update examples to supoort python 2

Author: taigw

examples/demo_densecrf.py

@@ -3,6 +3,26 @@
 from PIL import Image
 import matplotlib.pyplot as plt
 
+def densecrf(I, P, param):
+    """
+    input parameters:
+        I    : a numpy array of shape [H, W, C], where C should be 3.
+               type of I should be np.uint8, and the values are in [0, 255]
+        P    : a probability map of shape [H, W, L], where L is the number of classes
+               type of P should be np.float32
+        param: a tuple giving parameters of CRF (w1, alpha, beta, w2, gamma, it), where
+                w1    :   weight of bilateral term, e.g. 10.0
+                alpha :   spatial distance std, e.g., 80
+                beta  :   rgb value std, e.g., 15
+                w2    :   weight of spatial term, e.g., 3.0
+                gamma :   spatial distance std for spatial term, e.g., 3
+                it    :   iteration number, e.g., 5
+    output parameters:
+        out  : a numpy array of shape [H, W], where pixel values represent class indices. 
+    """
+    out = denseCRF.densecrf(I, P, param) 
+    return out   
+
 def convert_label_to_probability_map(label, color_list):
     [H, W, _] = label.shape
     C = len(color_list)
@@ -50,7 +70,7 @@ def demo_densecrf1():
     gamma = 3     # spatial std
     it    = 5.0   # iteration
     param = (w1, alpha, beta, w2, gamma, it)
-    lab = denseCRF.densecrf(Iq, prob, param)
+    lab = densecrf(Iq, prob, param)
     lab = Image.fromarray(lab*255)
     plt.subplot(1,3,1); plt.axis('off'); plt.imshow(I); plt.title('input image')
     plt.subplot(1,3,2); plt.axis('off'); plt.imshow(L); plt.title('initial label')
@@ -76,7 +96,7 @@ def demo_densecrf2():
     gamma = 3     # spatial std
     it    = 5.0   # iteration
     param = (w1, alpha, beta, w2, gamma, it)
-    lab = denseCRF.densecrf(Iq, prob, param)
+    lab = densecrf(Iq, prob, param)
     lab = colorize_label_map(lab, color_list)
     lab = Image.fromarray(lab)
     plt.subplot(1,3,1); plt.axis('off'); plt.imshow(I); plt.title('input image')
@@ -90,6 +110,7 @@ def demo_densecrf2():
     print(" 1 -- Dense CRF example for a multi-class segmentation")
     print("please enter the index of an example:")
     method = input()
+    method = "{0:}".format(method)
     if(method == '0'):
         demo_densecrf1()
     elif(method == '1'):

examples/demo_densecrf3d.py

@@ -4,7 +4,52 @@
 from PIL import Image
 import matplotlib.pyplot as plt
 
-def demo_densecrf3d():
+def densecrf3d(I, P, param):
+    """
+    input parameters:
+        I: a numpy array of shape [D, H, W, C], where C is the channel number
+           type of I should be np.uint8, and the values are in [0, 255]
+        P: a probability map of shape [D, H, W, L], where L is the number of classes
+           type of P should be np.float32
+        param: a tuple giving parameters of CRF. see the following two examples for details.
+    """
+    return denseCRF3D.densecrf3d(I, P, param)
+
+def demo_densecrf3d_1():
+    I1Nii = nibabel.load('../data/2013_12_1_img.nii.gz')
+    PNii  = nibabel.load('../data/2013_12_1_init.nii.gz')
+    I1 = I1Nii.get_data()
+    P  = PNii.get_data()
+
+    # convert input to intenstiy range of [0, 255]
+    I = np.asarray([I1], np.float32)
+    I = np.transpose(I, [1, 2, 3, 0])
+    I = I / I.max()* 255
+    I = np.asarray(I, np.uint8)
+
+    # probability map for each class
+    P = 0.5 + (P - 0.5) * 0.8
+    P = np.asarray([1.0 - P, P], np.float32)
+    P = np.transpose(P, [1, 2, 3, 0])
+
+    dense_crf_param = {}
+    dense_crf_param['MaxIterations'] = 2.0
+    dense_crf_param['PosW'] = 2.0
+    dense_crf_param['PosRStd'] = 5
+    dense_crf_param['PosCStd'] = 5
+    dense_crf_param['PosZStd'] = 5
+    dense_crf_param['BilateralW'] = 3.0
+    dense_crf_param['BilateralRStd'] = 5.0
+    dense_crf_param['BilateralCStd'] = 5.0
+    dense_crf_param['BilateralZStd'] = 5.0
+    dense_crf_param['ModalityNum'] = 1
+    dense_crf_param['BilateralModsStds'] = (5.0,)
+
+    lab = densecrf3d(I, P, dense_crf_param)
+    labNii = nibabel.Nifti1Image(lab, np.eye(4))
+    nibabel.save(labNii, '../data/seg_densecrf.nii.gz')
+
+def demo_densecrf3d_2():
     data_root  = '../dependency/densecrf3d/applicationAndExamples/example/'
     I1Nii = nibabel.load(data_root + 'Flair_normalized.nii.gz')
     I2Nii = nibabel.load(data_root + 'DWI_normalized.nii.gz')
@@ -36,14 +81,24 @@ def demo_densecrf3d():
     dense_crf_param['BilateralCStd'] = 5.0
     dense_crf_param['BilateralZStd'] = 5.0
     dense_crf_param['ModalityNum'] = 2
-    dense_crf_param['BilateralModsStds'] = (5.0,5.0)
+    dense_crf_param['BilateralModsStds'] = (5.0, 5.0)
 
-    lab = denseCRF3D.densecrf3d(I, P, dense_crf_param)
+    lab = densecrf3d(I, P, dense_crf_param)
     labNii = nibabel.Nifti1Image(lab, np.eye(4))
     nibabel.save(labNii, data_root + 'results/lesionSegMap.nii.gz')
 
 if __name__ == "__main__":
-    demo_densecrf3d()
-
+    print("example list")
+    print(" 0 -- 3D Dense CRF example for single-modal segmentation")
+    print(" 1 -- 3D Dense CRF example for multi-modal segmentation")
+    print("please enter the index of an example:")
+    method = input()
+    method = "{0:}".format(method)
+    if(method == '0'):
+        demo_densecrf3d_1()
+    elif(method == '1'):
+        demo_densecrf3d_2()
+    else:
+        print("invalid number : {0:}".format(method))
 
 

examples/demo_maxflow.py

@@ -106,6 +106,7 @@ def test_interactive_max_flow3d():
     print(" 3 -- 3D max flow with interactions")
     print("please enter the index of an example:")
     method = input()
+    method = "{0:}".format(method)
     if(method == '0'):
         demo_maxflow()
     elif(method == '1'):

setup.py

@@ -60,23 +60,28 @@
 description = 'An open-source toolkit for conditional random field (CRF) and dense CRF'
 
 # Get the long description
-with open('README.md', encoding='utf-8') as f:
-    long_description = f.read()
+if(sys.version[0] == '2'):
+    import io
+    with io.open('README.md', 'r', encoding='utf-8') as f:
+        long_description = f.read()
+else:
+    with open('README.md', encoding='utf-8') as f:
+        long_description = f.read()
 
 
 setup(name=package_name,
-      version = "0.0.1",
+      version = "0.0.5",
       author  ='Guotai Wang',
       author_email = '[email protected]',
       description  = description,
       long_description = long_description,
       long_description_content_type = 'text/markdown',
       url      = 'https://github.com/taigw/SimpleCRF',
-      license  = 'MIT',
+      license  = 'BSD',
       packages = setuptools.find_packages(),
       ext_modules = [module1, module2, module3],
       classifiers=[
-            'License :: OSI Approved :: MIT License',
+            'License :: OSI Approved :: BSD License',
             'Programming Language :: Python',
             'Programming Language :: Python :: 2',
             'Programming Language :: Python :: 3',