bringing git up to date with what is on stanford's copy

ImageCollection.py

@@ -2,9 +2,11 @@
 import matplotlib.pyplot as plt
 import os
 from PIL import Image
+from libtiff import TIFFimage
 import time
 import json
 from Rectangle import Rectangle
+import traceback,sys
 #from imageSourceMM import imageSource
 
 
@@ -89,8 +91,11 @@ def file_has_metadata(self,path):
         return 'txt' in theext
 
     def saveData(self,data):
-        img = Image.fromarray(data)
-        img.save(self.imagePath)
+        #img = Image.fromarray(data)
+        #img.save(self.imagePath)
+        tiff = TIFFimage(data, description='')
+        tiff.write_file(self.imagePath, compression='none')
+        del tiff
 
     def contains_rect(self,box):
         return self.boundBox.contains_rect(box)
@@ -100,6 +105,7 @@ def contains_point(self,x,y):
     def getData(self):
         img=Image.open(self.imagePath,mode='r')
         thedata=img.getdata()
+
         (width,height)=img.size
         data=np.reshape(np.array(thedata,np.dtype('uint8')),(height,width))
         return data
@@ -120,10 +126,28 @@ def __init__(self,rootpath,imageClass=MyImage,imageSource=None,axis=None):
         self.matplot_images=[]
         self.minvalue=0
         self.maxvalue=512
-
+
+    def display8bit(self,image, display_min, display_max): 
+        image = np.array(image, copy=True)
+        image.clip(display_min, display_max, out=image)
+        image -= display_min
+        image //= (display_max - display_min + 1) / 256.
+        return image.astype(np.uint8)
+
+    def lut_convert16as8bit(self,image, display_min, display_max) :
+        lut = np.arange(2**16, dtype='uint16')
+        lut = self.display8bit(lut, display_min, display_max)
+        return np.take(lut, image)
+
+
+
     def get_pixel_size(self):
         return self.imageSource.get_pixel_size()
 
+    def get_image_size_um(self):
+        (fw,fh)=self.imageSource.get_frame_size_um()
+        return (fw,fh)
+
     def set_view_home(self,box=None):
         if box==None:
             self.axis.set_xlim(left=self.bigBox.left,right=self.bigBox.right)
@@ -168,9 +192,15 @@ def add_image_at(self,x,y):
         #go get an image at x,y
         try:
             (thedata,bbox)=self.imageSource.take_image(x,y)
+            if thedata.dtype == np.uint16:
+                print "converting"
+                maxval=self.imageSource.get_max_pixel_value()
+                thedata=self.lut_convert16as8bit(thedata,0,maxval)
+
         except:
             #todo handle this better
             print "ahh no! imageSource failed us"
+            traceback.print_exc(file=sys.stdout)
         print "hmm.. bbox is"
         bbox.printRect()
         print "x,y is",x,y
@@ -263,6 +293,9 @@ def printBoundBoxes(self):
     def loadImageCollection(self):
         #list all metadata files in rootdir
         testimage=self.imageClass()
+        if not os.path.isdir(self.rootpath):
+            os.makedirs(self.rootpath)
+
         metafiles=[os.path.join(self.rootpath,f) for f in os.listdir(self.rootpath) if f.endswith('.txt') ]
 
         print "loading metadata"

MosaicImage.py

@@ -132,7 +132,7 @@ def __init__(self,axis,one_axis,two_axis,corr_axis,imgSrc,rootPath):
         self.oneImage=None
         self.twoImage=None
         self.corrImage=None
-
+        self.imgSrc = imgSrc
         self.imgCollection=ImageCollection(rootpath=rootPath,imageSource=imgSrc,axis=self.axis)
 
         (x,y)=imgSrc.get_xy()
@@ -141,9 +141,8 @@ def __init__(self,axis,one_axis,two_axis,corr_axis,imgSrc,rootPath):
         self.imgCollection.loadImageCollection()
 
 
-        self.maxvalue=255
-        imgSrc.set_channel('Violet')
-        imgSrc.set_exposure(250)
+        self.maxvalue=512
+
 
         self.axis.set_title('Mosaic Image')
 
@@ -490,8 +489,11 @@ def align_by_sift(self,xy1,xy2,window=70):
 
         #one_cuta=np.minimum(one_cut*256.0/self.maxvalue,255.0).astype(np.uint8)
         #two_cuta=np.minimum(two_cut*256.0/self.maxvalue,255.0).astype(np.uint8)
-        one_cuta=cv2.equalizeHist(one_cut)
-        two_cuta=cv2.equalizeHist(two_cut)
+        one_cuta = np.copy(one_cut)
+        two_cuta = np.copy(two_cut)
+
+        one_cuta=cv2.equalizeHist(one_cuta)
+        two_cuta=cv2.equalizeHist(two_cuta)
 
 
         sift = cv2.SIFT(nfeatures=500,contrastThreshold=.2)
@@ -502,8 +504,8 @@ def align_by_sift(self,xy1,xy2,window=70):
 
 
 
-        img_one = cv2.drawKeypoints(one_cuta,kp1)
-        img_two = cv2.drawKeypoints(two_cuta,kp2)
+        #img_one = cv2.drawKeypoints(one_cut,kp1)
+        #img_two = cv2.drawKeypoints(two_cut,kp2)
 
 
         #image2=self.two_axis.imshow(img_two)
@@ -597,13 +599,13 @@ def align_by_sift(self,xy1,xy2,window=70):
             print (dx_um,dy_um)
 
 
-            self.paintImageOne(img_one,xy=xy1)
-            self.paintImageTwo(img_two,xy=xy2,xyp=(x2-dx_um,y2-dy_um))
+            self.paintImageOne(one_cut,xy=xy1)
+            self.paintImageTwo(two_cut,xy=xy2,xyp=(x2-dx_um,y2-dy_um))
 
             return ((dx_um,dy_um),len(bestInlierIdx))
         else:
-            self.paintImageOne(img_one,xy=xy1)
-            self.paintImageTwo(img_two,xy=xy2)
+            self.paintImageOne(one_cut,xy=xy1)
+            self.paintImageTwo(two_cut,xy=xy2)
 
             return ((0.0,0.0),0)