stackreg

environment.yml

@@ -7,6 +7,7 @@ dependencies:
   - openpyxl
   - pandas
   - pydicom
+  - pystackreg
   - pypubsub
   - read-roi
   - scikit-image

imagepy/menus/Plugins/StackReg/stackreg_plgs.py

@@ -0,0 +1,57 @@
+from imagepy.core.engine import Filter, Simple
+from imagepy import IPy
+from pystackreg import StackReg
+import numpy as np
+import pandas as pd
+from skimage import transform as tf
+from imagepy.core.manager import TableManager
+
+class Register(Simple):
+	title = 'Stack Register'
+	note = ['8-bit', '16-bit', 'int', 'float', 'stack']
+
+	para = {'trans':'RIGID_BODY', 'ref':'previous', 'tab':False, 'new':'Inplace'}
+	view = [(list, 'trans', ['TRANSLATION', 'RIGID_BODY', 'SCALED_ROTATION', 'AFFINE', 'BILINEAR'], str,  'transform', ''),
+			(list, 'ref', ['previous', 'first', 'mean'], str, 'image', ''),
+			(list, 'new', ['Inplace', 'New', 'None'], str, 'reference', ''),
+			(bool, 'tab', 'show table')]
+
+	def run(self, ips, imgs, para = None):
+		news = np.array(imgs)
+		sr = StackReg(eval('StackReg.%s'%para['trans']))
+		sr.register_stack(news, reference=para['ref'])
+		mats = sr._tmats.reshape((sr._tmats.shape[0],-1))
+		if para['tab']: IPy.show_table(pd.DataFrame(
+			mats, columns=['A%d'%(i+1) for i in range(mats.shape[1])]), title='%s-Tmats'%ips.title)
+		if para['new'] == 'None': return
+		for i in range(sr._tmats.shape[0]):
+			tform = tf.ProjectiveTransform(matrix=sr._tmats[i])
+			if para['new'] == 'Inplace':
+				imgs[i] = tf.warp(imgs[i], tform)*imgs[i].max()
+			if para['new'] == 'New':
+				news[i] = tf.warp(imgs[i], tform)*imgs[i].max()
+		if para['new'] == 'New': IPy.show_img(news, '%s-reg'%ips.title)
+
+class Transform(Simple):
+	title = 'Register By Mats'
+	note = ['all']
+
+	para = {'mat':None, 'new':True}
+	view = [('tab', 'mat', 'transfrom', 'matrix'),
+			(bool, 'new', 'new image')]
+
+	def run(self, ips, imgs, para = None):
+		mats = TableManager.get(para['mat']).data.values
+		if len(imgs) != len(mats):
+			IPy.alert('image stack must has the same length as transfrom mats!')
+			return
+		newimgs = []
+		for i in range(len(mats)):
+			tform = tf.ProjectiveTransform(matrix=mats[i].reshape((3,3)))
+			img = tf.warp(imgs[i], tform)
+			img -= imgs[i].min(); img *= imgs[i].max() - imgs[i].min()
+			if para['new']: newimgs.append(img)
+			else: imgs[i] = img
+		if para['new']: IPy.show_img(newimgs, '%s-trans'%ips.title)
+
+plgs = [Register, Transform]

imagepy/menus/Plugins/__init__.py

@@ -1 +1 @@
-catlog = ['New', 'Macros', 'Manager', '-', 'Install', 'Contribute', 'update_plg', '-', 'screencap_plg', 'Games']
+catlog = ['New', 'Macros', 'Manager', '-', 'Install', 'Contribute', 'update_plg', '-', 'StackReg', 'Games', 'screencap_plg']

imagepy/menus/Process/Filters/classic_plgs.py

@@ -170,7 +170,6 @@ class Variance(Filter):
 
     #process
     def run(self, ips, snap, img, para = None):
-        print(snap.dtype, img.dtype)
         nimg.uniform_filter(snap**2, para['size'], output=img)
         img -= nimg.uniform_filter(snap, para['size'])**2
 

setup.py

@@ -30,6 +30,7 @@ def get_data_files():
             'read_roi',
             'numpy-stl',
             'pydicom',
+            'pystackreg',
             'pandas',
             'xlrd',
             'xlwt',