape}")
-    # print(f"Prob shape : {prob.shape}")
-    # d = dcrf.DenseCRF(262144, 3) # npoints, nlabels
 
     # Get unary potentials from softmax probabilities
     U = unary_from_softmax(prob)
@@ -165,7 +140,7 @@ def crf(image, prob, sa, sb, sg, w1, w2, n_iter=5):
 
 
 def crf_with_config(image, prob, config: CRFConfig = None, log=logger.info):
-    """Implements the CRF post-processing step for the W-Net.
+    """Implements the CRF post-processing step for the WNet3D.
 
     Args:
         image (np.ndarray): Array of shape (C, H, W, D) containing the input image.
@@ -202,7 +177,7 @@ def crf_with_config(image, prob, config: CRFConfig = None, log=logger.info):
 
 
 class CRFWorker(GeneratorWorker):
-    """Worker for the CRF post-processing step for the W-Net."""
+    """Worker for the CRF post-processing step for the WNet3D."""
 
     def __init__(
         self,
@@ -230,14 +205,12 @@ def __init__(
         self.log = log
 
     def _run_crf_job(self):
-        """Runs the CRF post-processing step for the W-Net."""
+        """Runs the CRF post-processing step for the WNet3D."""
         if not CRF_INSTALLED:
             logger.info(
-                "pydensecrf not installed, CRF post-processing will not be available. "
-                "Please install by running : pip install pydensecrf@git+https://github.com/lucasb-eyer/pydensecrf.git#egg=master"
-                "This is not a hard requirement, you do not need it to install it unless you want to use the CRF post-processing step."
+                "pydensecrf not installed, therefore CRF post-processing will not be available! Please install the package. "
+                "Please install by running: pip install pydensecrf2 "
             )
-        # raise ImportError("pydensecrf is not installed.")
 
         if len(self.images) != len(self.labels):
             raise ValueError("Number of images and labels must be the same.")